Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.1% → 39.0%

Time: 2.4min

Alternatives: 46

Speedup: 2.1×

• 88.8% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (+
  (-
   (+
    (+
     (-
      (* (- (* x y) (* z t)) (- (* a b) (* c i)))
      (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
     (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
    (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
   (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
  (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 30.1% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (+
  (-
   (+
    (+
     (-
      (* (- (* x y) (* z t)) (- (* a b) (* c i)))
      (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
     (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
    (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
   (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
  (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 39.0% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y4 - i \cdot y5\\ t_2 := z \cdot t - x \cdot y\\ t_3 := y0 \cdot y5 - y1 \cdot y4\\ t_4 := y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot t_3 + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ t_5 := \left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ t_6 := k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;j \leq -1 \cdot 10^{+200}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot t_3 + t \cdot t_1\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -5.4 \cdot 10^{+165}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;j \leq -1.75 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot t_2 - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq -3.4 \cdot 10^{+96}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.7 \cdot 10^{+41}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;j \leq -2.3 \cdot 10^{-23}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot t_1\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -9 \cdot 10^{-121}:\\ \;\;\;\;c \cdot \left(\left(i \cdot t_2 + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 4.6 \cdot 10^{-276}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;j \leq 4.2 \cdot 10^{-202}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;j \leq 5.5 \cdot 10^{-41}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+127}:\\ \;\;\;\;t_4\\ \mathbf{else}:\\ \;\;\;\;t_5\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y4) (* i y5)))
        (t_2 (- (* z t) (* x y)))
        (t_3 (- (* y0 y5) (* y1 y4)))
        (t_4
         (*
          y3
          (+
           (* y (- (* c y4) (* a y5)))
           (+ (* j t_3) (* z (- (* a y1) (* c y0)))))))
        (t_5 (* (* i j) (- (* x y1) (* t y5))))
        (t_6
         (*
          k
          (+
           (+ (* y (- (* i y5) (* b y4))) (* y2 (- (* y1 y4) (* y0 y5))))
           (* z (- (* b y0) (* i y1)))))))
   (if (<= j -1e+200)
     (* j (+ (+ (* y3 t_3) (* t t_1)) (* x (- (* i y1) (* b y0)))))
     (if (<= j -5.4e+165)
       t_6
       (if (<= j -1.75e+112)
         (*
          a
          (-
           (* y5 (- (* t y2) (* y y3)))
           (- (* b t_2) (* y1 (- (* z y3) (* x y2))))))
         (if (<= j -3.4e+96)
           (* y3 (* y4 (- (* y c) (* j y1))))
           (if (<= j -1.7e+41)
             t_5
             (if (<= j -2.3e-23)
               (*
                t
                (+
                 (+ (* z (- (* c i) (* a b))) (* j t_1))
                 (* y2 (- (* a y5) (* c y4)))))
               (if (<= j -9e-121)
                 (*
                  c
                  (+
                   (+ (* i t_2) (* y0 (- (* x y2) (* z y3))))
                   (* y4 (- (* y y3) (* t y2)))))
                 (if (<= j 4.6e-276)
                   t_6
                   (if (<= j 4.2e-202)
                     t_4
                     (if (<= j 5.5e-41)
                       t_6
                       (if (<= j 1.9e+127) t_4 t_5)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y4) - (i * y5);
	double t_2 = (z * t) - (x * y);
	double t_3 = (y0 * y5) - (y1 * y4);
	double t_4 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_3) + (z * ((a * y1) - (c * y0)))));
	double t_5 = (i * j) * ((x * y1) - (t * y5));
	double t_6 = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))));
	double tmp;
	if (j <= -1e+200) {
		tmp = j * (((y3 * t_3) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	} else if (j <= -5.4e+165) {
		tmp = t_6;
	} else if (j <= -1.75e+112) {
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_2) - (y1 * ((z * y3) - (x * y2)))));
	} else if (j <= -3.4e+96) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.7e+41) {
		tmp = t_5;
	} else if (j <= -2.3e-23) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	} else if (j <= -9e-121) {
		tmp = c * (((i * t_2) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 4.6e-276) {
		tmp = t_6;
	} else if (j <= 4.2e-202) {
		tmp = t_4;
	} else if (j <= 5.5e-41) {
		tmp = t_6;
	} else if (j <= 1.9e+127) {
		tmp = t_4;
	} else {
		tmp = t_5;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = (b * y4) - (i * y5)
    t_2 = (z * t) - (x * y)
    t_3 = (y0 * y5) - (y1 * y4)
    t_4 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_3) + (z * ((a * y1) - (c * y0)))))
    t_5 = (i * j) * ((x * y1) - (t * y5))
    t_6 = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))))
    if (j <= (-1d+200)) then
        tmp = j * (((y3 * t_3) + (t * t_1)) + (x * ((i * y1) - (b * y0))))
    else if (j <= (-5.4d+165)) then
        tmp = t_6
    else if (j <= (-1.75d+112)) then
        tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_2) - (y1 * ((z * y3) - (x * y2)))))
    else if (j <= (-3.4d+96)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (j <= (-1.7d+41)) then
        tmp = t_5
    else if (j <= (-2.3d-23)) then
        tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))))
    else if (j <= (-9d-121)) then
        tmp = c * (((i * t_2) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
    else if (j <= 4.6d-276) then
        tmp = t_6
    else if (j <= 4.2d-202) then
        tmp = t_4
    else if (j <= 5.5d-41) then
        tmp = t_6
    else if (j <= 1.9d+127) then
        tmp = t_4
    else
        tmp = t_5
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y4) - (i * y5);
	double t_2 = (z * t) - (x * y);
	double t_3 = (y0 * y5) - (y1 * y4);
	double t_4 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_3) + (z * ((a * y1) - (c * y0)))));
	double t_5 = (i * j) * ((x * y1) - (t * y5));
	double t_6 = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))));
	double tmp;
	if (j <= -1e+200) {
		tmp = j * (((y3 * t_3) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	} else if (j <= -5.4e+165) {
		tmp = t_6;
	} else if (j <= -1.75e+112) {
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_2) - (y1 * ((z * y3) - (x * y2)))));
	} else if (j <= -3.4e+96) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.7e+41) {
		tmp = t_5;
	} else if (j <= -2.3e-23) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	} else if (j <= -9e-121) {
		tmp = c * (((i * t_2) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 4.6e-276) {
		tmp = t_6;
	} else if (j <= 4.2e-202) {
		tmp = t_4;
	} else if (j <= 5.5e-41) {
		tmp = t_6;
	} else if (j <= 1.9e+127) {
		tmp = t_4;
	} else {
		tmp = t_5;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (b * y4) - (i * y5)
	t_2 = (z * t) - (x * y)
	t_3 = (y0 * y5) - (y1 * y4)
	t_4 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_3) + (z * ((a * y1) - (c * y0)))))
	t_5 = (i * j) * ((x * y1) - (t * y5))
	t_6 = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))))
	tmp = 0
	if j <= -1e+200:
		tmp = j * (((y3 * t_3) + (t * t_1)) + (x * ((i * y1) - (b * y0))))
	elif j <= -5.4e+165:
		tmp = t_6
	elif j <= -1.75e+112:
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_2) - (y1 * ((z * y3) - (x * y2)))))
	elif j <= -3.4e+96:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif j <= -1.7e+41:
		tmp = t_5
	elif j <= -2.3e-23:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))))
	elif j <= -9e-121:
		tmp = c * (((i * t_2) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
	elif j <= 4.6e-276:
		tmp = t_6
	elif j <= 4.2e-202:
		tmp = t_4
	elif j <= 5.5e-41:
		tmp = t_6
	elif j <= 1.9e+127:
		tmp = t_4
	else:
		tmp = t_5
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(b * y4) - Float64(i * y5))
	t_2 = Float64(Float64(z * t) - Float64(x * y))
	t_3 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_4 = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * t_3) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))))
	t_5 = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)))
	t_6 = Float64(k * Float64(Float64(Float64(y * Float64(Float64(i * y5) - Float64(b * y4))) + Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))))
	tmp = 0.0
	if (j <= -1e+200)
		tmp = Float64(j * Float64(Float64(Float64(y3 * t_3) + Float64(t * t_1)) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (j <= -5.4e+165)
		tmp = t_6;
	elseif (j <= -1.75e+112)
		tmp = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) - Float64(Float64(b * t_2) - Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))));
	elseif (j <= -3.4e+96)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (j <= -1.7e+41)
		tmp = t_5;
	elseif (j <= -2.3e-23)
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * t_1)) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= -9e-121)
		tmp = Float64(c * Float64(Float64(Float64(i * t_2) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= 4.6e-276)
		tmp = t_6;
	elseif (j <= 4.2e-202)
		tmp = t_4;
	elseif (j <= 5.5e-41)
		tmp = t_6;
	elseif (j <= 1.9e+127)
		tmp = t_4;
	else
		tmp = t_5;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (b * y4) - (i * y5);
	t_2 = (z * t) - (x * y);
	t_3 = (y0 * y5) - (y1 * y4);
	t_4 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_3) + (z * ((a * y1) - (c * y0)))));
	t_5 = (i * j) * ((x * y1) - (t * y5));
	t_6 = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))));
	tmp = 0.0;
	if (j <= -1e+200)
		tmp = j * (((y3 * t_3) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	elseif (j <= -5.4e+165)
		tmp = t_6;
	elseif (j <= -1.75e+112)
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_2) - (y1 * ((z * y3) - (x * y2)))));
	elseif (j <= -3.4e+96)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (j <= -1.7e+41)
		tmp = t_5;
	elseif (j <= -2.3e-23)
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	elseif (j <= -9e-121)
		tmp = c * (((i * t_2) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (j <= 4.6e-276)
		tmp = t_6;
	elseif (j <= 4.2e-202)
		tmp = t_4;
	elseif (j <= 5.5e-41)
		tmp = t_6;
	elseif (j <= 1.9e+127)
		tmp = t_4;
	else
		tmp = t_5;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * t$95$3), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(k * N[(N[(N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1e+200], N[(j * N[(N[(N[(y3 * t$95$3), $MachinePrecision] + N[(t * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5.4e+165], t$95$6, If[LessEqual[j, -1.75e+112], N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * t$95$2), $MachinePrecision] - N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -3.4e+96], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.7e+41], t$95$5, If[LessEqual[j, -2.3e-23], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -9e-121], N[(c * N[(N[(N[(i * t$95$2), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.6e-276], t$95$6, If[LessEqual[j, 4.2e-202], t$95$4, If[LessEqual[j, 5.5e-41], t$95$6, If[LessEqual[j, 1.9e+127], t$95$4, t$95$5]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if j < -9.9999999999999997e199

   1. Initial program 24.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 69.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -9.9999999999999997e199 < j < -5.3999999999999999e165 or -9.0000000000000007e-121 < j < 4.59999999999999963e-276 or 4.1999999999999997e-202 < j < 5.50000000000000022e-41

   1. Initial program 44.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 60.2%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if -5.3999999999999999e165 < j < -1.74999999999999998e112

   1. Initial program 37.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf 64.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if -1.74999999999999998e112 < j < -3.4000000000000001e96

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 75.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 100.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 100.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -3.4000000000000001e96 < j < -1.69999999999999999e41 or 1.8999999999999999e127 < j

   1. Initial program 26.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 57.1%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.1%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 55.1%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]

   if -1.69999999999999999e41 < j < -2.3000000000000001e-23

   1. Initial program 42.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in t around inf 58.3%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -2.3000000000000001e-23 < j < -9.0000000000000007e-121

   1. Initial program 19.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 58.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 4.59999999999999963e-276 < j < 4.1999999999999997e-202 or 5.50000000000000022e-41 < j < 1.8999999999999999e127

   1. Initial program 27.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 68.9%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 62.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1 \cdot 10^{+200}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -5.4 \cdot 10^{+165}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.75 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot \left(z \cdot t - x \cdot y\right) - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq -3.4 \cdot 10^{+96}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.7 \cdot 10^{+41}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;j \leq -2.3 \cdot 10^{-23}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -9 \cdot 10^{-121}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 4.6 \cdot 10^{-276}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 4.2 \cdot 10^{-202}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;j \leq 5.5 \cdot 10^{-41}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+127}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 53.2% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(c \cdot y0 - a \cdot y1\right) \cdot \left(x \cdot y2 - z \cdot y3\right)\\ t_2 := \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\\ t_3 := \left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)\\ t_4 := \sqrt[3]{t_3}\\ t_5 := \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\\ t_6 := \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{if}\;\left(\left(\left(\left(t_3 + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right) + t_1\right) + t_5\right) + t_2\right) + t_6 \leq \infty:\\ \;\;\;\;t_6 + \left(\left(t_5 + \mathsf{fma}\left(t_4 \cdot t_4, t_4, t_1 + \mathsf{fma}\left(b, y0, i \cdot \left(-y1\right)\right) \cdot \left(z \cdot k - x \cdot j\right)\right)\right) + t_2\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (- (* c y0) (* a y1)) (- (* x y2) (* z y3))))
        (t_2 (* (- (* t y2) (* y y3)) (- (* a y5) (* c y4))))
        (t_3 (* (- (* a b) (* c i)) (- (* x y) (* z t))))
        (t_4 (cbrt t_3))
        (t_5 (* (- (* t j) (* y k)) (- (* b y4) (* i y5))))
        (t_6 (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5)))))
   (if (<=
        (+
         (+
          (+ (+ (+ t_3 (* (- (* x j) (* z k)) (- (* i y1) (* b y0)))) t_1) t_5)
          t_2)
         t_6)
        INFINITY)
     (+
      t_6
      (+
       (+
        t_5
        (fma
         (* t_4 t_4)
         t_4
         (+ t_1 (* (fma b y0 (* i (- y1))) (- (* z k) (* x j))))))
       t_2))
     (*
      y3
      (+
       (* y (- (* c y4) (* a y5)))
       (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = ((c * y0) - (a * y1)) * ((x * y2) - (z * y3));
	double t_2 = ((t * y2) - (y * y3)) * ((a * y5) - (c * y4));
	double t_3 = ((a * b) - (c * i)) * ((x * y) - (z * t));
	double t_4 = cbrt(t_3);
	double t_5 = ((t * j) - (y * k)) * ((b * y4) - (i * y5));
	double t_6 = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	double tmp;
	if ((((((t_3 + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + t_1) + t_5) + t_2) + t_6) <= ((double) INFINITY)) {
		tmp = t_6 + ((t_5 + fma((t_4 * t_4), t_4, (t_1 + (fma(b, y0, (i * -y1)) * ((z * k) - (x * j)))))) + t_2);
	} else {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(Float64(c * y0) - Float64(a * y1)) * Float64(Float64(x * y2) - Float64(z * y3)))
	t_2 = Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(a * y5) - Float64(c * y4)))
	t_3 = Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t)))
	t_4 = cbrt(t_3)
	t_5 = Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(b * y4) - Float64(i * y5)))
	t_6 = Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5)))
	tmp = 0.0
	if (Float64(Float64(Float64(Float64(Float64(t_3 + Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(i * y1) - Float64(b * y0)))) + t_1) + t_5) + t_2) + t_6) <= Inf)
		tmp = Float64(t_6 + Float64(Float64(t_5 + fma(Float64(t_4 * t_4), t_4, Float64(t_1 + Float64(fma(b, y0, Float64(i * Float64(-y1))) * Float64(Float64(z * k) - Float64(x * j)))))) + t_2));
	else
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[t$95$3, 1/3], $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[(N[(N[(t$95$3 + N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision] + t$95$5), $MachinePrecision] + t$95$2), $MachinePrecision] + t$95$6), $MachinePrecision], Infinity], N[(t$95$6 + N[(N[(t$95$5 + N[(N[(t$95$4 * t$95$4), $MachinePrecision] * t$95$4 + N[(t$95$1 + N[(N[(b * y0 + N[(i * (-y1)), $MachinePrecision]), $MachinePrecision] * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0)))) < +inf.0

   1. Initial program 91.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   4. Applied egg-rr 91.1%

      \[\leadsto \left(\left(\color{blue}{\mathsf{fma}\left(\sqrt[3]{\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)} \cdot \sqrt[3]{\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)}, \sqrt[3]{\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)}, -\left(\left(x \cdot j - z \cdot k\right) \cdot \mathsf{fma}\left(b, y0, -i \cdot y1\right) - \left(x \cdot y2 - z \cdot y3\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   if +inf.0 < (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0))))

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 57.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(\left(\left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right) + \left(c \cdot y0 - a \cdot y1\right) \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) \leq \infty:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + \left(\left(\left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right) + \mathsf{fma}\left(\sqrt[3]{\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)} \cdot \sqrt[3]{\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)}, \sqrt[3]{\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right)}, \left(c \cdot y0 - a \cdot y1\right) \cdot \left(x \cdot y2 - z \cdot y3\right) + \mathsf{fma}\left(b, y0, i \cdot \left(-y1\right)\right) \cdot \left(z \cdot k - x \cdot j\right)\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 53.2% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(\left(\left(\left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right) + \left(c \cdot y0 - a \cdot y1\right) \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{if}\;t_1 \leq \infty:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (+
          (+
           (+
            (+
             (+
              (* (- (* a b) (* c i)) (- (* x y) (* z t)))
              (* (- (* x j) (* z k)) (- (* i y1) (* b y0))))
             (* (- (* c y0) (* a y1)) (- (* x y2) (* z y3))))
            (* (- (* t j) (* y k)) (- (* b y4) (* i y5))))
           (* (- (* t y2) (* y y3)) (- (* a y5) (* c y4))))
          (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5))))))
   (if (<= t_1 INFINITY)
     t_1
     (*
      y3
      (+
       (* y (- (* c y4) (* a y5)))
       (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((c * y0) - (a * y1)) * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	}
	return tmp;
}

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((c * y0) - (a * y1)) * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_1 <= Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((c * y0) - (a * y1)) * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if t_1 <= math.inf:
		tmp = t_1
	else:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t))) + Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(i * y1) - Float64(b * y0)))) + Float64(Float64(Float64(c * y0) - Float64(a * y1)) * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(a * y5) - Float64(c * y4)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((c * y0) - (a * y1)) * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(N[(N[(N[(N[(N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, Infinity], t$95$1, N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0)))) < +inf.0

   1. Initial program 91.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   if +inf.0 < (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0))))

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 57.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(\left(\left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right) + \left(c \cdot y0 - a \cdot y1\right) \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) \leq \infty:\\ \;\;\;\;\left(\left(\left(\left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right) + \left(c \cdot y0 - a \cdot y1\right) \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 33.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_2 := i \cdot \left(y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\\ t_3 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ t_4 := \left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{if}\;y2 \leq -4.9 \cdot 10^{+185}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -1.8 \cdot 10^{+164}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y2 \leq -2.15 \cdot 10^{+148}:\\ \;\;\;\;\left(t \cdot a - k \cdot y0\right) \cdot \left(y2 \cdot y5\right)\\ \mathbf{elif}\;y2 \leq -2.3 \cdot 10^{+36}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -85000000:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y2 \leq -4.1 \cdot 10^{-89}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -5 \cdot 10^{-232}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq -3.6 \cdot 10^{-288}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;y2 \leq 7.8 \cdot 10^{-191}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 2.3 \cdot 10^{-110}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;y2 \leq 1.1 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y2 \leq 7.5 \cdot 10^{+130}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 6.5 \cdot 10^{+301}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (* y2 (+ (* k (- (* y1 y4) (* y0 y5))) (* t (- (* a y5) (* c y4))))))
        (t_2 (* i (* y5 (- (* y k) (* t j)))))
        (t_3 (* x (* y2 (- (* c y0) (* a y1)))))
        (t_4 (* (* z y3) (- (* a y1) (* c y0)))))
   (if (<= y2 -4.9e+185)
     t_1
     (if (<= y2 -1.8e+164)
       t_3
       (if (<= y2 -2.15e+148)
         (* (- (* t a) (* k y0)) (* y2 y5))
         (if (<= y2 -2.3e+36)
           (* y3 (* y4 (- (* y c) (* j y1))))
           (if (<= y2 -85000000.0)
             (* a (* y5 (- (* t y2) (* y y3))))
             (if (<= y2 -4.1e-89)
               (* i (* k (- (* y y5) (* z y1))))
               (if (<= y2 -5e-232)
                 t_2
                 (if (<= y2 -3.6e-288)
                   t_4
                   (if (<= y2 7.8e-191)
                     t_2
                     (if (<= y2 2.3e-110)
                       t_4
                       (if (<= y2 1.1e-70)
                         (* x (* y (- (* a b) (* c i))))
                         (if (<= y2 7.5e+130)
                           t_1
                           (if (<= y2 6.5e+301)
                             t_3
                             (* k (* y1 (- (* y2 y4) (* z i)))))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))));
	double t_2 = i * (y5 * ((y * k) - (t * j)));
	double t_3 = x * (y2 * ((c * y0) - (a * y1)));
	double t_4 = (z * y3) * ((a * y1) - (c * y0));
	double tmp;
	if (y2 <= -4.9e+185) {
		tmp = t_1;
	} else if (y2 <= -1.8e+164) {
		tmp = t_3;
	} else if (y2 <= -2.15e+148) {
		tmp = ((t * a) - (k * y0)) * (y2 * y5);
	} else if (y2 <= -2.3e+36) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (y2 <= -85000000.0) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y2 <= -4.1e-89) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (y2 <= -5e-232) {
		tmp = t_2;
	} else if (y2 <= -3.6e-288) {
		tmp = t_4;
	} else if (y2 <= 7.8e-191) {
		tmp = t_2;
	} else if (y2 <= 2.3e-110) {
		tmp = t_4;
	} else if (y2 <= 1.1e-70) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y2 <= 7.5e+130) {
		tmp = t_1;
	} else if (y2 <= 6.5e+301) {
		tmp = t_3;
	} else {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))))
    t_2 = i * (y5 * ((y * k) - (t * j)))
    t_3 = x * (y2 * ((c * y0) - (a * y1)))
    t_4 = (z * y3) * ((a * y1) - (c * y0))
    if (y2 <= (-4.9d+185)) then
        tmp = t_1
    else if (y2 <= (-1.8d+164)) then
        tmp = t_3
    else if (y2 <= (-2.15d+148)) then
        tmp = ((t * a) - (k * y0)) * (y2 * y5)
    else if (y2 <= (-2.3d+36)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (y2 <= (-85000000.0d0)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (y2 <= (-4.1d-89)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (y2 <= (-5d-232)) then
        tmp = t_2
    else if (y2 <= (-3.6d-288)) then
        tmp = t_4
    else if (y2 <= 7.8d-191) then
        tmp = t_2
    else if (y2 <= 2.3d-110) then
        tmp = t_4
    else if (y2 <= 1.1d-70) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y2 <= 7.5d+130) then
        tmp = t_1
    else if (y2 <= 6.5d+301) then
        tmp = t_3
    else
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))));
	double t_2 = i * (y5 * ((y * k) - (t * j)));
	double t_3 = x * (y2 * ((c * y0) - (a * y1)));
	double t_4 = (z * y3) * ((a * y1) - (c * y0));
	double tmp;
	if (y2 <= -4.9e+185) {
		tmp = t_1;
	} else if (y2 <= -1.8e+164) {
		tmp = t_3;
	} else if (y2 <= -2.15e+148) {
		tmp = ((t * a) - (k * y0)) * (y2 * y5);
	} else if (y2 <= -2.3e+36) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (y2 <= -85000000.0) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y2 <= -4.1e-89) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (y2 <= -5e-232) {
		tmp = t_2;
	} else if (y2 <= -3.6e-288) {
		tmp = t_4;
	} else if (y2 <= 7.8e-191) {
		tmp = t_2;
	} else if (y2 <= 2.3e-110) {
		tmp = t_4;
	} else if (y2 <= 1.1e-70) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y2 <= 7.5e+130) {
		tmp = t_1;
	} else if (y2 <= 6.5e+301) {
		tmp = t_3;
	} else {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))))
	t_2 = i * (y5 * ((y * k) - (t * j)))
	t_3 = x * (y2 * ((c * y0) - (a * y1)))
	t_4 = (z * y3) * ((a * y1) - (c * y0))
	tmp = 0
	if y2 <= -4.9e+185:
		tmp = t_1
	elif y2 <= -1.8e+164:
		tmp = t_3
	elif y2 <= -2.15e+148:
		tmp = ((t * a) - (k * y0)) * (y2 * y5)
	elif y2 <= -2.3e+36:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif y2 <= -85000000.0:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif y2 <= -4.1e-89:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif y2 <= -5e-232:
		tmp = t_2
	elif y2 <= -3.6e-288:
		tmp = t_4
	elif y2 <= 7.8e-191:
		tmp = t_2
	elif y2 <= 2.3e-110:
		tmp = t_4
	elif y2 <= 1.1e-70:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y2 <= 7.5e+130:
		tmp = t_1
	elif y2 <= 6.5e+301:
		tmp = t_3
	else:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y2 * Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))))
	t_2 = Float64(i * Float64(y5 * Float64(Float64(y * k) - Float64(t * j))))
	t_3 = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	t_4 = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)))
	tmp = 0.0
	if (y2 <= -4.9e+185)
		tmp = t_1;
	elseif (y2 <= -1.8e+164)
		tmp = t_3;
	elseif (y2 <= -2.15e+148)
		tmp = Float64(Float64(Float64(t * a) - Float64(k * y0)) * Float64(y2 * y5));
	elseif (y2 <= -2.3e+36)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (y2 <= -85000000.0)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (y2 <= -4.1e-89)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (y2 <= -5e-232)
		tmp = t_2;
	elseif (y2 <= -3.6e-288)
		tmp = t_4;
	elseif (y2 <= 7.8e-191)
		tmp = t_2;
	elseif (y2 <= 2.3e-110)
		tmp = t_4;
	elseif (y2 <= 1.1e-70)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y2 <= 7.5e+130)
		tmp = t_1;
	elseif (y2 <= 6.5e+301)
		tmp = t_3;
	else
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))));
	t_2 = i * (y5 * ((y * k) - (t * j)));
	t_3 = x * (y2 * ((c * y0) - (a * y1)));
	t_4 = (z * y3) * ((a * y1) - (c * y0));
	tmp = 0.0;
	if (y2 <= -4.9e+185)
		tmp = t_1;
	elseif (y2 <= -1.8e+164)
		tmp = t_3;
	elseif (y2 <= -2.15e+148)
		tmp = ((t * a) - (k * y0)) * (y2 * y5);
	elseif (y2 <= -2.3e+36)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (y2 <= -85000000.0)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (y2 <= -4.1e-89)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (y2 <= -5e-232)
		tmp = t_2;
	elseif (y2 <= -3.6e-288)
		tmp = t_4;
	elseif (y2 <= 7.8e-191)
		tmp = t_2;
	elseif (y2 <= 2.3e-110)
		tmp = t_4;
	elseif (y2 <= 1.1e-70)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y2 <= 7.5e+130)
		tmp = t_1;
	elseif (y2 <= 6.5e+301)
		tmp = t_3;
	else
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y2 * N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(i * N[(y5 * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -4.9e+185], t$95$1, If[LessEqual[y2, -1.8e+164], t$95$3, If[LessEqual[y2, -2.15e+148], N[(N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision] * N[(y2 * y5), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -2.3e+36], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -85000000.0], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -4.1e-89], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -5e-232], t$95$2, If[LessEqual[y2, -3.6e-288], t$95$4, If[LessEqual[y2, 7.8e-191], t$95$2, If[LessEqual[y2, 2.3e-110], t$95$4, If[LessEqual[y2, 1.1e-70], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 7.5e+130], t$95$1, If[LessEqual[y2, 6.5e+301], t$95$3, N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y2 < -4.89999999999999984e185 or 1.0999999999999999e-70 < y2 < 7.5000000000000003e130

   1. Initial program 37.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 59.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around 0 59.5%

      \[\leadsto \color{blue}{y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 59.5%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot k} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) \]

   6. Simplified 59.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot k - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -4.89999999999999984e185 < y2 < -1.79999999999999995e164 or 7.5000000000000003e130 < y2 < 6.4999999999999999e301

   1. Initial program 25.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 60.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -1.79999999999999995e164 < y2 < -2.1500000000000001e148

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 40.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y5 around inf 80.9%

      \[\leadsto \color{blue}{y2 \cdot \left(y5 \cdot \left(-1 \cdot \left(k \cdot y0\right) - -1 \cdot \left(a \cdot t\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 80.9%

         \[\leadsto \color{blue}{\left(y2 \cdot y5\right) \cdot \left(-1 \cdot \left(k \cdot y0\right) - -1 \cdot \left(a \cdot t\right)\right)} \]

      2. *-commutative 80.9%

         \[\leadsto \color{blue}{\left(y5 \cdot y2\right)} \cdot \left(-1 \cdot \left(k \cdot y0\right) - -1 \cdot \left(a \cdot t\right)\right) \]

      3. distribute-lft-out-- 80.9%

         \[\leadsto \left(y5 \cdot y2\right) \cdot \color{blue}{\left(-1 \cdot \left(k \cdot y0 - a \cdot t\right)\right)} \]

      4. *-commutative 80.9%

         \[\leadsto \left(y5 \cdot y2\right) \cdot \left(-1 \cdot \left(\color{blue}{y0 \cdot k} - a \cdot t\right)\right) \]

   6. Simplified 80.9%

      \[\leadsto \color{blue}{\left(y5 \cdot y2\right) \cdot \left(-1 \cdot \left(y0 \cdot k - a \cdot t\right)\right)} \]

   if -2.1500000000000001e148 < y2 < -2.29999999999999996e36

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 41.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 60.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 60.0%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 60.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -2.29999999999999996e36 < y2 < -8.5e7

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.7%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.7%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.7%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.7%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 59.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -8.5e7 < y2 < -4.0999999999999998e-89

   1. Initial program 23.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 46.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 61.8%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -4.0999999999999998e-89 < y2 < -4.9999999999999999e-232 or -3.6000000000000001e-288 < y2 < 7.7999999999999999e-191

   1. Initial program 34.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 43.5%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 43.5%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.5%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 43.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 49.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 49.6%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 49.6%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 49.6%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 49.6%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 49.6%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 49.6%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   if -4.9999999999999999e-232 < y2 < -3.6000000000000001e-288 or 7.7999999999999999e-191 < y2 < 2.3000000000000001e-110

   1. Initial program 38.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 53.4%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in z around inf 60.1%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 60.1%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   6. Simplified 60.1%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 2.3000000000000001e-110 < y2 < 1.0999999999999999e-70

   1. Initial program 45.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 55.6%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 64.7%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 6.4999999999999999e301 < y2

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 100.0%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 100.0%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 100.0%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 58.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -4.9 \cdot 10^{+185}:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq -1.8 \cdot 10^{+164}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -2.15 \cdot 10^{+148}:\\ \;\;\;\;\left(t \cdot a - k \cdot y0\right) \cdot \left(y2 \cdot y5\right)\\ \mathbf{elif}\;y2 \leq -2.3 \cdot 10^{+36}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -85000000:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y2 \leq -4.1 \cdot 10^{-89}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -5 \cdot 10^{-232}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\\ \mathbf{elif}\;y2 \leq -3.6 \cdot 10^{-288}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;y2 \leq 7.8 \cdot 10^{-191}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\\ \mathbf{elif}\;y2 \leq 2.3 \cdot 10^{-110}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;y2 \leq 1.1 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y2 \leq 7.5 \cdot 10^{+130}:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 6.5 \cdot 10^{+301}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 34.0% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_2 := \left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ t_3 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ t_4 := y \cdot k - t \cdot j\\ \mathbf{if}\;y2 \leq -3.4 \cdot 10^{+185}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -1.95 \cdot 10^{+164}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y2 \leq -2.2 \cdot 10^{+148}:\\ \;\;\;\;\left(t \cdot a - k \cdot y0\right) \cdot \left(y2 \cdot y5\right)\\ \mathbf{elif}\;y2 \leq -1.9 \cdot 10^{+36}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -24000:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y2 \leq -5.5 \cdot 10^{-89}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -4.5 \cdot 10^{-231}:\\ \;\;\;\;i \cdot \left(y5 \cdot t_4\right)\\ \mathbf{elif}\;y2 \leq -2.3 \cdot 10^{-286}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 4.3 \cdot 10^{-144}:\\ \;\;\;\;y5 \cdot \left(i \cdot t_4 + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq 5 \cdot 10^{-109}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 2.5 \cdot 10^{-69}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y2 \leq 7.5 \cdot 10^{+131}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 6.5 \cdot 10^{+301}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (* y2 (+ (* k (- (* y1 y4) (* y0 y5))) (* t (- (* a y5) (* c y4))))))
        (t_2 (* (* z y3) (- (* a y1) (* c y0))))
        (t_3 (* x (* y2 (- (* c y0) (* a y1)))))
        (t_4 (- (* y k) (* t j))))
   (if (<= y2 -3.4e+185)
     t_1
     (if (<= y2 -1.95e+164)
       t_3
       (if (<= y2 -2.2e+148)
         (* (- (* t a) (* k y0)) (* y2 y5))
         (if (<= y2 -1.9e+36)
           (* y3 (* y4 (- (* y c) (* j y1))))
           (if (<= y2 -24000.0)
             (* a (* y5 (- (* t y2) (* y y3))))
             (if (<= y2 -5.5e-89)
               (* i (* k (- (* y y5) (* z y1))))
               (if (<= y2 -4.5e-231)
                 (* i (* y5 t_4))
                 (if (<= y2 -2.3e-286)
                   t_2
                   (if (<= y2 4.3e-144)
                     (* y5 (+ (* i t_4) (* y0 (- (* j y3) (* k y2)))))
                     (if (<= y2 5e-109)
                       t_2
                       (if (<= y2 2.5e-69)
                         (* x (* y (- (* a b) (* c i))))
                         (if (<= y2 7.5e+131)
                           t_1
                           (if (<= y2 6.5e+301)
                             t_3
                             (* k (* y1 (- (* y2 y4) (* z i)))))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))));
	double t_2 = (z * y3) * ((a * y1) - (c * y0));
	double t_3 = x * (y2 * ((c * y0) - (a * y1)));
	double t_4 = (y * k) - (t * j);
	double tmp;
	if (y2 <= -3.4e+185) {
		tmp = t_1;
	} else if (y2 <= -1.95e+164) {
		tmp = t_3;
	} else if (y2 <= -2.2e+148) {
		tmp = ((t * a) - (k * y0)) * (y2 * y5);
	} else if (y2 <= -1.9e+36) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (y2 <= -24000.0) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y2 <= -5.5e-89) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (y2 <= -4.5e-231) {
		tmp = i * (y5 * t_4);
	} else if (y2 <= -2.3e-286) {
		tmp = t_2;
	} else if (y2 <= 4.3e-144) {
		tmp = y5 * ((i * t_4) + (y0 * ((j * y3) - (k * y2))));
	} else if (y2 <= 5e-109) {
		tmp = t_2;
	} else if (y2 <= 2.5e-69) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y2 <= 7.5e+131) {
		tmp = t_1;
	} else if (y2 <= 6.5e+301) {
		tmp = t_3;
	} else {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))))
    t_2 = (z * y3) * ((a * y1) - (c * y0))
    t_3 = x * (y2 * ((c * y0) - (a * y1)))
    t_4 = (y * k) - (t * j)
    if (y2 <= (-3.4d+185)) then
        tmp = t_1
    else if (y2 <= (-1.95d+164)) then
        tmp = t_3
    else if (y2 <= (-2.2d+148)) then
        tmp = ((t * a) - (k * y0)) * (y2 * y5)
    else if (y2 <= (-1.9d+36)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (y2 <= (-24000.0d0)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (y2 <= (-5.5d-89)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (y2 <= (-4.5d-231)) then
        tmp = i * (y5 * t_4)
    else if (y2 <= (-2.3d-286)) then
        tmp = t_2
    else if (y2 <= 4.3d-144) then
        tmp = y5 * ((i * t_4) + (y0 * ((j * y3) - (k * y2))))
    else if (y2 <= 5d-109) then
        tmp = t_2
    else if (y2 <= 2.5d-69) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y2 <= 7.5d+131) then
        tmp = t_1
    else if (y2 <= 6.5d+301) then
        tmp = t_3
    else
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))));
	double t_2 = (z * y3) * ((a * y1) - (c * y0));
	double t_3 = x * (y2 * ((c * y0) - (a * y1)));
	double t_4 = (y * k) - (t * j);
	double tmp;
	if (y2 <= -3.4e+185) {
		tmp = t_1;
	} else if (y2 <= -1.95e+164) {
		tmp = t_3;
	} else if (y2 <= -2.2e+148) {
		tmp = ((t * a) - (k * y0)) * (y2 * y5);
	} else if (y2 <= -1.9e+36) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (y2 <= -24000.0) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y2 <= -5.5e-89) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (y2 <= -4.5e-231) {
		tmp = i * (y5 * t_4);
	} else if (y2 <= -2.3e-286) {
		tmp = t_2;
	} else if (y2 <= 4.3e-144) {
		tmp = y5 * ((i * t_4) + (y0 * ((j * y3) - (k * y2))));
	} else if (y2 <= 5e-109) {
		tmp = t_2;
	} else if (y2 <= 2.5e-69) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y2 <= 7.5e+131) {
		tmp = t_1;
	} else if (y2 <= 6.5e+301) {
		tmp = t_3;
	} else {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))))
	t_2 = (z * y3) * ((a * y1) - (c * y0))
	t_3 = x * (y2 * ((c * y0) - (a * y1)))
	t_4 = (y * k) - (t * j)
	tmp = 0
	if y2 <= -3.4e+185:
		tmp = t_1
	elif y2 <= -1.95e+164:
		tmp = t_3
	elif y2 <= -2.2e+148:
		tmp = ((t * a) - (k * y0)) * (y2 * y5)
	elif y2 <= -1.9e+36:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif y2 <= -24000.0:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif y2 <= -5.5e-89:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif y2 <= -4.5e-231:
		tmp = i * (y5 * t_4)
	elif y2 <= -2.3e-286:
		tmp = t_2
	elif y2 <= 4.3e-144:
		tmp = y5 * ((i * t_4) + (y0 * ((j * y3) - (k * y2))))
	elif y2 <= 5e-109:
		tmp = t_2
	elif y2 <= 2.5e-69:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y2 <= 7.5e+131:
		tmp = t_1
	elif y2 <= 6.5e+301:
		tmp = t_3
	else:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y2 * Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))))
	t_2 = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)))
	t_3 = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	t_4 = Float64(Float64(y * k) - Float64(t * j))
	tmp = 0.0
	if (y2 <= -3.4e+185)
		tmp = t_1;
	elseif (y2 <= -1.95e+164)
		tmp = t_3;
	elseif (y2 <= -2.2e+148)
		tmp = Float64(Float64(Float64(t * a) - Float64(k * y0)) * Float64(y2 * y5));
	elseif (y2 <= -1.9e+36)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (y2 <= -24000.0)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (y2 <= -5.5e-89)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (y2 <= -4.5e-231)
		tmp = Float64(i * Float64(y5 * t_4));
	elseif (y2 <= -2.3e-286)
		tmp = t_2;
	elseif (y2 <= 4.3e-144)
		tmp = Float64(y5 * Float64(Float64(i * t_4) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (y2 <= 5e-109)
		tmp = t_2;
	elseif (y2 <= 2.5e-69)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y2 <= 7.5e+131)
		tmp = t_1;
	elseif (y2 <= 6.5e+301)
		tmp = t_3;
	else
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y2 * ((k * ((y1 * y4) - (y0 * y5))) + (t * ((a * y5) - (c * y4))));
	t_2 = (z * y3) * ((a * y1) - (c * y0));
	t_3 = x * (y2 * ((c * y0) - (a * y1)));
	t_4 = (y * k) - (t * j);
	tmp = 0.0;
	if (y2 <= -3.4e+185)
		tmp = t_1;
	elseif (y2 <= -1.95e+164)
		tmp = t_3;
	elseif (y2 <= -2.2e+148)
		tmp = ((t * a) - (k * y0)) * (y2 * y5);
	elseif (y2 <= -1.9e+36)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (y2 <= -24000.0)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (y2 <= -5.5e-89)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (y2 <= -4.5e-231)
		tmp = i * (y5 * t_4);
	elseif (y2 <= -2.3e-286)
		tmp = t_2;
	elseif (y2 <= 4.3e-144)
		tmp = y5 * ((i * t_4) + (y0 * ((j * y3) - (k * y2))));
	elseif (y2 <= 5e-109)
		tmp = t_2;
	elseif (y2 <= 2.5e-69)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y2 <= 7.5e+131)
		tmp = t_1;
	elseif (y2 <= 6.5e+301)
		tmp = t_3;
	else
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y2 * N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -3.4e+185], t$95$1, If[LessEqual[y2, -1.95e+164], t$95$3, If[LessEqual[y2, -2.2e+148], N[(N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision] * N[(y2 * y5), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -1.9e+36], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -24000.0], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -5.5e-89], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -4.5e-231], N[(i * N[(y5 * t$95$4), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -2.3e-286], t$95$2, If[LessEqual[y2, 4.3e-144], N[(y5 * N[(N[(i * t$95$4), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5e-109], t$95$2, If[LessEqual[y2, 2.5e-69], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 7.5e+131], t$95$1, If[LessEqual[y2, 6.5e+301], t$95$3, N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if y2 < -3.40000000000000017e185 or 2.50000000000000017e-69 < y2 < 7.4999999999999995e131

   1. Initial program 37.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 59.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around 0 59.5%

      \[\leadsto \color{blue}{y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 59.5%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot k} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) \]

   6. Simplified 59.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot k - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -3.40000000000000017e185 < y2 < -1.94999999999999993e164 or 7.4999999999999995e131 < y2 < 6.4999999999999999e301

   1. Initial program 25.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 60.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -1.94999999999999993e164 < y2 < -2.1999999999999999e148

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 40.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y5 around inf 80.9%

      \[\leadsto \color{blue}{y2 \cdot \left(y5 \cdot \left(-1 \cdot \left(k \cdot y0\right) - -1 \cdot \left(a \cdot t\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 80.9%

         \[\leadsto \color{blue}{\left(y2 \cdot y5\right) \cdot \left(-1 \cdot \left(k \cdot y0\right) - -1 \cdot \left(a \cdot t\right)\right)} \]

      2. *-commutative 80.9%

         \[\leadsto \color{blue}{\left(y5 \cdot y2\right)} \cdot \left(-1 \cdot \left(k \cdot y0\right) - -1 \cdot \left(a \cdot t\right)\right) \]

      3. distribute-lft-out-- 80.9%

         \[\leadsto \left(y5 \cdot y2\right) \cdot \color{blue}{\left(-1 \cdot \left(k \cdot y0 - a \cdot t\right)\right)} \]

      4. *-commutative 80.9%

         \[\leadsto \left(y5 \cdot y2\right) \cdot \left(-1 \cdot \left(\color{blue}{y0 \cdot k} - a \cdot t\right)\right) \]

   6. Simplified 80.9%

      \[\leadsto \color{blue}{\left(y5 \cdot y2\right) \cdot \left(-1 \cdot \left(y0 \cdot k - a \cdot t\right)\right)} \]

   if -2.1999999999999999e148 < y2 < -1.90000000000000012e36

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 41.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 60.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 60.0%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 60.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -1.90000000000000012e36 < y2 < -24000

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.7%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.7%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.7%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.7%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 59.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -24000 < y2 < -5.50000000000000012e-89

   1. Initial program 23.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 46.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 61.8%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -5.50000000000000012e-89 < y2 < -4.4999999999999998e-231

   1. Initial program 25.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 40.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 40.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 40.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 40.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 54.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 54.2%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 54.2%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 54.2%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 54.2%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 54.2%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 54.2%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   if -4.4999999999999998e-231 < y2 < -2.3000000000000002e-286 or 4.2999999999999999e-144 < y2 < 5.0000000000000002e-109

   1. Initial program 41.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 56.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in z around inf 65.4%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 65.4%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   6. Simplified 65.4%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -2.3000000000000002e-286 < y2 < 4.2999999999999999e-144

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 52.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   4. Taylor expanded in a around 0 47.7%

      \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} \]

   if 5.0000000000000002e-109 < y2 < 2.50000000000000017e-69

   1. Initial program 45.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 55.6%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 64.7%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 6.4999999999999999e301 < y2

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 100.0%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 100.0%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 100.0%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 58.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -3.4 \cdot 10^{+185}:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq -1.95 \cdot 10^{+164}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -2.2 \cdot 10^{+148}:\\ \;\;\;\;\left(t \cdot a - k \cdot y0\right) \cdot \left(y2 \cdot y5\right)\\ \mathbf{elif}\;y2 \leq -1.9 \cdot 10^{+36}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -24000:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y2 \leq -5.5 \cdot 10^{-89}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq -4.5 \cdot 10^{-231}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\\ \mathbf{elif}\;y2 \leq -2.3 \cdot 10^{-286}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;y2 \leq 4.3 \cdot 10^{-144}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq 5 \cdot 10^{-109}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;y2 \leq 2.5 \cdot 10^{-69}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y2 \leq 7.5 \cdot 10^{+131}:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 6.5 \cdot 10^{+301}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 35.8% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{if}\;c \leq -7.2 \cdot 10^{+134}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq -1.3 \cdot 10^{-59}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -3.8 \cdot 10^{-150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 1.25 \cdot 10^{-197}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;c \leq 5.4 \cdot 10^{-117}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{-23}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 0.00115:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq 5.2 \cdot 10^{+77}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 6.8 \cdot 10^{+123}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq 1.9 \cdot 10^{+157}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          c
          (+
           (+ (* i (- (* z t) (* x y))) (* y0 (- (* x y2) (* z y3))))
           (* y4 (- (* y y3) (* t y2)))))))
   (if (<= c -7.2e+134)
     (* y0 (* y2 (- (* x c) (* k y5))))
     (if (<= c -1.3e-59)
       (* y3 (* y4 (- (* y c) (* j y1))))
       (if (<= c -3.8e-150)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= c 1.25e-197)
           (*
            y5
            (+
             (* a (- (* t y2) (* y y3)))
             (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2))))))
           (if (<= c 5.4e-117)
             (*
              y3
              (+
               (* y (- (* c y4) (* a y5)))
               (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0))))))
             (if (<= c 2.4e-23)
               (* y5 (* y (- (* i k) (* a y3))))
               (if (<= c 0.00115)
                 (* k (* y4 (- (* y1 y2) (* y b))))
                 (if (<= c 5.2e+77)
                   t_1
                   (if (<= c 6.8e+123)
                     (* t (* y2 (- (* a y5) (* c y4))))
                     (if (<= c 1.9e+157)
                       (* i (* k (- (* y y5) (* z y1))))
                       t_1))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	double tmp;
	if (c <= -7.2e+134) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (c <= -1.3e-59) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (c <= -3.8e-150) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= 1.25e-197) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (c <= 5.4e-117) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (c <= 2.4e-23) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (c <= 0.00115) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (c <= 5.2e+77) {
		tmp = t_1;
	} else if (c <= 6.8e+123) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (c <= 1.9e+157) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
    if (c <= (-7.2d+134)) then
        tmp = y0 * (y2 * ((x * c) - (k * y5)))
    else if (c <= (-1.3d-59)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (c <= (-3.8d-150)) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (c <= 1.25d-197) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
    else if (c <= 5.4d-117) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
    else if (c <= 2.4d-23) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else if (c <= 0.00115d0) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (c <= 5.2d+77) then
        tmp = t_1
    else if (c <= 6.8d+123) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (c <= 1.9d+157) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	double tmp;
	if (c <= -7.2e+134) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (c <= -1.3e-59) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (c <= -3.8e-150) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= 1.25e-197) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (c <= 5.4e-117) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (c <= 2.4e-23) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (c <= 0.00115) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (c <= 5.2e+77) {
		tmp = t_1;
	} else if (c <= 6.8e+123) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (c <= 1.9e+157) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
	tmp = 0
	if c <= -7.2e+134:
		tmp = y0 * (y2 * ((x * c) - (k * y5)))
	elif c <= -1.3e-59:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif c <= -3.8e-150:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif c <= 1.25e-197:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
	elif c <= 5.4e-117:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	elif c <= 2.4e-23:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	elif c <= 0.00115:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif c <= 5.2e+77:
		tmp = t_1
	elif c <= 6.8e+123:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif c <= 1.9e+157:
		tmp = i * (k * ((y * y5) - (z * y1)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(Float64(Float64(i * Float64(Float64(z * t) - Float64(x * y))) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))))
	tmp = 0.0
	if (c <= -7.2e+134)
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (c <= -1.3e-59)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (c <= -3.8e-150)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (c <= 1.25e-197)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (c <= 5.4e-117)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	elseif (c <= 2.4e-23)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (c <= 0.00115)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (c <= 5.2e+77)
		tmp = t_1;
	elseif (c <= 6.8e+123)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (c <= 1.9e+157)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	tmp = 0.0;
	if (c <= -7.2e+134)
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	elseif (c <= -1.3e-59)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (c <= -3.8e-150)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (c <= 1.25e-197)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	elseif (c <= 5.4e-117)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	elseif (c <= 2.4e-23)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	elseif (c <= 0.00115)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (c <= 5.2e+77)
		tmp = t_1;
	elseif (c <= 6.8e+123)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (c <= 1.9e+157)
		tmp = i * (k * ((y * y5) - (z * y1)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(N[(N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -7.2e+134], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.3e-59], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -3.8e-150], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.25e-197], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5.4e-117], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.4e-23], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 0.00115], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5.2e+77], t$95$1, If[LessEqual[c, 6.8e+123], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.9e+157], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if c < -7.19999999999999976e134

   1. Initial program 24.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 49.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 56.5%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 56.5%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 56.5%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 56.5%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 56.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 56.5%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 56.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 56.5%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 56.5%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   if -7.19999999999999976e134 < c < -1.29999999999999999e-59

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 37.4%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 52.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 52.0%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 52.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -1.29999999999999999e-59 < c < -3.7999999999999998e-150

   1. Initial program 31.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 32.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 55.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 55.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 55.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 55.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 55.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 55.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 55.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if -3.7999999999999998e-150 < c < 1.2500000000000001e-197

   1. Initial program 41.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 53.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if 1.2500000000000001e-197 < c < 5.40000000000000005e-117

   1. Initial program 45.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 73.4%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if 5.40000000000000005e-117 < c < 2.39999999999999996e-23

   1. Initial program 45.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 63.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 44.1%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 44.1%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 48.9%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 48.9%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if 2.39999999999999996e-23 < c < 0.00115

   1. Initial program 71.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 43.2%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 57.7%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 57.7%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 57.7%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 57.7%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 57.7%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 57.7%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if 0.00115 < c < 5.2000000000000004e77 or 1.9e157 < c

   1. Initial program 21.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 69.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 5.2000000000000004e77 < c < 6.80000000000000002e123

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 75.2%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if 6.80000000000000002e123 < c < 1.9e157

   1. Initial program 11.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 69.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 70.5%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 59.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -7.2 \cdot 10^{+134}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq -1.3 \cdot 10^{-59}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -3.8 \cdot 10^{-150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 1.25 \cdot 10^{-197}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;c \leq 5.4 \cdot 10^{-117}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{-23}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 0.00115:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq 5.2 \cdot 10^{+77}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 6.8 \cdot 10^{+123}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq 1.9 \cdot 10^{+157}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 39.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y4 - i \cdot y5\\ t_2 := c \cdot y4 - a \cdot y5\\ t_3 := i \cdot y5 - b \cdot y4\\ t_4 := z \cdot t - x \cdot y\\ t_5 := y0 \cdot y5 - y1 \cdot y4\\ t_6 := \left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ t_7 := k \cdot \left(\left(y \cdot t_3 + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;j \leq -8 \cdot 10^{+199}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot t_5 + t \cdot t_1\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2.05 \cdot 10^{+154}:\\ \;\;\;\;t_7\\ \mathbf{elif}\;j \leq -2 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot t_4 - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq -5 \cdot 10^{+95}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{+46}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;j \leq -3.5 \cdot 10^{-23}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot t_1\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -6.4 \cdot 10^{-115}:\\ \;\;\;\;c \cdot \left(\left(i \cdot t_4 + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -1.75 \cdot 10^{-184}:\\ \;\;\;\;y \cdot \left(\left(k \cdot t_3 + x \cdot \left(a \cdot b - c \cdot i\right)\right) + y3 \cdot t_2\right)\\ \mathbf{elif}\;j \leq 3.8 \cdot 10^{-38}:\\ \;\;\;\;t_7\\ \mathbf{elif}\;j \leq 2.7 \cdot 10^{+126}:\\ \;\;\;\;y3 \cdot \left(y \cdot t_2 + \left(j \cdot t_5 + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_6\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y4) (* i y5)))
        (t_2 (- (* c y4) (* a y5)))
        (t_3 (- (* i y5) (* b y4)))
        (t_4 (- (* z t) (* x y)))
        (t_5 (- (* y0 y5) (* y1 y4)))
        (t_6 (* (* i j) (- (* x y1) (* t y5))))
        (t_7
         (*
          k
          (+
           (+ (* y t_3) (* y2 (- (* y1 y4) (* y0 y5))))
           (* z (- (* b y0) (* i y1)))))))
   (if (<= j -8e+199)
     (* j (+ (+ (* y3 t_5) (* t t_1)) (* x (- (* i y1) (* b y0)))))
     (if (<= j -2.05e+154)
       t_7
       (if (<= j -2e+112)
         (*
          a
          (-
           (* y5 (- (* t y2) (* y y3)))
           (- (* b t_4) (* y1 (- (* z y3) (* x y2))))))
         (if (<= j -5e+95)
           (* y3 (* y4 (- (* y c) (* j y1))))
           (if (<= j -1.15e+46)
             t_6
             (if (<= j -3.5e-23)
               (*
                t
                (+
                 (+ (* z (- (* c i) (* a b))) (* j t_1))
                 (* y2 (- (* a y5) (* c y4)))))
               (if (<= j -6.4e-115)
                 (*
                  c
                  (+
                   (+ (* i t_4) (* y0 (- (* x y2) (* z y3))))
                   (* y4 (- (* y y3) (* t y2)))))
                 (if (<= j -1.75e-184)
                   (* y (+ (+ (* k t_3) (* x (- (* a b) (* c i)))) (* y3 t_2)))
                   (if (<= j 3.8e-38)
                     t_7
                     (if (<= j 2.7e+126)
                       (*
                        y3
                        (+
                         (* y t_2)
                         (+ (* j t_5) (* z (- (* a y1) (* c y0))))))
                       t_6))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y4) - (i * y5);
	double t_2 = (c * y4) - (a * y5);
	double t_3 = (i * y5) - (b * y4);
	double t_4 = (z * t) - (x * y);
	double t_5 = (y0 * y5) - (y1 * y4);
	double t_6 = (i * j) * ((x * y1) - (t * y5));
	double t_7 = k * (((y * t_3) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))));
	double tmp;
	if (j <= -8e+199) {
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	} else if (j <= -2.05e+154) {
		tmp = t_7;
	} else if (j <= -2e+112) {
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))));
	} else if (j <= -5e+95) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.15e+46) {
		tmp = t_6;
	} else if (j <= -3.5e-23) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	} else if (j <= -6.4e-115) {
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= -1.75e-184) {
		tmp = y * (((k * t_3) + (x * ((a * b) - (c * i)))) + (y3 * t_2));
	} else if (j <= 3.8e-38) {
		tmp = t_7;
	} else if (j <= 2.7e+126) {
		tmp = y3 * ((y * t_2) + ((j * t_5) + (z * ((a * y1) - (c * y0)))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: tmp
    t_1 = (b * y4) - (i * y5)
    t_2 = (c * y4) - (a * y5)
    t_3 = (i * y5) - (b * y4)
    t_4 = (z * t) - (x * y)
    t_5 = (y0 * y5) - (y1 * y4)
    t_6 = (i * j) * ((x * y1) - (t * y5))
    t_7 = k * (((y * t_3) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))))
    if (j <= (-8d+199)) then
        tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))))
    else if (j <= (-2.05d+154)) then
        tmp = t_7
    else if (j <= (-2d+112)) then
        tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))))
    else if (j <= (-5d+95)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (j <= (-1.15d+46)) then
        tmp = t_6
    else if (j <= (-3.5d-23)) then
        tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))))
    else if (j <= (-6.4d-115)) then
        tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
    else if (j <= (-1.75d-184)) then
        tmp = y * (((k * t_3) + (x * ((a * b) - (c * i)))) + (y3 * t_2))
    else if (j <= 3.8d-38) then
        tmp = t_7
    else if (j <= 2.7d+126) then
        tmp = y3 * ((y * t_2) + ((j * t_5) + (z * ((a * y1) - (c * y0)))))
    else
        tmp = t_6
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y4) - (i * y5);
	double t_2 = (c * y4) - (a * y5);
	double t_3 = (i * y5) - (b * y4);
	double t_4 = (z * t) - (x * y);
	double t_5 = (y0 * y5) - (y1 * y4);
	double t_6 = (i * j) * ((x * y1) - (t * y5));
	double t_7 = k * (((y * t_3) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))));
	double tmp;
	if (j <= -8e+199) {
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	} else if (j <= -2.05e+154) {
		tmp = t_7;
	} else if (j <= -2e+112) {
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))));
	} else if (j <= -5e+95) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.15e+46) {
		tmp = t_6;
	} else if (j <= -3.5e-23) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	} else if (j <= -6.4e-115) {
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= -1.75e-184) {
		tmp = y * (((k * t_3) + (x * ((a * b) - (c * i)))) + (y3 * t_2));
	} else if (j <= 3.8e-38) {
		tmp = t_7;
	} else if (j <= 2.7e+126) {
		tmp = y3 * ((y * t_2) + ((j * t_5) + (z * ((a * y1) - (c * y0)))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (b * y4) - (i * y5)
	t_2 = (c * y4) - (a * y5)
	t_3 = (i * y5) - (b * y4)
	t_4 = (z * t) - (x * y)
	t_5 = (y0 * y5) - (y1 * y4)
	t_6 = (i * j) * ((x * y1) - (t * y5))
	t_7 = k * (((y * t_3) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))))
	tmp = 0
	if j <= -8e+199:
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))))
	elif j <= -2.05e+154:
		tmp = t_7
	elif j <= -2e+112:
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))))
	elif j <= -5e+95:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif j <= -1.15e+46:
		tmp = t_6
	elif j <= -3.5e-23:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))))
	elif j <= -6.4e-115:
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
	elif j <= -1.75e-184:
		tmp = y * (((k * t_3) + (x * ((a * b) - (c * i)))) + (y3 * t_2))
	elif j <= 3.8e-38:
		tmp = t_7
	elif j <= 2.7e+126:
		tmp = y3 * ((y * t_2) + ((j * t_5) + (z * ((a * y1) - (c * y0)))))
	else:
		tmp = t_6
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(b * y4) - Float64(i * y5))
	t_2 = Float64(Float64(c * y4) - Float64(a * y5))
	t_3 = Float64(Float64(i * y5) - Float64(b * y4))
	t_4 = Float64(Float64(z * t) - Float64(x * y))
	t_5 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_6 = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)))
	t_7 = Float64(k * Float64(Float64(Float64(y * t_3) + Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))))
	tmp = 0.0
	if (j <= -8e+199)
		tmp = Float64(j * Float64(Float64(Float64(y3 * t_5) + Float64(t * t_1)) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (j <= -2.05e+154)
		tmp = t_7;
	elseif (j <= -2e+112)
		tmp = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) - Float64(Float64(b * t_4) - Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))));
	elseif (j <= -5e+95)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (j <= -1.15e+46)
		tmp = t_6;
	elseif (j <= -3.5e-23)
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * t_1)) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= -6.4e-115)
		tmp = Float64(c * Float64(Float64(Float64(i * t_4) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= -1.75e-184)
		tmp = Float64(y * Float64(Float64(Float64(k * t_3) + Float64(x * Float64(Float64(a * b) - Float64(c * i)))) + Float64(y3 * t_2)));
	elseif (j <= 3.8e-38)
		tmp = t_7;
	elseif (j <= 2.7e+126)
		tmp = Float64(y3 * Float64(Float64(y * t_2) + Float64(Float64(j * t_5) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	else
		tmp = t_6;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (b * y4) - (i * y5);
	t_2 = (c * y4) - (a * y5);
	t_3 = (i * y5) - (b * y4);
	t_4 = (z * t) - (x * y);
	t_5 = (y0 * y5) - (y1 * y4);
	t_6 = (i * j) * ((x * y1) - (t * y5));
	t_7 = k * (((y * t_3) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * ((b * y0) - (i * y1))));
	tmp = 0.0;
	if (j <= -8e+199)
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	elseif (j <= -2.05e+154)
		tmp = t_7;
	elseif (j <= -2e+112)
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))));
	elseif (j <= -5e+95)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (j <= -1.15e+46)
		tmp = t_6;
	elseif (j <= -3.5e-23)
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	elseif (j <= -6.4e-115)
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (j <= -1.75e-184)
		tmp = y * (((k * t_3) + (x * ((a * b) - (c * i)))) + (y3 * t_2));
	elseif (j <= 3.8e-38)
		tmp = t_7;
	elseif (j <= 2.7e+126)
		tmp = y3 * ((y * t_2) + ((j * t_5) + (z * ((a * y1) - (c * y0)))));
	else
		tmp = t_6;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(k * N[(N[(N[(y * t$95$3), $MachinePrecision] + N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -8e+199], N[(j * N[(N[(N[(y3 * t$95$5), $MachinePrecision] + N[(t * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.05e+154], t$95$7, If[LessEqual[j, -2e+112], N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * t$95$4), $MachinePrecision] - N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5e+95], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.15e+46], t$95$6, If[LessEqual[j, -3.5e-23], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -6.4e-115], N[(c * N[(N[(N[(i * t$95$4), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.75e-184], N[(y * N[(N[(N[(k * t$95$3), $MachinePrecision] + N[(x * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.8e-38], t$95$7, If[LessEqual[j, 2.7e+126], N[(y3 * N[(N[(y * t$95$2), $MachinePrecision] + N[(N[(j * t$95$5), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$6]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if j < -8.00000000000000078e199

   1. Initial program 24.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 69.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -8.00000000000000078e199 < j < -2.05e154 or -1.74999999999999991e-184 < j < 3.8e-38

   1. Initial program 39.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 55.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if -2.05e154 < j < -1.9999999999999999e112

   1. Initial program 37.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf 64.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if -1.9999999999999999e112 < j < -5.00000000000000025e95

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 75.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 100.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 100.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -5.00000000000000025e95 < j < -1.15e46 or 2.70000000000000002e126 < j

   1. Initial program 26.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 57.1%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.1%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 55.1%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]

   if -1.15e46 < j < -3.49999999999999993e-23

   1. Initial program 42.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in t around inf 58.3%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -3.49999999999999993e-23 < j < -6.4e-115

   1. Initial program 21.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 62.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -6.4e-115 < j < -1.74999999999999991e-184

   1. Initial program 45.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 81.8%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if 3.8e-38 < j < 2.70000000000000002e126

   1. Initial program 30.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 71.3%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 61.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -8 \cdot 10^{+199}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2.05 \cdot 10^{+154}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -2 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot \left(z \cdot t - x \cdot y\right) - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq -5 \cdot 10^{+95}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{+46}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;j \leq -3.5 \cdot 10^{-23}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -6.4 \cdot 10^{-115}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -1.75 \cdot 10^{-184}:\\ \;\;\;\;y \cdot \left(\left(k \cdot \left(i \cdot y5 - b \cdot y4\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) + y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 3.8 \cdot 10^{-38}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 2.7 \cdot 10^{+126}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 38.0% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot t - x \cdot y\\ t_2 := y \cdot y3 - t \cdot y2\\ t_3 := z \cdot y3 - x \cdot y2\\ t_4 := t \cdot j - y \cdot k\\ t_5 := a \cdot y5 - c \cdot y4\\ t_6 := k \cdot y2 - j \cdot y3\\ t_7 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;t \leq -3.2 \cdot 10^{+151}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;t \leq -2.05 \cdot 10^{+64}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t_4 + y1 \cdot t_6\right) + c \cdot t_2\right)\\ \mathbf{elif}\;t \leq -2.9 \cdot 10^{-158}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_7 - \left(b \cdot t_1 - y1 \cdot t_3\right)\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-176}:\\ \;\;\;\;c \cdot \left(\left(i \cdot t_1 + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot t_2\right)\\ \mathbf{elif}\;t \leq -6.1 \cdot 10^{-229}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot t_3 + y4 \cdot t_6\right) + i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-296}:\\ \;\;\;\;t_6 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + \left(t_7 \cdot t_5 - i \cdot \left(y5 \cdot t_4\right)\right)\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-112}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.1 \cdot 10^{+17}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.62 \cdot 10^{+115}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot t_5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* z t) (* x y)))
        (t_2 (- (* y y3) (* t y2)))
        (t_3 (- (* z y3) (* x y2)))
        (t_4 (- (* t j) (* y k)))
        (t_5 (- (* a y5) (* c y4)))
        (t_6 (- (* k y2) (* j y3)))
        (t_7 (- (* t y2) (* y y3))))
   (if (<= t -3.2e+151)
     (* (* i j) (- (* x y1) (* t y5)))
     (if (<= t -2.05e+64)
       (* y4 (+ (+ (* b t_4) (* y1 t_6)) (* c t_2)))
       (if (<= t -2.9e-158)
         (* a (- (* y5 t_7) (- (* b t_1) (* y1 t_3))))
         (if (<= t -9e-176)
           (* c (+ (+ (* i t_1) (* y0 (- (* x y2) (* z y3)))) (* y4 t_2)))
           (if (<= t -6.1e-229)
             (* y1 (+ (+ (* a t_3) (* y4 t_6)) (* i (- (* x j) (* z k)))))
             (if (<= t -9e-296)
               (+
                (* t_6 (- (* y1 y4) (* y0 y5)))
                (- (* t_7 t_5) (* i (* y5 t_4))))
               (if (<= t 7e-112)
                 (*
                  y3
                  (+
                   (* y (- (* c y4) (* a y5)))
                   (+
                    (* j (- (* y0 y5) (* y1 y4)))
                    (* z (- (* a y1) (* c y0))))))
                 (if (<= t 3.1e+17)
                   (* k (* z (- (* b y0) (* i y1))))
                   (if (<= t 1.62e+115)
                     (* y5 (* y (- (* i k) (* a y3))))
                     (*
                      t
                      (+
                       (+
                        (* z (- (* c i) (* a b)))
                        (* j (- (* b y4) (* i y5))))
                       (* y2 t_5))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (z * t) - (x * y);
	double t_2 = (y * y3) - (t * y2);
	double t_3 = (z * y3) - (x * y2);
	double t_4 = (t * j) - (y * k);
	double t_5 = (a * y5) - (c * y4);
	double t_6 = (k * y2) - (j * y3);
	double t_7 = (t * y2) - (y * y3);
	double tmp;
	if (t <= -3.2e+151) {
		tmp = (i * j) * ((x * y1) - (t * y5));
	} else if (t <= -2.05e+64) {
		tmp = y4 * (((b * t_4) + (y1 * t_6)) + (c * t_2));
	} else if (t <= -2.9e-158) {
		tmp = a * ((y5 * t_7) - ((b * t_1) - (y1 * t_3)));
	} else if (t <= -9e-176) {
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2));
	} else if (t <= -6.1e-229) {
		tmp = y1 * (((a * t_3) + (y4 * t_6)) + (i * ((x * j) - (z * k))));
	} else if (t <= -9e-296) {
		tmp = (t_6 * ((y1 * y4) - (y0 * y5))) + ((t_7 * t_5) - (i * (y5 * t_4)));
	} else if (t <= 7e-112) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 3.1e+17) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (t <= 1.62e+115) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * t_5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: tmp
    t_1 = (z * t) - (x * y)
    t_2 = (y * y3) - (t * y2)
    t_3 = (z * y3) - (x * y2)
    t_4 = (t * j) - (y * k)
    t_5 = (a * y5) - (c * y4)
    t_6 = (k * y2) - (j * y3)
    t_7 = (t * y2) - (y * y3)
    if (t <= (-3.2d+151)) then
        tmp = (i * j) * ((x * y1) - (t * y5))
    else if (t <= (-2.05d+64)) then
        tmp = y4 * (((b * t_4) + (y1 * t_6)) + (c * t_2))
    else if (t <= (-2.9d-158)) then
        tmp = a * ((y5 * t_7) - ((b * t_1) - (y1 * t_3)))
    else if (t <= (-9d-176)) then
        tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2))
    else if (t <= (-6.1d-229)) then
        tmp = y1 * (((a * t_3) + (y4 * t_6)) + (i * ((x * j) - (z * k))))
    else if (t <= (-9d-296)) then
        tmp = (t_6 * ((y1 * y4) - (y0 * y5))) + ((t_7 * t_5) - (i * (y5 * t_4)))
    else if (t <= 7d-112) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
    else if (t <= 3.1d+17) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (t <= 1.62d+115) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else
        tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * t_5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (z * t) - (x * y);
	double t_2 = (y * y3) - (t * y2);
	double t_3 = (z * y3) - (x * y2);
	double t_4 = (t * j) - (y * k);
	double t_5 = (a * y5) - (c * y4);
	double t_6 = (k * y2) - (j * y3);
	double t_7 = (t * y2) - (y * y3);
	double tmp;
	if (t <= -3.2e+151) {
		tmp = (i * j) * ((x * y1) - (t * y5));
	} else if (t <= -2.05e+64) {
		tmp = y4 * (((b * t_4) + (y1 * t_6)) + (c * t_2));
	} else if (t <= -2.9e-158) {
		tmp = a * ((y5 * t_7) - ((b * t_1) - (y1 * t_3)));
	} else if (t <= -9e-176) {
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2));
	} else if (t <= -6.1e-229) {
		tmp = y1 * (((a * t_3) + (y4 * t_6)) + (i * ((x * j) - (z * k))));
	} else if (t <= -9e-296) {
		tmp = (t_6 * ((y1 * y4) - (y0 * y5))) + ((t_7 * t_5) - (i * (y5 * t_4)));
	} else if (t <= 7e-112) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 3.1e+17) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (t <= 1.62e+115) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * t_5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (z * t) - (x * y)
	t_2 = (y * y3) - (t * y2)
	t_3 = (z * y3) - (x * y2)
	t_4 = (t * j) - (y * k)
	t_5 = (a * y5) - (c * y4)
	t_6 = (k * y2) - (j * y3)
	t_7 = (t * y2) - (y * y3)
	tmp = 0
	if t <= -3.2e+151:
		tmp = (i * j) * ((x * y1) - (t * y5))
	elif t <= -2.05e+64:
		tmp = y4 * (((b * t_4) + (y1 * t_6)) + (c * t_2))
	elif t <= -2.9e-158:
		tmp = a * ((y5 * t_7) - ((b * t_1) - (y1 * t_3)))
	elif t <= -9e-176:
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2))
	elif t <= -6.1e-229:
		tmp = y1 * (((a * t_3) + (y4 * t_6)) + (i * ((x * j) - (z * k))))
	elif t <= -9e-296:
		tmp = (t_6 * ((y1 * y4) - (y0 * y5))) + ((t_7 * t_5) - (i * (y5 * t_4)))
	elif t <= 7e-112:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	elif t <= 3.1e+17:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif t <= 1.62e+115:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	else:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * t_5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(z * t) - Float64(x * y))
	t_2 = Float64(Float64(y * y3) - Float64(t * y2))
	t_3 = Float64(Float64(z * y3) - Float64(x * y2))
	t_4 = Float64(Float64(t * j) - Float64(y * k))
	t_5 = Float64(Float64(a * y5) - Float64(c * y4))
	t_6 = Float64(Float64(k * y2) - Float64(j * y3))
	t_7 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (t <= -3.2e+151)
		tmp = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)));
	elseif (t <= -2.05e+64)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_4) + Float64(y1 * t_6)) + Float64(c * t_2)));
	elseif (t <= -2.9e-158)
		tmp = Float64(a * Float64(Float64(y5 * t_7) - Float64(Float64(b * t_1) - Float64(y1 * t_3))));
	elseif (t <= -9e-176)
		tmp = Float64(c * Float64(Float64(Float64(i * t_1) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * t_2)));
	elseif (t <= -6.1e-229)
		tmp = Float64(y1 * Float64(Float64(Float64(a * t_3) + Float64(y4 * t_6)) + Float64(i * Float64(Float64(x * j) - Float64(z * k)))));
	elseif (t <= -9e-296)
		tmp = Float64(Float64(t_6 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(Float64(t_7 * t_5) - Float64(i * Float64(y5 * t_4))));
	elseif (t <= 7e-112)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	elseif (t <= 3.1e+17)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (t <= 1.62e+115)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(y2 * t_5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (z * t) - (x * y);
	t_2 = (y * y3) - (t * y2);
	t_3 = (z * y3) - (x * y2);
	t_4 = (t * j) - (y * k);
	t_5 = (a * y5) - (c * y4);
	t_6 = (k * y2) - (j * y3);
	t_7 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (t <= -3.2e+151)
		tmp = (i * j) * ((x * y1) - (t * y5));
	elseif (t <= -2.05e+64)
		tmp = y4 * (((b * t_4) + (y1 * t_6)) + (c * t_2));
	elseif (t <= -2.9e-158)
		tmp = a * ((y5 * t_7) - ((b * t_1) - (y1 * t_3)));
	elseif (t <= -9e-176)
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2));
	elseif (t <= -6.1e-229)
		tmp = y1 * (((a * t_3) + (y4 * t_6)) + (i * ((x * j) - (z * k))));
	elseif (t <= -9e-296)
		tmp = (t_6 * ((y1 * y4) - (y0 * y5))) + ((t_7 * t_5) - (i * (y5 * t_4)));
	elseif (t <= 7e-112)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	elseif (t <= 3.1e+17)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (t <= 1.62e+115)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	else
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * t_5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.2e+151], N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.05e+64], N[(y4 * N[(N[(N[(b * t$95$4), $MachinePrecision] + N[(y1 * t$95$6), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.9e-158], N[(a * N[(N[(y5 * t$95$7), $MachinePrecision] - N[(N[(b * t$95$1), $MachinePrecision] - N[(y1 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -9e-176], N[(c * N[(N[(N[(i * t$95$1), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -6.1e-229], N[(y1 * N[(N[(N[(a * t$95$3), $MachinePrecision] + N[(y4 * t$95$6), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -9e-296], N[(N[(t$95$6 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$7 * t$95$5), $MachinePrecision] - N[(i * N[(y5 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7e-112], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.1e+17], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.62e+115], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -3.19999999999999994e151

   1. Initial program 12.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 58.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.6%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 55.6%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]

   if -3.19999999999999994e151 < t < -2.04999999999999989e64

   1. Initial program 33.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 62.7%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -2.04999999999999989e64 < t < -2.8999999999999998e-158

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf 49.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if -2.8999999999999998e-158 < t < -9e-176

   1. Initial program 16.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 67.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -9e-176 < t < -6.0999999999999997e-229

   1. Initial program 45.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 72.9%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   if -6.0999999999999997e-229 < t < -9.0000000000000003e-296

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 69.5%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 69.5%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 69.5%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 69.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   if -9.0000000000000003e-296 < t < 6.99999999999999988e-112

   1. Initial program 37.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 62.9%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if 6.99999999999999988e-112 < t < 3.1e17

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 41.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 55.2%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 55.2%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 55.2%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 55.2%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 3.1e17 < t < 1.62e115

   1. Initial program 39.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 48.0%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 61.5%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 61.5%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 61.5%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 61.5%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if 1.62e115 < t

   1. Initial program 39.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in t around inf 67.6%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 60.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.2 \cdot 10^{+151}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;t \leq -2.05 \cdot 10^{+64}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -2.9 \cdot 10^{-158}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot \left(z \cdot t - x \cdot y\right) - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-176}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -6.1 \cdot 10^{-229}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot \left(z \cdot y3 - x \cdot y2\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-296}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + \left(\left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right) - i \cdot \left(y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-112}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.1 \cdot 10^{+17}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.62 \cdot 10^{+115}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 37.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot t - x \cdot y\\ t_2 := y \cdot y3 - t \cdot y2\\ t_3 := z \cdot y3 - x \cdot y2\\ t_4 := k \cdot y2 - j \cdot y3\\ \mathbf{if}\;t \leq -3.8 \cdot 10^{+151}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;t \leq -1.35 \cdot 10^{+66}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot t_4\right) + c \cdot t_2\right)\\ \mathbf{elif}\;t \leq -1.95 \cdot 10^{-154}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot t_1 - y1 \cdot t_3\right)\right)\\ \mathbf{elif}\;t \leq -2.22 \cdot 10^{-181}:\\ \;\;\;\;c \cdot \left(\left(i \cdot t_1 + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot t_2\right)\\ \mathbf{elif}\;t \leq -3.6 \cdot 10^{-201}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot t_3 + y4 \cdot t_4\right) + i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -5.5 \cdot 10^{-296}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-113}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{+14}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{+115}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* z t) (* x y)))
        (t_2 (- (* y y3) (* t y2)))
        (t_3 (- (* z y3) (* x y2)))
        (t_4 (- (* k y2) (* j y3))))
   (if (<= t -3.8e+151)
     (* (* i j) (- (* x y1) (* t y5)))
     (if (<= t -1.35e+66)
       (* y4 (+ (+ (* b (- (* t j) (* y k))) (* y1 t_4)) (* c t_2)))
       (if (<= t -1.95e-154)
         (* a (- (* y5 (- (* t y2) (* y y3))) (- (* b t_1) (* y1 t_3))))
         (if (<= t -2.22e-181)
           (* c (+ (+ (* i t_1) (* y0 (- (* x y2) (* z y3)))) (* y4 t_2)))
           (if (<= t -3.6e-201)
             (* y1 (+ (+ (* a t_3) (* y4 t_4)) (* i (- (* x j) (* z k)))))
             (if (<= t -5.5e-296)
               (*
                y5
                (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2)))))
               (if (<= t 8e-113)
                 (*
                  y3
                  (+
                   (* y (- (* c y4) (* a y5)))
                   (+
                    (* j (- (* y0 y5) (* y1 y4)))
                    (* z (- (* a y1) (* c y0))))))
                 (if (<= t 2.7e+14)
                   (* k (* z (- (* b y0) (* i y1))))
                   (if (<= t 1.6e+115)
                     (* y5 (* y (- (* i k) (* a y3))))
                     (*
                      t
                      (+
                       (+
                        (* z (- (* c i) (* a b)))
                        (* j (- (* b y4) (* i y5))))
                       (* y2 (- (* a y5) (* c y4))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (z * t) - (x * y);
	double t_2 = (y * y3) - (t * y2);
	double t_3 = (z * y3) - (x * y2);
	double t_4 = (k * y2) - (j * y3);
	double tmp;
	if (t <= -3.8e+151) {
		tmp = (i * j) * ((x * y1) - (t * y5));
	} else if (t <= -1.35e+66) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) + (c * t_2));
	} else if (t <= -1.95e-154) {
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_1) - (y1 * t_3)));
	} else if (t <= -2.22e-181) {
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2));
	} else if (t <= -3.6e-201) {
		tmp = y1 * (((a * t_3) + (y4 * t_4)) + (i * ((x * j) - (z * k))));
	} else if (t <= -5.5e-296) {
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	} else if (t <= 8e-113) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 2.7e+14) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (t <= 1.6e+115) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * ((a * y5) - (c * y4))));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = (z * t) - (x * y)
    t_2 = (y * y3) - (t * y2)
    t_3 = (z * y3) - (x * y2)
    t_4 = (k * y2) - (j * y3)
    if (t <= (-3.8d+151)) then
        tmp = (i * j) * ((x * y1) - (t * y5))
    else if (t <= (-1.35d+66)) then
        tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) + (c * t_2))
    else if (t <= (-1.95d-154)) then
        tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_1) - (y1 * t_3)))
    else if (t <= (-2.22d-181)) then
        tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2))
    else if (t <= (-3.6d-201)) then
        tmp = y1 * (((a * t_3) + (y4 * t_4)) + (i * ((x * j) - (z * k))))
    else if (t <= (-5.5d-296)) then
        tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))))
    else if (t <= 8d-113) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
    else if (t <= 2.7d+14) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (t <= 1.6d+115) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else
        tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * ((a * y5) - (c * y4))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (z * t) - (x * y);
	double t_2 = (y * y3) - (t * y2);
	double t_3 = (z * y3) - (x * y2);
	double t_4 = (k * y2) - (j * y3);
	double tmp;
	if (t <= -3.8e+151) {
		tmp = (i * j) * ((x * y1) - (t * y5));
	} else if (t <= -1.35e+66) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) + (c * t_2));
	} else if (t <= -1.95e-154) {
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_1) - (y1 * t_3)));
	} else if (t <= -2.22e-181) {
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2));
	} else if (t <= -3.6e-201) {
		tmp = y1 * (((a * t_3) + (y4 * t_4)) + (i * ((x * j) - (z * k))));
	} else if (t <= -5.5e-296) {
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	} else if (t <= 8e-113) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 2.7e+14) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (t <= 1.6e+115) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * ((a * y5) - (c * y4))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (z * t) - (x * y)
	t_2 = (y * y3) - (t * y2)
	t_3 = (z * y3) - (x * y2)
	t_4 = (k * y2) - (j * y3)
	tmp = 0
	if t <= -3.8e+151:
		tmp = (i * j) * ((x * y1) - (t * y5))
	elif t <= -1.35e+66:
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) + (c * t_2))
	elif t <= -1.95e-154:
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_1) - (y1 * t_3)))
	elif t <= -2.22e-181:
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2))
	elif t <= -3.6e-201:
		tmp = y1 * (((a * t_3) + (y4 * t_4)) + (i * ((x * j) - (z * k))))
	elif t <= -5.5e-296:
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))))
	elif t <= 8e-113:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	elif t <= 2.7e+14:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif t <= 1.6e+115:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	else:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * ((a * y5) - (c * y4))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(z * t) - Float64(x * y))
	t_2 = Float64(Float64(y * y3) - Float64(t * y2))
	t_3 = Float64(Float64(z * y3) - Float64(x * y2))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	tmp = 0.0
	if (t <= -3.8e+151)
		tmp = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)));
	elseif (t <= -1.35e+66)
		tmp = Float64(y4 * Float64(Float64(Float64(b * Float64(Float64(t * j) - Float64(y * k))) + Float64(y1 * t_4)) + Float64(c * t_2)));
	elseif (t <= -1.95e-154)
		tmp = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) - Float64(Float64(b * t_1) - Float64(y1 * t_3))));
	elseif (t <= -2.22e-181)
		tmp = Float64(c * Float64(Float64(Float64(i * t_1) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * t_2)));
	elseif (t <= -3.6e-201)
		tmp = Float64(y1 * Float64(Float64(Float64(a * t_3) + Float64(y4 * t_4)) + Float64(i * Float64(Float64(x * j) - Float64(z * k)))));
	elseif (t <= -5.5e-296)
		tmp = Float64(y5 * Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (t <= 8e-113)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	elseif (t <= 2.7e+14)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (t <= 1.6e+115)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (z * t) - (x * y);
	t_2 = (y * y3) - (t * y2);
	t_3 = (z * y3) - (x * y2);
	t_4 = (k * y2) - (j * y3);
	tmp = 0.0;
	if (t <= -3.8e+151)
		tmp = (i * j) * ((x * y1) - (t * y5));
	elseif (t <= -1.35e+66)
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) + (c * t_2));
	elseif (t <= -1.95e-154)
		tmp = a * ((y5 * ((t * y2) - (y * y3))) - ((b * t_1) - (y1 * t_3)));
	elseif (t <= -2.22e-181)
		tmp = c * (((i * t_1) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_2));
	elseif (t <= -3.6e-201)
		tmp = y1 * (((a * t_3) + (y4 * t_4)) + (i * ((x * j) - (z * k))));
	elseif (t <= -5.5e-296)
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	elseif (t <= 8e-113)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	elseif (t <= 2.7e+14)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (t <= 1.6e+115)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	else
		tmp = t * (((z * ((c * i) - (a * b))) + (j * ((b * y4) - (i * y5)))) + (y2 * ((a * y5) - (c * y4))));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.8e+151], N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.35e+66], N[(y4 * N[(N[(N[(b * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.95e-154], N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * t$95$1), $MachinePrecision] - N[(y1 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.22e-181], N[(c * N[(N[(N[(i * t$95$1), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.6e-201], N[(y1 * N[(N[(N[(a * t$95$3), $MachinePrecision] + N[(y4 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.5e-296], N[(y5 * N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 8e-113], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.7e+14], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.6e+115], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -3.8e151

   1. Initial program 12.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 58.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.6%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 55.6%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]

   if -3.8e151 < t < -1.35e66

   1. Initial program 33.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 62.7%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -1.35e66 < t < -1.95000000000000016e-154

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf 49.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if -1.95000000000000016e-154 < t < -2.21999999999999996e-181

   1. Initial program 16.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 67.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -2.21999999999999996e-181 < t < -3.60000000000000031e-201

   1. Initial program 75.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 100.0%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   if -3.60000000000000031e-201 < t < -5.5000000000000004e-296

   1. Initial program 31.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 61.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   4. Taylor expanded in a around 0 62.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} \]

   if -5.5000000000000004e-296 < t < 7.99999999999999983e-113

   1. Initial program 37.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 62.9%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if 7.99999999999999983e-113 < t < 2.7e14

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 41.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 55.2%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 55.2%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 55.2%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 55.2%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 2.7e14 < t < 1.6e115

   1. Initial program 39.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 48.0%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 61.5%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 61.5%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 61.5%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 61.5%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if 1.6e115 < t

   1. Initial program 39.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in t around inf 67.6%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 60.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.8 \cdot 10^{+151}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;t \leq -1.35 \cdot 10^{+66}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -1.95 \cdot 10^{-154}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot \left(z \cdot t - x \cdot y\right) - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -2.22 \cdot 10^{-181}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -3.6 \cdot 10^{-201}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot \left(z \cdot y3 - x \cdot y2\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -5.5 \cdot 10^{-296}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-113}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{+14}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{+115}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 10: 30.7% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ t_2 := k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ t_3 := y0 \cdot y3 - t \cdot i\\ \mathbf{if}\;y5 \leq -2.7 \cdot 10^{+258}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y5 \leq -1.25 \cdot 10^{+42}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -1.95 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -8 \cdot 10^{-87}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -3 \cdot 10^{-175}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 3.2 \cdot 10^{-267}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 1.05 \cdot 10^{-109}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 3.4 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 1.65 \cdot 10^{+19}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 1.35 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq 4.2 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y5 \cdot t_3\right)\\ \mathbf{elif}\;y5 \leq 5.4 \cdot 10^{+212}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3 \cdot \left(j \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5)))))
        (t_2 (* k (* y5 (- (* y i) (* y0 y2)))))
        (t_3 (- (* y0 y3) (* t i))))
   (if (<= y5 -2.7e+258)
     t_2
     (if (<= y5 -1.25e+42)
       t_1
       (if (<= y5 -1.95e-25)
         (* (* j y4) (- (* t b) (* y1 y3)))
         (if (<= y5 -8e-87)
           (* y5 (* y (- (* i k) (* a y3))))
           (if (<= y5 -3e-175)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y5 3.2e-267)
               (* k (* z (- (* b y0) (* i y1))))
               (if (<= y5 1.05e-109)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= y5 3.4e-43)
                   (* y1 (* y4 (- (* k y2) (* j y3))))
                   (if (<= y5 1.65e+19)
                     t_1
                     (if (<= y5 1.35e+29)
                       (* c (* x (* y0 y2)))
                       (if (<= y5 4.2e+111)
                         (* j (* y5 t_3))
                         (if (<= y5 5.4e+212)
                           t_2
                           (* t_3 (* j y5))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = k * (y5 * ((y * i) - (y0 * y2)));
	double t_3 = (y0 * y3) - (t * i);
	double tmp;
	if (y5 <= -2.7e+258) {
		tmp = t_2;
	} else if (y5 <= -1.25e+42) {
		tmp = t_1;
	} else if (y5 <= -1.95e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -8e-87) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -3e-175) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 3.2e-267) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 1.05e-109) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 3.4e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 1.65e+19) {
		tmp = t_1;
	} else if (y5 <= 1.35e+29) {
		tmp = c * (x * (y0 * y2));
	} else if (y5 <= 4.2e+111) {
		tmp = j * (y5 * t_3);
	} else if (y5 <= 5.4e+212) {
		tmp = t_2;
	} else {
		tmp = t_3 * (j * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    t_2 = k * (y5 * ((y * i) - (y0 * y2)))
    t_3 = (y0 * y3) - (t * i)
    if (y5 <= (-2.7d+258)) then
        tmp = t_2
    else if (y5 <= (-1.25d+42)) then
        tmp = t_1
    else if (y5 <= (-1.95d-25)) then
        tmp = (j * y4) * ((t * b) - (y1 * y3))
    else if (y5 <= (-8d-87)) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else if (y5 <= (-3d-175)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 3.2d-267) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y5 <= 1.05d-109) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 3.4d-43) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y5 <= 1.65d+19) then
        tmp = t_1
    else if (y5 <= 1.35d+29) then
        tmp = c * (x * (y0 * y2))
    else if (y5 <= 4.2d+111) then
        tmp = j * (y5 * t_3)
    else if (y5 <= 5.4d+212) then
        tmp = t_2
    else
        tmp = t_3 * (j * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = k * (y5 * ((y * i) - (y0 * y2)));
	double t_3 = (y0 * y3) - (t * i);
	double tmp;
	if (y5 <= -2.7e+258) {
		tmp = t_2;
	} else if (y5 <= -1.25e+42) {
		tmp = t_1;
	} else if (y5 <= -1.95e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -8e-87) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -3e-175) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 3.2e-267) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 1.05e-109) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 3.4e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 1.65e+19) {
		tmp = t_1;
	} else if (y5 <= 1.35e+29) {
		tmp = c * (x * (y0 * y2));
	} else if (y5 <= 4.2e+111) {
		tmp = j * (y5 * t_3);
	} else if (y5 <= 5.4e+212) {
		tmp = t_2;
	} else {
		tmp = t_3 * (j * y5);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	t_2 = k * (y5 * ((y * i) - (y0 * y2)))
	t_3 = (y0 * y3) - (t * i)
	tmp = 0
	if y5 <= -2.7e+258:
		tmp = t_2
	elif y5 <= -1.25e+42:
		tmp = t_1
	elif y5 <= -1.95e-25:
		tmp = (j * y4) * ((t * b) - (y1 * y3))
	elif y5 <= -8e-87:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	elif y5 <= -3e-175:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 3.2e-267:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y5 <= 1.05e-109:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 3.4e-43:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y5 <= 1.65e+19:
		tmp = t_1
	elif y5 <= 1.35e+29:
		tmp = c * (x * (y0 * y2))
	elif y5 <= 4.2e+111:
		tmp = j * (y5 * t_3)
	elif y5 <= 5.4e+212:
		tmp = t_2
	else:
		tmp = t_3 * (j * y5)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	t_2 = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))))
	t_3 = Float64(Float64(y0 * y3) - Float64(t * i))
	tmp = 0.0
	if (y5 <= -2.7e+258)
		tmp = t_2;
	elseif (y5 <= -1.25e+42)
		tmp = t_1;
	elseif (y5 <= -1.95e-25)
		tmp = Float64(Float64(j * y4) * Float64(Float64(t * b) - Float64(y1 * y3)));
	elseif (y5 <= -8e-87)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (y5 <= -3e-175)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 3.2e-267)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y5 <= 1.05e-109)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 3.4e-43)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y5 <= 1.65e+19)
		tmp = t_1;
	elseif (y5 <= 1.35e+29)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y5 <= 4.2e+111)
		tmp = Float64(j * Float64(y5 * t_3));
	elseif (y5 <= 5.4e+212)
		tmp = t_2;
	else
		tmp = Float64(t_3 * Float64(j * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	t_2 = k * (y5 * ((y * i) - (y0 * y2)));
	t_3 = (y0 * y3) - (t * i);
	tmp = 0.0;
	if (y5 <= -2.7e+258)
		tmp = t_2;
	elseif (y5 <= -1.25e+42)
		tmp = t_1;
	elseif (y5 <= -1.95e-25)
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	elseif (y5 <= -8e-87)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	elseif (y5 <= -3e-175)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 3.2e-267)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y5 <= 1.05e-109)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 3.4e-43)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y5 <= 1.65e+19)
		tmp = t_1;
	elseif (y5 <= 1.35e+29)
		tmp = c * (x * (y0 * y2));
	elseif (y5 <= 4.2e+111)
		tmp = j * (y5 * t_3);
	elseif (y5 <= 5.4e+212)
		tmp = t_2;
	else
		tmp = t_3 * (j * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -2.7e+258], t$95$2, If[LessEqual[y5, -1.25e+42], t$95$1, If[LessEqual[y5, -1.95e-25], N[(N[(j * y4), $MachinePrecision] * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -8e-87], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -3e-175], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.2e-267], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.05e-109], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.4e-43], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.65e+19], t$95$1, If[LessEqual[y5, 1.35e+29], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.2e+111], N[(j * N[(y5 * t$95$3), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.4e+212], t$95$2, N[(t$95$3 * N[(j * y5), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if y5 < -2.69999999999999996e258 or 4.1999999999999999e111 < y5 < 5.4e212

   1. Initial program 8.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 69.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 69.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -2.69999999999999996e258 < y5 < -1.25000000000000002e42 or 3.4000000000000001e-43 < y5 < 1.65e19

   1. Initial program 29.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 38.7%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 52.5%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -1.25000000000000002e42 < y5 < -1.95e-25

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 59.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y4 around inf 65.4%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 53.9%

         \[\leadsto \color{blue}{\left(j \cdot y4\right) \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)} \]

      2. *-commutative 53.9%

         \[\leadsto \color{blue}{\left(y4 \cdot j\right)} \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \]

      3. +-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \]

      4. mul-1-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \]

      5. unsub-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \]

      6. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(\color{blue}{t \cdot b} - y1 \cdot y3\right) \]

      7. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(t \cdot b - \color{blue}{y3 \cdot y1}\right) \]

   6. Simplified 53.9%

      \[\leadsto \color{blue}{\left(y4 \cdot j\right) \cdot \left(t \cdot b - y3 \cdot y1\right)} \]

   if -1.95e-25 < y5 < -8.00000000000000014e-87

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 65.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 37.1%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.1%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 37.1%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 37.1%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if -8.00000000000000014e-87 < y5 < -3e-175

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -3e-175 < y5 < 3.19999999999999986e-267

   1. Initial program 35.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 40.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 43.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.6%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 43.6%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 43.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 3.19999999999999986e-267 < y5 < 1.04999999999999998e-109

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 1.04999999999999998e-109 < y5 < 3.4000000000000001e-43

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 52.2%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 1.65e19 < y5 < 1.35e29

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 100.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 67.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 100.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 100.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if 1.35e29 < y5 < 4.1999999999999999e111

   1. Initial program 33.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 39.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 50.7%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 50.7%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if 5.4e212 < y5

   1. Initial program 27.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 27.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 69.9%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 73.3%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)} \]

      2. *-commutative 73.3%

         \[\leadsto \color{blue}{\left(y5 \cdot j\right)} \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right) \]

      3. +-commutative 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)} \]

      4. mul-1-neg 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right) \]

      5. unsub-neg 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)} \]

      6. *-commutative 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right) \]

      7. *-commutative 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right) \]

   6. Simplified 73.3%

      \[\leadsto \color{blue}{\left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - t \cdot i\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 54.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -2.7 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.25 \cdot 10^{+42}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -1.95 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -8 \cdot 10^{-87}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -3 \cdot 10^{-175}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 3.2 \cdot 10^{-267}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 1.05 \cdot 10^{-109}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 3.4 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 1.65 \cdot 10^{+19}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 1.35 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq 4.2 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.4 \cdot 10^{+212}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y0 \cdot y3 - t \cdot i\right) \cdot \left(j \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 30.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ t_2 := k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ t_3 := y0 \cdot y3 - t \cdot i\\ \mathbf{if}\;y5 \leq -7.6 \cdot 10^{+258}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y5 \leq -7.8 \cdot 10^{+41}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -2.7 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -2.8 \cdot 10^{-87}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -3.7 \cdot 10^{-174}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 5.3 \cdot 10^{-266}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{elif}\;y5 \leq 5.5 \cdot 10^{-110}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 6.5 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 1.7 \cdot 10^{+18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 1.18 \cdot 10^{+30}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq 4.05 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y5 \cdot t_3\right)\\ \mathbf{elif}\;y5 \leq 4.1 \cdot 10^{+210}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3 \cdot \left(j \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5)))))
        (t_2 (* k (* y5 (- (* y i) (* y0 y2)))))
        (t_3 (- (* y0 y3) (* t i))))
   (if (<= y5 -7.6e+258)
     t_2
     (if (<= y5 -7.8e+41)
       t_1
       (if (<= y5 -2.7e-25)
         (* (* j y4) (- (* t b) (* y1 y3)))
         (if (<= y5 -2.8e-87)
           (* y5 (* y (- (* i k) (* a y3))))
           (if (<= y5 -3.7e-174)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y5 5.3e-266)
               (* (- (* b y0) (* i y1)) (* z k))
               (if (<= y5 5.5e-110)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= y5 6.5e-43)
                   (* y1 (* y4 (- (* k y2) (* j y3))))
                   (if (<= y5 1.7e+18)
                     t_1
                     (if (<= y5 1.18e+30)
                       (* c (* x (* y0 y2)))
                       (if (<= y5 4.05e+111)
                         (* j (* y5 t_3))
                         (if (<= y5 4.1e+210)
                           t_2
                           (* t_3 (* j y5))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = k * (y5 * ((y * i) - (y0 * y2)));
	double t_3 = (y0 * y3) - (t * i);
	double tmp;
	if (y5 <= -7.6e+258) {
		tmp = t_2;
	} else if (y5 <= -7.8e+41) {
		tmp = t_1;
	} else if (y5 <= -2.7e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -2.8e-87) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -3.7e-174) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 5.3e-266) {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	} else if (y5 <= 5.5e-110) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 6.5e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 1.7e+18) {
		tmp = t_1;
	} else if (y5 <= 1.18e+30) {
		tmp = c * (x * (y0 * y2));
	} else if (y5 <= 4.05e+111) {
		tmp = j * (y5 * t_3);
	} else if (y5 <= 4.1e+210) {
		tmp = t_2;
	} else {
		tmp = t_3 * (j * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    t_2 = k * (y5 * ((y * i) - (y0 * y2)))
    t_3 = (y0 * y3) - (t * i)
    if (y5 <= (-7.6d+258)) then
        tmp = t_2
    else if (y5 <= (-7.8d+41)) then
        tmp = t_1
    else if (y5 <= (-2.7d-25)) then
        tmp = (j * y4) * ((t * b) - (y1 * y3))
    else if (y5 <= (-2.8d-87)) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else if (y5 <= (-3.7d-174)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 5.3d-266) then
        tmp = ((b * y0) - (i * y1)) * (z * k)
    else if (y5 <= 5.5d-110) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 6.5d-43) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y5 <= 1.7d+18) then
        tmp = t_1
    else if (y5 <= 1.18d+30) then
        tmp = c * (x * (y0 * y2))
    else if (y5 <= 4.05d+111) then
        tmp = j * (y5 * t_3)
    else if (y5 <= 4.1d+210) then
        tmp = t_2
    else
        tmp = t_3 * (j * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = k * (y5 * ((y * i) - (y0 * y2)));
	double t_3 = (y0 * y3) - (t * i);
	double tmp;
	if (y5 <= -7.6e+258) {
		tmp = t_2;
	} else if (y5 <= -7.8e+41) {
		tmp = t_1;
	} else if (y5 <= -2.7e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -2.8e-87) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -3.7e-174) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 5.3e-266) {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	} else if (y5 <= 5.5e-110) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 6.5e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 1.7e+18) {
		tmp = t_1;
	} else if (y5 <= 1.18e+30) {
		tmp = c * (x * (y0 * y2));
	} else if (y5 <= 4.05e+111) {
		tmp = j * (y5 * t_3);
	} else if (y5 <= 4.1e+210) {
		tmp = t_2;
	} else {
		tmp = t_3 * (j * y5);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	t_2 = k * (y5 * ((y * i) - (y0 * y2)))
	t_3 = (y0 * y3) - (t * i)
	tmp = 0
	if y5 <= -7.6e+258:
		tmp = t_2
	elif y5 <= -7.8e+41:
		tmp = t_1
	elif y5 <= -2.7e-25:
		tmp = (j * y4) * ((t * b) - (y1 * y3))
	elif y5 <= -2.8e-87:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	elif y5 <= -3.7e-174:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 5.3e-266:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	elif y5 <= 5.5e-110:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 6.5e-43:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y5 <= 1.7e+18:
		tmp = t_1
	elif y5 <= 1.18e+30:
		tmp = c * (x * (y0 * y2))
	elif y5 <= 4.05e+111:
		tmp = j * (y5 * t_3)
	elif y5 <= 4.1e+210:
		tmp = t_2
	else:
		tmp = t_3 * (j * y5)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	t_2 = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))))
	t_3 = Float64(Float64(y0 * y3) - Float64(t * i))
	tmp = 0.0
	if (y5 <= -7.6e+258)
		tmp = t_2;
	elseif (y5 <= -7.8e+41)
		tmp = t_1;
	elseif (y5 <= -2.7e-25)
		tmp = Float64(Float64(j * y4) * Float64(Float64(t * b) - Float64(y1 * y3)));
	elseif (y5 <= -2.8e-87)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (y5 <= -3.7e-174)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 5.3e-266)
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	elseif (y5 <= 5.5e-110)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 6.5e-43)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y5 <= 1.7e+18)
		tmp = t_1;
	elseif (y5 <= 1.18e+30)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y5 <= 4.05e+111)
		tmp = Float64(j * Float64(y5 * t_3));
	elseif (y5 <= 4.1e+210)
		tmp = t_2;
	else
		tmp = Float64(t_3 * Float64(j * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	t_2 = k * (y5 * ((y * i) - (y0 * y2)));
	t_3 = (y0 * y3) - (t * i);
	tmp = 0.0;
	if (y5 <= -7.6e+258)
		tmp = t_2;
	elseif (y5 <= -7.8e+41)
		tmp = t_1;
	elseif (y5 <= -2.7e-25)
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	elseif (y5 <= -2.8e-87)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	elseif (y5 <= -3.7e-174)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 5.3e-266)
		tmp = ((b * y0) - (i * y1)) * (z * k);
	elseif (y5 <= 5.5e-110)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 6.5e-43)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y5 <= 1.7e+18)
		tmp = t_1;
	elseif (y5 <= 1.18e+30)
		tmp = c * (x * (y0 * y2));
	elseif (y5 <= 4.05e+111)
		tmp = j * (y5 * t_3);
	elseif (y5 <= 4.1e+210)
		tmp = t_2;
	else
		tmp = t_3 * (j * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -7.6e+258], t$95$2, If[LessEqual[y5, -7.8e+41], t$95$1, If[LessEqual[y5, -2.7e-25], N[(N[(j * y4), $MachinePrecision] * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -2.8e-87], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -3.7e-174], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.3e-266], N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.5e-110], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 6.5e-43], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.7e+18], t$95$1, If[LessEqual[y5, 1.18e+30], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.05e+111], N[(j * N[(y5 * t$95$3), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.1e+210], t$95$2, N[(t$95$3 * N[(j * y5), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if y5 < -7.60000000000000018e258 or 4.04999999999999985e111 < y5 < 4.10000000000000001e210

   1. Initial program 8.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 69.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 69.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 69.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -7.60000000000000018e258 < y5 < -7.7999999999999994e41 or 6.50000000000000001e-43 < y5 < 1.7e18

   1. Initial program 29.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 38.7%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 52.5%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -7.7999999999999994e41 < y5 < -2.70000000000000016e-25

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 59.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y4 around inf 65.4%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 53.9%

         \[\leadsto \color{blue}{\left(j \cdot y4\right) \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)} \]

      2. *-commutative 53.9%

         \[\leadsto \color{blue}{\left(y4 \cdot j\right)} \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \]

      3. +-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \]

      4. mul-1-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \]

      5. unsub-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \]

      6. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(\color{blue}{t \cdot b} - y1 \cdot y3\right) \]

      7. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(t \cdot b - \color{blue}{y3 \cdot y1}\right) \]

   6. Simplified 53.9%

      \[\leadsto \color{blue}{\left(y4 \cdot j\right) \cdot \left(t \cdot b - y3 \cdot y1\right)} \]

   if -2.70000000000000016e-25 < y5 < -2.8000000000000001e-87

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 65.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 37.1%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.1%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 37.1%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 37.1%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if -2.8000000000000001e-87 < y5 < -3.7000000000000001e-174

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -3.7000000000000001e-174 < y5 < 5.3000000000000003e-266

   1. Initial program 35.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 40.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around -inf 43.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 43.6%

         \[\leadsto \color{blue}{-k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

      2. associate-*r* 44.7%

         \[\leadsto -\color{blue}{\left(k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      3. distribute-lft-neg-in 44.7%

         \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      4. *-commutative 44.7%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      5. *-commutative 44.7%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   6. Simplified 44.7%

      \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   if 5.3000000000000003e-266 < y5 < 5.4999999999999998e-110

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 5.4999999999999998e-110 < y5 < 6.50000000000000001e-43

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 52.2%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 1.7e18 < y5 < 1.18e30

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 100.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 67.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 100.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 100.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if 1.18e30 < y5 < 4.04999999999999985e111

   1. Initial program 33.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 39.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 50.7%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 50.7%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 50.7%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if 4.10000000000000001e210 < y5

   1. Initial program 27.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 27.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 69.9%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 73.3%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)} \]

      2. *-commutative 73.3%

         \[\leadsto \color{blue}{\left(y5 \cdot j\right)} \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right) \]

      3. +-commutative 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)} \]

      4. mul-1-neg 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right) \]

      5. unsub-neg 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)} \]

      6. *-commutative 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right) \]

      7. *-commutative 73.3%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right) \]

   6. Simplified 73.3%

      \[\leadsto \color{blue}{\left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - t \cdot i\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 54.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -7.6 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -7.8 \cdot 10^{+41}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -2.7 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -2.8 \cdot 10^{-87}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -3.7 \cdot 10^{-174}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 5.3 \cdot 10^{-266}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{elif}\;y5 \leq 5.5 \cdot 10^{-110}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 6.5 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 1.7 \cdot 10^{+18}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 1.18 \cdot 10^{+30}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq 4.05 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 4.1 \cdot 10^{+210}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y0 \cdot y3 - t \cdot i\right) \cdot \left(j \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 32.2% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{if}\;t \leq -8 \cdot 10^{+151}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;t \leq -7.5 \cdot 10^{+72}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -2.7:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-121}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -2.1 \cdot 10^{-138}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -2.95 \cdot 10^{-229}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -7.6 \cdot 10^{-296}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-112}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.55 \cdot 10^{+19}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{+116}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y0 (- (* z b) (* y2 y5))))))
   (if (<= t -8e+151)
     (* (* i j) (- (* x y1) (* t y5)))
     (if (<= t -7.5e+72)
       (*
        y4
        (+
         (+ (* b (- (* t j) (* y k))) (* y1 (- (* k y2) (* j y3))))
         (* c (- (* y y3) (* t y2)))))
       (if (<= t -2.7)
         t_1
         (if (<= t -9e-121)
           (* x (* y (- (* a b) (* c i))))
           (if (<= t -2.1e-138)
             t_1
             (if (<= t -2.95e-229)
               (* y3 (* y4 (- (* y c) (* j y1))))
               (if (<= t -7.6e-296)
                 (*
                  y5
                  (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2)))))
                 (if (<= t 6.8e-112)
                   (*
                    y3
                    (+
                     (* y (- (* c y4) (* a y5)))
                     (+
                      (* j (- (* y0 y5) (* y1 y4)))
                      (* z (- (* a y1) (* c y0))))))
                   (if (<= t 3.55e+19)
                     (* k (* z (- (* b y0) (* i y1))))
                     (if (<= t 1.15e+116)
                       (* y5 (* y (- (* i k) (* a y3))))
                       (* j (* y5 (- (* y0 y3) (* t i))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y0 * ((z * b) - (y2 * y5)));
	double tmp;
	if (t <= -8e+151) {
		tmp = (i * j) * ((x * y1) - (t * y5));
	} else if (t <= -7.5e+72) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (t <= -2.7) {
		tmp = t_1;
	} else if (t <= -9e-121) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (t <= -2.1e-138) {
		tmp = t_1;
	} else if (t <= -2.95e-229) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (t <= -7.6e-296) {
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	} else if (t <= 6.8e-112) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 3.55e+19) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (t <= 1.15e+116) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = k * (y0 * ((z * b) - (y2 * y5)))
    if (t <= (-8d+151)) then
        tmp = (i * j) * ((x * y1) - (t * y5))
    else if (t <= (-7.5d+72)) then
        tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (t <= (-2.7d0)) then
        tmp = t_1
    else if (t <= (-9d-121)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (t <= (-2.1d-138)) then
        tmp = t_1
    else if (t <= (-2.95d-229)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (t <= (-7.6d-296)) then
        tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))))
    else if (t <= 6.8d-112) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
    else if (t <= 3.55d+19) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (t <= 1.15d+116) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y0 * ((z * b) - (y2 * y5)));
	double tmp;
	if (t <= -8e+151) {
		tmp = (i * j) * ((x * y1) - (t * y5));
	} else if (t <= -7.5e+72) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (t <= -2.7) {
		tmp = t_1;
	} else if (t <= -9e-121) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (t <= -2.1e-138) {
		tmp = t_1;
	} else if (t <= -2.95e-229) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (t <= -7.6e-296) {
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	} else if (t <= 6.8e-112) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 3.55e+19) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (t <= 1.15e+116) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y0 * ((z * b) - (y2 * y5)))
	tmp = 0
	if t <= -8e+151:
		tmp = (i * j) * ((x * y1) - (t * y5))
	elif t <= -7.5e+72:
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif t <= -2.7:
		tmp = t_1
	elif t <= -9e-121:
		tmp = x * (y * ((a * b) - (c * i)))
	elif t <= -2.1e-138:
		tmp = t_1
	elif t <= -2.95e-229:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif t <= -7.6e-296:
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))))
	elif t <= 6.8e-112:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	elif t <= 3.55e+19:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif t <= 1.15e+116:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(y0 * Float64(Float64(z * b) - Float64(y2 * y5))))
	tmp = 0.0
	if (t <= -8e+151)
		tmp = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)));
	elseif (t <= -7.5e+72)
		tmp = Float64(y4 * Float64(Float64(Float64(b * Float64(Float64(t * j) - Float64(y * k))) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (t <= -2.7)
		tmp = t_1;
	elseif (t <= -9e-121)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (t <= -2.1e-138)
		tmp = t_1;
	elseif (t <= -2.95e-229)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (t <= -7.6e-296)
		tmp = Float64(y5 * Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (t <= 6.8e-112)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	elseif (t <= 3.55e+19)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (t <= 1.15e+116)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (y0 * ((z * b) - (y2 * y5)));
	tmp = 0.0;
	if (t <= -8e+151)
		tmp = (i * j) * ((x * y1) - (t * y5));
	elseif (t <= -7.5e+72)
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (t <= -2.7)
		tmp = t_1;
	elseif (t <= -9e-121)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (t <= -2.1e-138)
		tmp = t_1;
	elseif (t <= -2.95e-229)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (t <= -7.6e-296)
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	elseif (t <= 6.8e-112)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	elseif (t <= 3.55e+19)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (t <= 1.15e+116)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(y0 * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -8e+151], N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -7.5e+72], N[(y4 * N[(N[(N[(b * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.7], t$95$1, If[LessEqual[t, -9e-121], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.1e-138], t$95$1, If[LessEqual[t, -2.95e-229], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -7.6e-296], N[(y5 * N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.8e-112], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.55e+19], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.15e+116], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -8.00000000000000014e151

   1. Initial program 12.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 58.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.6%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 55.6%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 55.6%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]

   if -8.00000000000000014e151 < t < -7.50000000000000027e72

   1. Initial program 32.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 69.4%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -7.50000000000000027e72 < t < -2.7000000000000002 or -9.0000000000000007e-121 < t < -2.09999999999999986e-138

   1. Initial program 30.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 42.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 57.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 57.5%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 57.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 57.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 57.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   if -2.7000000000000002 < t < -9.0000000000000007e-121

   1. Initial program 23.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 45.7%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 55.4%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if -2.09999999999999986e-138 < t < -2.9500000000000002e-229

   1. Initial program 36.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 32.5%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 51.4%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 51.4%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 51.4%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -2.9500000000000002e-229 < t < -7.6000000000000004e-296

   1. Initial program 35.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 67.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   4. Taylor expanded in a around 0 67.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} \]

   if -7.6000000000000004e-296 < t < 6.7999999999999996e-112

   1. Initial program 37.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 62.9%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if 6.7999999999999996e-112 < t < 3.55e19

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 41.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 55.2%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 55.2%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 55.2%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 55.2%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 3.55e19 < t < 1.14999999999999997e116

   1. Initial program 39.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 48.0%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 61.5%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 61.5%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 61.5%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 61.5%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if 1.14999999999999997e116 < t

   1. Initial program 39.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 38.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 55.6%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 55.6%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 55.6%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 55.6%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 55.6%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 55.6%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 55.6%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 58.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -8 \cdot 10^{+151}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;t \leq -7.5 \cdot 10^{+72}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -2.7:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-121}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -2.1 \cdot 10^{-138}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -2.95 \cdot 10^{-229}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -7.6 \cdot 10^{-296}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-112}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.55 \cdot 10^{+19}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{+116}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 38.8% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y4 - i \cdot y5\\ t_2 := t \cdot y2 - y \cdot y3\\ t_3 := \left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ t_4 := z \cdot t - x \cdot y\\ t_5 := y0 \cdot y5 - y1 \cdot y4\\ t_6 := a \cdot y1 - c \cdot y0\\ \mathbf{if}\;j \leq -3.8 \cdot 10^{+142}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot t_5 + t \cdot t_1\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2 \cdot 10^{+95}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_2 - \left(b \cdot t_4 - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq -2.15 \cdot 10^{+44}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq -4.3 \cdot 10^{-23}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot t_1\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 6.2 \cdot 10^{-257}:\\ \;\;\;\;c \cdot \left(\left(i \cdot t_4 + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 3.3 \cdot 10^{-178}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot t_6\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{-86}:\\ \;\;\;\;y5 \cdot \left(a \cdot t_2 + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq 5.8 \cdot 10^{+127}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot t_5 + z \cdot t_6\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y4) (* i y5)))
        (t_2 (- (* t y2) (* y y3)))
        (t_3 (* (* i j) (- (* x y1) (* t y5))))
        (t_4 (- (* z t) (* x y)))
        (t_5 (- (* y0 y5) (* y1 y4)))
        (t_6 (- (* a y1) (* c y0))))
   (if (<= j -3.8e+142)
     (* j (+ (+ (* y3 t_5) (* t t_1)) (* x (- (* i y1) (* b y0)))))
     (if (<= j -2e+95)
       (* a (- (* y5 t_2) (- (* b t_4) (* y1 (- (* z y3) (* x y2))))))
       (if (<= j -2.15e+44)
         t_3
         (if (<= j -4.3e-23)
           (*
            t
            (+
             (+ (* z (- (* c i) (* a b))) (* j t_1))
             (* y2 (- (* a y5) (* c y4)))))
           (if (<= j 6.2e-257)
             (*
              c
              (+
               (+ (* i t_4) (* y0 (- (* x y2) (* z y3))))
               (* y4 (- (* y y3) (* t y2)))))
             (if (<= j 3.3e-178)
               (* (* z y3) t_6)
               (if (<= j 6.5e-86)
                 (*
                  y5
                  (+
                   (* a t_2)
                   (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2))))))
                 (if (<= j 5.8e+127)
                   (*
                    y3
                    (+ (* y (- (* c y4) (* a y5))) (+ (* j t_5) (* z t_6))))
                   t_3))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y4) - (i * y5);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = (i * j) * ((x * y1) - (t * y5));
	double t_4 = (z * t) - (x * y);
	double t_5 = (y0 * y5) - (y1 * y4);
	double t_6 = (a * y1) - (c * y0);
	double tmp;
	if (j <= -3.8e+142) {
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	} else if (j <= -2e+95) {
		tmp = a * ((y5 * t_2) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))));
	} else if (j <= -2.15e+44) {
		tmp = t_3;
	} else if (j <= -4.3e-23) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	} else if (j <= 6.2e-257) {
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 3.3e-178) {
		tmp = (z * y3) * t_6;
	} else if (j <= 6.5e-86) {
		tmp = y5 * ((a * t_2) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (j <= 5.8e+127) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_5) + (z * t_6)));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = (b * y4) - (i * y5)
    t_2 = (t * y2) - (y * y3)
    t_3 = (i * j) * ((x * y1) - (t * y5))
    t_4 = (z * t) - (x * y)
    t_5 = (y0 * y5) - (y1 * y4)
    t_6 = (a * y1) - (c * y0)
    if (j <= (-3.8d+142)) then
        tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))))
    else if (j <= (-2d+95)) then
        tmp = a * ((y5 * t_2) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))))
    else if (j <= (-2.15d+44)) then
        tmp = t_3
    else if (j <= (-4.3d-23)) then
        tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))))
    else if (j <= 6.2d-257) then
        tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
    else if (j <= 3.3d-178) then
        tmp = (z * y3) * t_6
    else if (j <= 6.5d-86) then
        tmp = y5 * ((a * t_2) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
    else if (j <= 5.8d+127) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_5) + (z * t_6)))
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y4) - (i * y5);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = (i * j) * ((x * y1) - (t * y5));
	double t_4 = (z * t) - (x * y);
	double t_5 = (y0 * y5) - (y1 * y4);
	double t_6 = (a * y1) - (c * y0);
	double tmp;
	if (j <= -3.8e+142) {
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	} else if (j <= -2e+95) {
		tmp = a * ((y5 * t_2) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))));
	} else if (j <= -2.15e+44) {
		tmp = t_3;
	} else if (j <= -4.3e-23) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	} else if (j <= 6.2e-257) {
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 3.3e-178) {
		tmp = (z * y3) * t_6;
	} else if (j <= 6.5e-86) {
		tmp = y5 * ((a * t_2) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (j <= 5.8e+127) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_5) + (z * t_6)));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (b * y4) - (i * y5)
	t_2 = (t * y2) - (y * y3)
	t_3 = (i * j) * ((x * y1) - (t * y5))
	t_4 = (z * t) - (x * y)
	t_5 = (y0 * y5) - (y1 * y4)
	t_6 = (a * y1) - (c * y0)
	tmp = 0
	if j <= -3.8e+142:
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))))
	elif j <= -2e+95:
		tmp = a * ((y5 * t_2) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))))
	elif j <= -2.15e+44:
		tmp = t_3
	elif j <= -4.3e-23:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))))
	elif j <= 6.2e-257:
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
	elif j <= 3.3e-178:
		tmp = (z * y3) * t_6
	elif j <= 6.5e-86:
		tmp = y5 * ((a * t_2) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
	elif j <= 5.8e+127:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_5) + (z * t_6)))
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(b * y4) - Float64(i * y5))
	t_2 = Float64(Float64(t * y2) - Float64(y * y3))
	t_3 = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)))
	t_4 = Float64(Float64(z * t) - Float64(x * y))
	t_5 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_6 = Float64(Float64(a * y1) - Float64(c * y0))
	tmp = 0.0
	if (j <= -3.8e+142)
		tmp = Float64(j * Float64(Float64(Float64(y3 * t_5) + Float64(t * t_1)) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (j <= -2e+95)
		tmp = Float64(a * Float64(Float64(y5 * t_2) - Float64(Float64(b * t_4) - Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))));
	elseif (j <= -2.15e+44)
		tmp = t_3;
	elseif (j <= -4.3e-23)
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * t_1)) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= 6.2e-257)
		tmp = Float64(c * Float64(Float64(Float64(i * t_4) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= 3.3e-178)
		tmp = Float64(Float64(z * y3) * t_6);
	elseif (j <= 6.5e-86)
		tmp = Float64(y5 * Float64(Float64(a * t_2) + Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (j <= 5.8e+127)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * t_5) + Float64(z * t_6))));
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (b * y4) - (i * y5);
	t_2 = (t * y2) - (y * y3);
	t_3 = (i * j) * ((x * y1) - (t * y5));
	t_4 = (z * t) - (x * y);
	t_5 = (y0 * y5) - (y1 * y4);
	t_6 = (a * y1) - (c * y0);
	tmp = 0.0;
	if (j <= -3.8e+142)
		tmp = j * (((y3 * t_5) + (t * t_1)) + (x * ((i * y1) - (b * y0))));
	elseif (j <= -2e+95)
		tmp = a * ((y5 * t_2) - ((b * t_4) - (y1 * ((z * y3) - (x * y2)))));
	elseif (j <= -2.15e+44)
		tmp = t_3;
	elseif (j <= -4.3e-23)
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * ((a * y5) - (c * y4))));
	elseif (j <= 6.2e-257)
		tmp = c * (((i * t_4) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (j <= 3.3e-178)
		tmp = (z * y3) * t_6;
	elseif (j <= 6.5e-86)
		tmp = y5 * ((a * t_2) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	elseif (j <= 5.8e+127)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_5) + (z * t_6)));
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -3.8e+142], N[(j * N[(N[(N[(y3 * t$95$5), $MachinePrecision] + N[(t * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2e+95], N[(a * N[(N[(y5 * t$95$2), $MachinePrecision] - N[(N[(b * t$95$4), $MachinePrecision] - N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.15e+44], t$95$3, If[LessEqual[j, -4.3e-23], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.2e-257], N[(c * N[(N[(N[(i * t$95$4), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.3e-178], N[(N[(z * y3), $MachinePrecision] * t$95$6), $MachinePrecision], If[LessEqual[j, 6.5e-86], N[(y5 * N[(N[(a * t$95$2), $MachinePrecision] + N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5.8e+127], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * t$95$5), $MachinePrecision] + N[(z * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if j < -3.7999999999999999e142

   1. Initial program 24.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 62.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -3.7999999999999999e142 < j < -2.00000000000000004e95

   1. Initial program 36.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in a around inf 64.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if -2.00000000000000004e95 < j < -2.14999999999999991e44 or 5.8000000000000004e127 < j

   1. Initial program 26.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 57.1%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.1%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 55.1%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 55.1%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]

   if -2.14999999999999991e44 < j < -4.30000000000000002e-23

   1. Initial program 42.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in t around inf 58.3%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -4.30000000000000002e-23 < j < 6.20000000000000016e-257

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 48.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 6.20000000000000016e-257 < j < 3.3000000000000002e-178

   1. Initial program 18.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 53.4%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in z around inf 59.6%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 59.6%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   6. Simplified 59.6%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 3.3000000000000002e-178 < j < 6.50000000000000028e-86

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 71.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if 6.50000000000000028e-86 < j < 5.8000000000000004e127

   1. Initial program 39.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 65.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 57.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -3.8 \cdot 10^{+142}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2 \cdot 10^{+95}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) - \left(b \cdot \left(z \cdot t - x \cdot y\right) - y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq -2.15 \cdot 10^{+44}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \mathbf{elif}\;j \leq -4.3 \cdot 10^{-23}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 6.2 \cdot 10^{-257}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 3.3 \cdot 10^{-178}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{-86}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq 5.8 \cdot 10^{+127}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 14: 29.9% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ t_2 := x \cdot c - k \cdot y5\\ \mathbf{if}\;y5 \leq -4.8 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -3.2 \cdot 10^{+42}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -4.5 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -9 \cdot 10^{-88}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -1.12 \cdot 10^{-175}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2 \cdot 10^{-268}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{elif}\;y5 \leq 1.72 \cdot 10^{-109}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 1.5 \cdot 10^{-53}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 2.5 \cdot 10^{-19}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot t_2\right)\\ \mathbf{elif}\;y5 \leq 0.0095:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 1.9 \cdot 10^{+69}:\\ \;\;\;\;\left(y0 \cdot y2\right) \cdot t_2\\ \mathbf{else}:\\ \;\;\;\;\left(y0 \cdot y3 - t \cdot i\right) \cdot \left(j \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5))))) (t_2 (- (* x c) (* k y5))))
   (if (<= y5 -4.8e+258)
     (* k (* y5 (- (* y i) (* y0 y2))))
     (if (<= y5 -3.2e+42)
       t_1
       (if (<= y5 -4.5e-25)
         (* (* j y4) (- (* t b) (* y1 y3)))
         (if (<= y5 -9e-88)
           (* y5 (* y (- (* i k) (* a y3))))
           (if (<= y5 -1.12e-175)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y5 2e-268)
               (* (- (* b y0) (* i y1)) (* z k))
               (if (<= y5 1.72e-109)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= y5 1.5e-53)
                   (* y1 (* y4 (- (* k y2) (* j y3))))
                   (if (<= y5 2.5e-19)
                     (* y0 (* y2 t_2))
                     (if (<= y5 0.0095)
                       t_1
                       (if (<= y5 1.9e+69)
                         (* (* y0 y2) t_2)
                         (* (- (* y0 y3) (* t i)) (* j y5)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = (x * c) - (k * y5);
	double tmp;
	if (y5 <= -4.8e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -3.2e+42) {
		tmp = t_1;
	} else if (y5 <= -4.5e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -9e-88) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -1.12e-175) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 2e-268) {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	} else if (y5 <= 1.72e-109) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 1.5e-53) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 2.5e-19) {
		tmp = y0 * (y2 * t_2);
	} else if (y5 <= 0.0095) {
		tmp = t_1;
	} else if (y5 <= 1.9e+69) {
		tmp = (y0 * y2) * t_2;
	} else {
		tmp = ((y0 * y3) - (t * i)) * (j * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    t_2 = (x * c) - (k * y5)
    if (y5 <= (-4.8d+258)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (y5 <= (-3.2d+42)) then
        tmp = t_1
    else if (y5 <= (-4.5d-25)) then
        tmp = (j * y4) * ((t * b) - (y1 * y3))
    else if (y5 <= (-9d-88)) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else if (y5 <= (-1.12d-175)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 2d-268) then
        tmp = ((b * y0) - (i * y1)) * (z * k)
    else if (y5 <= 1.72d-109) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 1.5d-53) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y5 <= 2.5d-19) then
        tmp = y0 * (y2 * t_2)
    else if (y5 <= 0.0095d0) then
        tmp = t_1
    else if (y5 <= 1.9d+69) then
        tmp = (y0 * y2) * t_2
    else
        tmp = ((y0 * y3) - (t * i)) * (j * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = (x * c) - (k * y5);
	double tmp;
	if (y5 <= -4.8e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -3.2e+42) {
		tmp = t_1;
	} else if (y5 <= -4.5e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -9e-88) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -1.12e-175) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 2e-268) {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	} else if (y5 <= 1.72e-109) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 1.5e-53) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 2.5e-19) {
		tmp = y0 * (y2 * t_2);
	} else if (y5 <= 0.0095) {
		tmp = t_1;
	} else if (y5 <= 1.9e+69) {
		tmp = (y0 * y2) * t_2;
	} else {
		tmp = ((y0 * y3) - (t * i)) * (j * y5);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	t_2 = (x * c) - (k * y5)
	tmp = 0
	if y5 <= -4.8e+258:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif y5 <= -3.2e+42:
		tmp = t_1
	elif y5 <= -4.5e-25:
		tmp = (j * y4) * ((t * b) - (y1 * y3))
	elif y5 <= -9e-88:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	elif y5 <= -1.12e-175:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 2e-268:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	elif y5 <= 1.72e-109:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 1.5e-53:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y5 <= 2.5e-19:
		tmp = y0 * (y2 * t_2)
	elif y5 <= 0.0095:
		tmp = t_1
	elif y5 <= 1.9e+69:
		tmp = (y0 * y2) * t_2
	else:
		tmp = ((y0 * y3) - (t * i)) * (j * y5)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	t_2 = Float64(Float64(x * c) - Float64(k * y5))
	tmp = 0.0
	if (y5 <= -4.8e+258)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (y5 <= -3.2e+42)
		tmp = t_1;
	elseif (y5 <= -4.5e-25)
		tmp = Float64(Float64(j * y4) * Float64(Float64(t * b) - Float64(y1 * y3)));
	elseif (y5 <= -9e-88)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (y5 <= -1.12e-175)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 2e-268)
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	elseif (y5 <= 1.72e-109)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 1.5e-53)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y5 <= 2.5e-19)
		tmp = Float64(y0 * Float64(y2 * t_2));
	elseif (y5 <= 0.0095)
		tmp = t_1;
	elseif (y5 <= 1.9e+69)
		tmp = Float64(Float64(y0 * y2) * t_2);
	else
		tmp = Float64(Float64(Float64(y0 * y3) - Float64(t * i)) * Float64(j * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	t_2 = (x * c) - (k * y5);
	tmp = 0.0;
	if (y5 <= -4.8e+258)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (y5 <= -3.2e+42)
		tmp = t_1;
	elseif (y5 <= -4.5e-25)
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	elseif (y5 <= -9e-88)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	elseif (y5 <= -1.12e-175)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 2e-268)
		tmp = ((b * y0) - (i * y1)) * (z * k);
	elseif (y5 <= 1.72e-109)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 1.5e-53)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y5 <= 2.5e-19)
		tmp = y0 * (y2 * t_2);
	elseif (y5 <= 0.0095)
		tmp = t_1;
	elseif (y5 <= 1.9e+69)
		tmp = (y0 * y2) * t_2;
	else
		tmp = ((y0 * y3) - (t * i)) * (j * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -4.8e+258], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -3.2e+42], t$95$1, If[LessEqual[y5, -4.5e-25], N[(N[(j * y4), $MachinePrecision] * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -9e-88], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1.12e-175], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2e-268], N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.72e-109], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.5e-53], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.5e-19], N[(y0 * N[(y2 * t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 0.0095], t$95$1, If[LessEqual[y5, 1.9e+69], N[(N[(y0 * y2), $MachinePrecision] * t$95$2), $MachinePrecision], N[(N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision] * N[(j * y5), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if y5 < -4.7999999999999999e258

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 36.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -4.7999999999999999e258 < y5 < -3.20000000000000002e42 or 2.5000000000000002e-19 < y5 < 0.00949999999999999976

   1. Initial program 29.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 39.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 52.7%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -3.20000000000000002e42 < y5 < -4.5000000000000001e-25

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 59.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y4 around inf 65.4%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 53.9%

         \[\leadsto \color{blue}{\left(j \cdot y4\right) \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)} \]

      2. *-commutative 53.9%

         \[\leadsto \color{blue}{\left(y4 \cdot j\right)} \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \]

      3. +-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \]

      4. mul-1-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \]

      5. unsub-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \]

      6. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(\color{blue}{t \cdot b} - y1 \cdot y3\right) \]

      7. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(t \cdot b - \color{blue}{y3 \cdot y1}\right) \]

   6. Simplified 53.9%

      \[\leadsto \color{blue}{\left(y4 \cdot j\right) \cdot \left(t \cdot b - y3 \cdot y1\right)} \]

   if -4.5000000000000001e-25 < y5 < -8.99999999999999982e-88

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 65.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 37.1%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.1%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 37.1%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 37.1%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if -8.99999999999999982e-88 < y5 < -1.1200000000000001e-175

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -1.1200000000000001e-175 < y5 < 1.99999999999999992e-268

   1. Initial program 35.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 40.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around -inf 43.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 43.6%

         \[\leadsto \color{blue}{-k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

      2. associate-*r* 44.7%

         \[\leadsto -\color{blue}{\left(k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      3. distribute-lft-neg-in 44.7%

         \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      4. *-commutative 44.7%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      5. *-commutative 44.7%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   6. Simplified 44.7%

      \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   if 1.99999999999999992e-268 < y5 < 1.7200000000000001e-109

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 1.7200000000000001e-109 < y5 < 1.5000000000000001e-53

   1. Initial program 31.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 56.2%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 1.5000000000000001e-53 < y5 < 2.5000000000000002e-19

   1. Initial program 33.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 23.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 68.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 68.7%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 68.7%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 68.7%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 68.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 68.7%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 68.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 68.7%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 68.7%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   if 0.00949999999999999976 < y5 < 1.90000000000000014e69

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 58.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around inf 43.6%

      \[\leadsto \color{blue}{y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(k \cdot y5\right) + c \cdot x\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 58.9%

         \[\leadsto \color{blue}{\left(y0 \cdot y2\right) \cdot \left(-1 \cdot \left(k \cdot y5\right) + c \cdot x\right)} \]

      2. +-commutative 58.9%

         \[\leadsto \left(y0 \cdot y2\right) \cdot \color{blue}{\left(c \cdot x + -1 \cdot \left(k \cdot y5\right)\right)} \]

      3. mul-1-neg 58.9%

         \[\leadsto \left(y0 \cdot y2\right) \cdot \left(c \cdot x + \color{blue}{\left(-k \cdot y5\right)}\right) \]

      4. unsub-neg 58.9%

         \[\leadsto \left(y0 \cdot y2\right) \cdot \color{blue}{\left(c \cdot x - k \cdot y5\right)} \]

      5. *-commutative 58.9%

         \[\leadsto \left(y0 \cdot y2\right) \cdot \left(c \cdot x - \color{blue}{y5 \cdot k}\right) \]

   6. Simplified 58.9%

      \[\leadsto \color{blue}{\left(y0 \cdot y2\right) \cdot \left(c \cdot x - y5 \cdot k\right)} \]

   if 1.90000000000000014e69 < y5

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 60.0%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 63.1%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)} \]

      2. *-commutative 63.1%

         \[\leadsto \color{blue}{\left(y5 \cdot j\right)} \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right) \]

      3. +-commutative 63.1%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)} \]

      4. mul-1-neg 63.1%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right) \]

      5. unsub-neg 63.1%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)} \]

      6. *-commutative 63.1%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right) \]

      7. *-commutative 63.1%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right) \]

   6. Simplified 63.1%

      \[\leadsto \color{blue}{\left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - t \cdot i\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 54.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -4.8 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -3.2 \cdot 10^{+42}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -4.5 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -9 \cdot 10^{-88}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -1.12 \cdot 10^{-175}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2 \cdot 10^{-268}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{elif}\;y5 \leq 1.72 \cdot 10^{-109}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 1.5 \cdot 10^{-53}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 2.5 \cdot 10^{-19}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 0.0095:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 1.9 \cdot 10^{+69}:\\ \;\;\;\;\left(y0 \cdot y2\right) \cdot \left(x \cdot c - k \cdot y5\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y0 \cdot y3 - t \cdot i\right) \cdot \left(j \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 30.3% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ t_2 := c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{if}\;y5 \leq -7.5 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -5.2 \cdot 10^{+41}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -3.9 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -5.2 \cdot 10^{-88}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y5 \leq -1.4 \cdot 10^{-174}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 7.6 \cdot 10^{-261}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{elif}\;y5 \leq 2.5 \cdot 10^{-109}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.5 \cdot 10^{-53}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 2 \cdot 10^{-19}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 6.5 \cdot 10^{+23}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 4.8 \cdot 10^{+101}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\left(y0 \cdot y3 - t \cdot i\right) \cdot \left(j \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5)))))
        (t_2 (* c (* y3 (- (* y y4) (* z y0))))))
   (if (<= y5 -7.5e+258)
     (* k (* y5 (- (* y i) (* y0 y2))))
     (if (<= y5 -5.2e+41)
       t_1
       (if (<= y5 -3.9e-25)
         (* (* j y4) (- (* t b) (* y1 y3)))
         (if (<= y5 -5.2e-88)
           t_2
           (if (<= y5 -1.4e-174)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y5 7.6e-261)
               (* (- (* b y0) (* i y1)) (* z k))
               (if (<= y5 2.5e-109)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= y5 5.5e-53)
                   (* y1 (* y4 (- (* k y2) (* j y3))))
                   (if (<= y5 2e-19)
                     (* y0 (* y2 (- (* x c) (* k y5))))
                     (if (<= y5 6.5e+23)
                       t_1
                       (if (<= y5 4.8e+101)
                         t_2
                         (* (- (* y0 y3) (* t i)) (* j y5)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = c * (y3 * ((y * y4) - (z * y0)));
	double tmp;
	if (y5 <= -7.5e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -5.2e+41) {
		tmp = t_1;
	} else if (y5 <= -3.9e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -5.2e-88) {
		tmp = t_2;
	} else if (y5 <= -1.4e-174) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 7.6e-261) {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	} else if (y5 <= 2.5e-109) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 5.5e-53) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 2e-19) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (y5 <= 6.5e+23) {
		tmp = t_1;
	} else if (y5 <= 4.8e+101) {
		tmp = t_2;
	} else {
		tmp = ((y0 * y3) - (t * i)) * (j * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    t_2 = c * (y3 * ((y * y4) - (z * y0)))
    if (y5 <= (-7.5d+258)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (y5 <= (-5.2d+41)) then
        tmp = t_1
    else if (y5 <= (-3.9d-25)) then
        tmp = (j * y4) * ((t * b) - (y1 * y3))
    else if (y5 <= (-5.2d-88)) then
        tmp = t_2
    else if (y5 <= (-1.4d-174)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 7.6d-261) then
        tmp = ((b * y0) - (i * y1)) * (z * k)
    else if (y5 <= 2.5d-109) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 5.5d-53) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y5 <= 2d-19) then
        tmp = y0 * (y2 * ((x * c) - (k * y5)))
    else if (y5 <= 6.5d+23) then
        tmp = t_1
    else if (y5 <= 4.8d+101) then
        tmp = t_2
    else
        tmp = ((y0 * y3) - (t * i)) * (j * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double t_2 = c * (y3 * ((y * y4) - (z * y0)));
	double tmp;
	if (y5 <= -7.5e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -5.2e+41) {
		tmp = t_1;
	} else if (y5 <= -3.9e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -5.2e-88) {
		tmp = t_2;
	} else if (y5 <= -1.4e-174) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 7.6e-261) {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	} else if (y5 <= 2.5e-109) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 5.5e-53) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 2e-19) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (y5 <= 6.5e+23) {
		tmp = t_1;
	} else if (y5 <= 4.8e+101) {
		tmp = t_2;
	} else {
		tmp = ((y0 * y3) - (t * i)) * (j * y5);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	t_2 = c * (y3 * ((y * y4) - (z * y0)))
	tmp = 0
	if y5 <= -7.5e+258:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif y5 <= -5.2e+41:
		tmp = t_1
	elif y5 <= -3.9e-25:
		tmp = (j * y4) * ((t * b) - (y1 * y3))
	elif y5 <= -5.2e-88:
		tmp = t_2
	elif y5 <= -1.4e-174:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 7.6e-261:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	elif y5 <= 2.5e-109:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 5.5e-53:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y5 <= 2e-19:
		tmp = y0 * (y2 * ((x * c) - (k * y5)))
	elif y5 <= 6.5e+23:
		tmp = t_1
	elif y5 <= 4.8e+101:
		tmp = t_2
	else:
		tmp = ((y0 * y3) - (t * i)) * (j * y5)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	t_2 = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))))
	tmp = 0.0
	if (y5 <= -7.5e+258)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (y5 <= -5.2e+41)
		tmp = t_1;
	elseif (y5 <= -3.9e-25)
		tmp = Float64(Float64(j * y4) * Float64(Float64(t * b) - Float64(y1 * y3)));
	elseif (y5 <= -5.2e-88)
		tmp = t_2;
	elseif (y5 <= -1.4e-174)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 7.6e-261)
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	elseif (y5 <= 2.5e-109)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 5.5e-53)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y5 <= 2e-19)
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (y5 <= 6.5e+23)
		tmp = t_1;
	elseif (y5 <= 4.8e+101)
		tmp = t_2;
	else
		tmp = Float64(Float64(Float64(y0 * y3) - Float64(t * i)) * Float64(j * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	t_2 = c * (y3 * ((y * y4) - (z * y0)));
	tmp = 0.0;
	if (y5 <= -7.5e+258)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (y5 <= -5.2e+41)
		tmp = t_1;
	elseif (y5 <= -3.9e-25)
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	elseif (y5 <= -5.2e-88)
		tmp = t_2;
	elseif (y5 <= -1.4e-174)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 7.6e-261)
		tmp = ((b * y0) - (i * y1)) * (z * k);
	elseif (y5 <= 2.5e-109)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 5.5e-53)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y5 <= 2e-19)
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	elseif (y5 <= 6.5e+23)
		tmp = t_1;
	elseif (y5 <= 4.8e+101)
		tmp = t_2;
	else
		tmp = ((y0 * y3) - (t * i)) * (j * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -7.5e+258], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -5.2e+41], t$95$1, If[LessEqual[y5, -3.9e-25], N[(N[(j * y4), $MachinePrecision] * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -5.2e-88], t$95$2, If[LessEqual[y5, -1.4e-174], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 7.6e-261], N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.5e-109], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.5e-53], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2e-19], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 6.5e+23], t$95$1, If[LessEqual[y5, 4.8e+101], t$95$2, N[(N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision] * N[(j * y5), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y5 < -7.50000000000000032e258

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 36.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -7.50000000000000032e258 < y5 < -5.2000000000000001e41 or 2e-19 < y5 < 6.4999999999999996e23

   1. Initial program 29.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 38.9%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 53.5%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -5.2000000000000001e41 < y5 < -3.9e-25

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 59.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y4 around inf 65.4%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 53.9%

         \[\leadsto \color{blue}{\left(j \cdot y4\right) \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)} \]

      2. *-commutative 53.9%

         \[\leadsto \color{blue}{\left(y4 \cdot j\right)} \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \]

      3. +-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \]

      4. mul-1-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \]

      5. unsub-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \]

      6. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(\color{blue}{t \cdot b} - y1 \cdot y3\right) \]

      7. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(t \cdot b - \color{blue}{y3 \cdot y1}\right) \]

   6. Simplified 53.9%

      \[\leadsto \color{blue}{\left(y4 \cdot j\right) \cdot \left(t \cdot b - y3 \cdot y1\right)} \]

   if -3.9e-25 < y5 < -5.20000000000000027e-88 or 6.4999999999999996e23 < y5 < 4.79999999999999977e101

   1. Initial program 43.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 40.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in c around inf 47.4%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot \left(y0 \cdot z - y \cdot y4\right)\right)\right)} \]

   if -5.20000000000000027e-88 < y5 < -1.39999999999999999e-174

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -1.39999999999999999e-174 < y5 < 7.5999999999999999e-261

   1. Initial program 35.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 40.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around -inf 43.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 43.6%

         \[\leadsto \color{blue}{-k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

      2. associate-*r* 44.7%

         \[\leadsto -\color{blue}{\left(k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      3. distribute-lft-neg-in 44.7%

         \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      4. *-commutative 44.7%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      5. *-commutative 44.7%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   6. Simplified 44.7%

      \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   if 7.5999999999999999e-261 < y5 < 2.5000000000000001e-109

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 2.5000000000000001e-109 < y5 < 5.50000000000000023e-53

   1. Initial program 31.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 56.2%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 5.50000000000000023e-53 < y5 < 2e-19

   1. Initial program 33.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 23.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 68.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 68.7%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 68.7%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 68.7%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 68.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 68.7%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 68.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 68.7%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 68.7%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   if 4.79999999999999977e101 < y5

   1. Initial program 20.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 30.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 62.3%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 68.0%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)} \]

      2. *-commutative 68.0%

         \[\leadsto \color{blue}{\left(y5 \cdot j\right)} \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right) \]

      3. +-commutative 68.0%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)} \]

      4. mul-1-neg 68.0%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right) \]

      5. unsub-neg 68.0%

         \[\leadsto \left(y5 \cdot j\right) \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)} \]

      6. *-commutative 68.0%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right) \]

      7. *-commutative 68.0%

         \[\leadsto \left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right) \]

   6. Simplified 68.0%

      \[\leadsto \color{blue}{\left(y5 \cdot j\right) \cdot \left(y3 \cdot y0 - t \cdot i\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 55.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -7.5 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -5.2 \cdot 10^{+41}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -3.9 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -5.2 \cdot 10^{-88}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;y5 \leq -1.4 \cdot 10^{-174}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 7.6 \cdot 10^{-261}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{elif}\;y5 \leq 2.5 \cdot 10^{-109}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.5 \cdot 10^{-53}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 2 \cdot 10^{-19}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 6.5 \cdot 10^{+23}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 4.8 \cdot 10^{+101}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(y0 \cdot y3 - t \cdot i\right) \cdot \left(j \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 31.1% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{if}\;y5 \leq -2.7 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.1 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -4.5 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -8 \cdot 10^{-87}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -1.1 \cdot 10^{-175}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 4 \cdot 10^{-263}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2.1 \cdot 10^{-108}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 4.8 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 4.8 \cdot 10^{+17}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 5.4 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5))))))
   (if (<= y5 -2.7e+258)
     (* k (* y5 (- (* y i) (* y0 y2))))
     (if (<= y5 -1.1e+43)
       t_1
       (if (<= y5 -4.5e-25)
         (* (* j y4) (- (* t b) (* y1 y3)))
         (if (<= y5 -8e-87)
           (* y5 (* y (- (* i k) (* a y3))))
           (if (<= y5 -1.1e-175)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y5 4e-263)
               (* k (* z (- (* b y0) (* i y1))))
               (if (<= y5 2.1e-108)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= y5 4.8e-43)
                   (* y1 (* y4 (- (* k y2) (* j y3))))
                   (if (<= y5 4.8e+17)
                     t_1
                     (if (<= y5 5.4e+29)
                       (* c (* x (* y0 y2)))
                       (* j (* y5 (- (* y0 y3) (* t i))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double tmp;
	if (y5 <= -2.7e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -1.1e+43) {
		tmp = t_1;
	} else if (y5 <= -4.5e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -8e-87) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -1.1e-175) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 4e-263) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 2.1e-108) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 4.8e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 4.8e+17) {
		tmp = t_1;
	} else if (y5 <= 5.4e+29) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    if (y5 <= (-2.7d+258)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (y5 <= (-1.1d+43)) then
        tmp = t_1
    else if (y5 <= (-4.5d-25)) then
        tmp = (j * y4) * ((t * b) - (y1 * y3))
    else if (y5 <= (-8d-87)) then
        tmp = y5 * (y * ((i * k) - (a * y3)))
    else if (y5 <= (-1.1d-175)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 4d-263) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y5 <= 2.1d-108) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 4.8d-43) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y5 <= 4.8d+17) then
        tmp = t_1
    else if (y5 <= 5.4d+29) then
        tmp = c * (x * (y0 * y2))
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double tmp;
	if (y5 <= -2.7e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -1.1e+43) {
		tmp = t_1;
	} else if (y5 <= -4.5e-25) {
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	} else if (y5 <= -8e-87) {
		tmp = y5 * (y * ((i * k) - (a * y3)));
	} else if (y5 <= -1.1e-175) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 4e-263) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 2.1e-108) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 4.8e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 4.8e+17) {
		tmp = t_1;
	} else if (y5 <= 5.4e+29) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	tmp = 0
	if y5 <= -2.7e+258:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif y5 <= -1.1e+43:
		tmp = t_1
	elif y5 <= -4.5e-25:
		tmp = (j * y4) * ((t * b) - (y1 * y3))
	elif y5 <= -8e-87:
		tmp = y5 * (y * ((i * k) - (a * y3)))
	elif y5 <= -1.1e-175:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 4e-263:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y5 <= 2.1e-108:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 4.8e-43:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y5 <= 4.8e+17:
		tmp = t_1
	elif y5 <= 5.4e+29:
		tmp = c * (x * (y0 * y2))
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	tmp = 0.0
	if (y5 <= -2.7e+258)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (y5 <= -1.1e+43)
		tmp = t_1;
	elseif (y5 <= -4.5e-25)
		tmp = Float64(Float64(j * y4) * Float64(Float64(t * b) - Float64(y1 * y3)));
	elseif (y5 <= -8e-87)
		tmp = Float64(y5 * Float64(y * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (y5 <= -1.1e-175)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 4e-263)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y5 <= 2.1e-108)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 4.8e-43)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y5 <= 4.8e+17)
		tmp = t_1;
	elseif (y5 <= 5.4e+29)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	tmp = 0.0;
	if (y5 <= -2.7e+258)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (y5 <= -1.1e+43)
		tmp = t_1;
	elseif (y5 <= -4.5e-25)
		tmp = (j * y4) * ((t * b) - (y1 * y3));
	elseif (y5 <= -8e-87)
		tmp = y5 * (y * ((i * k) - (a * y3)));
	elseif (y5 <= -1.1e-175)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 4e-263)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y5 <= 2.1e-108)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 4.8e-43)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y5 <= 4.8e+17)
		tmp = t_1;
	elseif (y5 <= 5.4e+29)
		tmp = c * (x * (y0 * y2));
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -2.7e+258], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1.1e+43], t$95$1, If[LessEqual[y5, -4.5e-25], N[(N[(j * y4), $MachinePrecision] * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -8e-87], N[(y5 * N[(y * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1.1e-175], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4e-263], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.1e-108], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.8e-43], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.8e+17], t$95$1, If[LessEqual[y5, 5.4e+29], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y5 < -2.69999999999999996e258

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 36.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -2.69999999999999996e258 < y5 < -1.1e43 or 4.8000000000000004e-43 < y5 < 4.8e17

   1. Initial program 29.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 38.7%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 52.5%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -1.1e43 < y5 < -4.5000000000000001e-25

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 59.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y4 around inf 65.4%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 53.9%

         \[\leadsto \color{blue}{\left(j \cdot y4\right) \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)} \]

      2. *-commutative 53.9%

         \[\leadsto \color{blue}{\left(y4 \cdot j\right)} \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \]

      3. +-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \]

      4. mul-1-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \]

      5. unsub-neg 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \]

      6. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(\color{blue}{t \cdot b} - y1 \cdot y3\right) \]

      7. *-commutative 53.9%

         \[\leadsto \left(y4 \cdot j\right) \cdot \left(t \cdot b - \color{blue}{y3 \cdot y1}\right) \]

   6. Simplified 53.9%

      \[\leadsto \color{blue}{\left(y4 \cdot j\right) \cdot \left(t \cdot b - y3 \cdot y1\right)} \]

   if -4.5000000000000001e-25 < y5 < -8.00000000000000014e-87

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 65.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 37.1%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.1%

         \[\leadsto \color{blue}{\left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right) \cdot y} \]

      2. associate-*l* 37.1%

         \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   6. Simplified 37.1%

      \[\leadsto \color{blue}{y5 \cdot \left(\left(i \cdot k - a \cdot y3\right) \cdot y\right)} \]

   if -8.00000000000000014e-87 < y5 < -1.1e-175

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -1.1e-175 < y5 < 4e-263

   1. Initial program 35.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 40.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 43.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.6%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 43.6%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 43.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 4e-263 < y5 < 2.0999999999999999e-108

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 2.0999999999999999e-108 < y5 < 4.8000000000000004e-43

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 52.2%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 4.8e17 < y5 < 5.4e29

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 100.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 67.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 100.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 100.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if 5.4e29 < y5

   1. Initial program 25.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 34.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 58.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 58.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 53.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -2.7 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.1 \cdot 10^{+43}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -4.5 \cdot 10^{-25}:\\ \;\;\;\;\left(j \cdot y4\right) \cdot \left(t \cdot b - y1 \cdot y3\right)\\ \mathbf{elif}\;y5 \leq -8 \cdot 10^{-87}:\\ \;\;\;\;y5 \cdot \left(y \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -1.1 \cdot 10^{-175}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 4 \cdot 10^{-263}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2.1 \cdot 10^{-108}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 4.8 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 4.8 \cdot 10^{+17}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 5.4 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 17: 40.2% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot y5 - y1 \cdot y4\\ t_2 := y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot t_1 + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{if}\;j \leq -7.5 \cdot 10^{-22}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot t_1 + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 6.4 \cdot 10^{-249}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 7.5 \cdot 10^{-212}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 6.6 \cdot 10^{-178}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 3.4 \cdot 10^{-86}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq 6 \cdot 10^{+127}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y0 y5) (* y1 y4)))
        (t_2
         (*
          y3
          (+
           (* y (- (* c y4) (* a y5)))
           (+ (* j t_1) (* z (- (* a y1) (* c y0))))))))
   (if (<= j -7.5e-22)
     (*
      j
      (+
       (+ (* y3 t_1) (* t (- (* b y4) (* i y5))))
       (* x (- (* i y1) (* b y0)))))
     (if (<= j 6.4e-249)
       (*
        c
        (+
         (+ (* i (- (* z t) (* x y))) (* y0 (- (* x y2) (* z y3))))
         (* y4 (- (* y y3) (* t y2)))))
       (if (<= j 7.5e-212)
         t_2
         (if (<= j 6.6e-178)
           (* k (* y0 (- (* z b) (* y2 y5))))
           (if (<= j 3.4e-86)
             (*
              y5
              (+
               (* a (- (* t y2) (* y y3)))
               (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2))))))
             (if (<= j 6e+127) t_2 (* (* i j) (- (* x y1) (* t y5)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y0 * y5) - (y1 * y4);
	double t_2 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_1) + (z * ((a * y1) - (c * y0)))));
	double tmp;
	if (j <= -7.5e-22) {
		tmp = j * (((y3 * t_1) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))));
	} else if (j <= 6.4e-249) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 7.5e-212) {
		tmp = t_2;
	} else if (j <= 6.6e-178) {
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	} else if (j <= 3.4e-86) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (j <= 6e+127) {
		tmp = t_2;
	} else {
		tmp = (i * j) * ((x * y1) - (t * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (y0 * y5) - (y1 * y4)
    t_2 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_1) + (z * ((a * y1) - (c * y0)))))
    if (j <= (-7.5d-22)) then
        tmp = j * (((y3 * t_1) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))))
    else if (j <= 6.4d-249) then
        tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
    else if (j <= 7.5d-212) then
        tmp = t_2
    else if (j <= 6.6d-178) then
        tmp = k * (y0 * ((z * b) - (y2 * y5)))
    else if (j <= 3.4d-86) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
    else if (j <= 6d+127) then
        tmp = t_2
    else
        tmp = (i * j) * ((x * y1) - (t * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y0 * y5) - (y1 * y4);
	double t_2 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_1) + (z * ((a * y1) - (c * y0)))));
	double tmp;
	if (j <= -7.5e-22) {
		tmp = j * (((y3 * t_1) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))));
	} else if (j <= 6.4e-249) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 7.5e-212) {
		tmp = t_2;
	} else if (j <= 6.6e-178) {
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	} else if (j <= 3.4e-86) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (j <= 6e+127) {
		tmp = t_2;
	} else {
		tmp = (i * j) * ((x * y1) - (t * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y0 * y5) - (y1 * y4)
	t_2 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_1) + (z * ((a * y1) - (c * y0)))))
	tmp = 0
	if j <= -7.5e-22:
		tmp = j * (((y3 * t_1) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))))
	elif j <= 6.4e-249:
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))))
	elif j <= 7.5e-212:
		tmp = t_2
	elif j <= 6.6e-178:
		tmp = k * (y0 * ((z * b) - (y2 * y5)))
	elif j <= 3.4e-86:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
	elif j <= 6e+127:
		tmp = t_2
	else:
		tmp = (i * j) * ((x * y1) - (t * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_2 = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * t_1) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))))
	tmp = 0.0
	if (j <= -7.5e-22)
		tmp = Float64(j * Float64(Float64(Float64(y3 * t_1) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (j <= 6.4e-249)
		tmp = Float64(c * Float64(Float64(Float64(i * Float64(Float64(z * t) - Float64(x * y))) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= 7.5e-212)
		tmp = t_2;
	elseif (j <= 6.6e-178)
		tmp = Float64(k * Float64(y0 * Float64(Float64(z * b) - Float64(y2 * y5))));
	elseif (j <= 3.4e-86)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (j <= 6e+127)
		tmp = t_2;
	else
		tmp = Float64(Float64(i * j) * Float64(Float64(x * y1) - Float64(t * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y0 * y5) - (y1 * y4);
	t_2 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * t_1) + (z * ((a * y1) - (c * y0)))));
	tmp = 0.0;
	if (j <= -7.5e-22)
		tmp = j * (((y3 * t_1) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))));
	elseif (j <= 6.4e-249)
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (j <= 7.5e-212)
		tmp = t_2;
	elseif (j <= 6.6e-178)
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	elseif (j <= 3.4e-86)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	elseif (j <= 6e+127)
		tmp = t_2;
	else
		tmp = (i * j) * ((x * y1) - (t * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * t$95$1), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -7.5e-22], N[(j * N[(N[(N[(y3 * t$95$1), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.4e-249], N[(c * N[(N[(N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.5e-212], t$95$2, If[LessEqual[j, 6.6e-178], N[(k * N[(y0 * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.4e-86], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6e+127], t$95$2, N[(N[(i * j), $MachinePrecision] * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -7.49999999999999978e-22

   1. Initial program 25.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 51.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -7.49999999999999978e-22 < j < 6.4000000000000003e-249

   1. Initial program 41.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 47.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 6.4000000000000003e-249 < j < 7.50000000000000012e-212 or 3.4e-86 < j < 6.0000000000000005e127

   1. Initial program 36.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 67.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if 7.50000000000000012e-212 < j < 6.6000000000000003e-178

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 66.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 68.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 68.4%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 68.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 68.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 68.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   if 6.6000000000000003e-178 < j < 3.4e-86

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 71.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if 6.0000000000000005e127 < j

   1. Initial program 31.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 55.0%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 52.3%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(t \cdot y5\right) - -1 \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-lft-out-- 52.3%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(-1 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)} \]

      3. *-commutative 52.3%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot t} - x \cdot y1\right)\right) \]

      4. *-commutative 52.3%

         \[\leadsto \left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - \color{blue}{y1 \cdot x}\right)\right) \]

   6. Simplified 52.3%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(-1 \cdot \left(y5 \cdot t - y1 \cdot x\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 55.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -7.5 \cdot 10^{-22}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 6.4 \cdot 10^{-249}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 7.5 \cdot 10^{-212}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;j \leq 6.6 \cdot 10^{-178}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 3.4 \cdot 10^{-86}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;j \leq 6 \cdot 10^{+127}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(x \cdot y1 - t \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 18: 32.3% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -3.5 \cdot 10^{+124}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.05 \cdot 10^{-48}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -9.2 \cdot 10^{-104}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;z \leq -5.9 \cdot 10^{-139}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{-278}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{-52}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+129}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 2.9 \cdot 10^{+192}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{+219}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -3.5e+124)
   (* k (* z (- (* b y0) (* i y1))))
   (if (<= z -1.05e-48)
     (* k (* y0 (- (* z b) (* y2 y5))))
     (if (<= z -9.2e-104)
       (* k (* y4 (- (* y1 y2) (* y b))))
       (if (<= z -5.9e-139)
         (* k (* y5 (- (* y i) (* y0 y2))))
         (if (<= z 1.3e-278)
           (* y3 (* y4 (- (* y c) (* j y1))))
           (if (<= z 3.1e-52)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= z 5e+129)
               (* x (* y (- (* a b) (* c i))))
               (if (<= z 2.9e+192)
                 (* c (* y3 (- (* y y4) (* z y0))))
                 (if (<= z 7e+219)
                   (* i (* k (- (* y y5) (* z y1))))
                   (* (* z y3) (- (* a y1) (* c y0)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.5e+124) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (z <= -1.05e-48) {
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	} else if (z <= -9.2e-104) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (z <= -5.9e-139) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (z <= 1.3e-278) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 3.1e-52) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 5e+129) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 2.9e+192) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (z <= 7e+219) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-3.5d+124)) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (z <= (-1.05d-48)) then
        tmp = k * (y0 * ((z * b) - (y2 * y5)))
    else if (z <= (-9.2d-104)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (z <= (-5.9d-139)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (z <= 1.3d-278) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (z <= 3.1d-52) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (z <= 5d+129) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (z <= 2.9d+192) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (z <= 7d+219) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else
        tmp = (z * y3) * ((a * y1) - (c * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.5e+124) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (z <= -1.05e-48) {
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	} else if (z <= -9.2e-104) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (z <= -5.9e-139) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (z <= 1.3e-278) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 3.1e-52) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 5e+129) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 2.9e+192) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (z <= 7e+219) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -3.5e+124:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif z <= -1.05e-48:
		tmp = k * (y0 * ((z * b) - (y2 * y5)))
	elif z <= -9.2e-104:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif z <= -5.9e-139:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif z <= 1.3e-278:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif z <= 3.1e-52:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif z <= 5e+129:
		tmp = x * (y * ((a * b) - (c * i)))
	elif z <= 2.9e+192:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif z <= 7e+219:
		tmp = i * (k * ((y * y5) - (z * y1)))
	else:
		tmp = (z * y3) * ((a * y1) - (c * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -3.5e+124)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (z <= -1.05e-48)
		tmp = Float64(k * Float64(y0 * Float64(Float64(z * b) - Float64(y2 * y5))));
	elseif (z <= -9.2e-104)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (z <= -5.9e-139)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (z <= 1.3e-278)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (z <= 3.1e-52)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 5e+129)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (z <= 2.9e+192)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (z <= 7e+219)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	else
		tmp = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -3.5e+124)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (z <= -1.05e-48)
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	elseif (z <= -9.2e-104)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (z <= -5.9e-139)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (z <= 1.3e-278)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (z <= 3.1e-52)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (z <= 5e+129)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (z <= 2.9e+192)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (z <= 7e+219)
		tmp = i * (k * ((y * y5) - (z * y1)));
	else
		tmp = (z * y3) * ((a * y1) - (c * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -3.5e+124], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.05e-48], N[(k * N[(y0 * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -9.2e-104], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -5.9e-139], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.3e-278], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.1e-52], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5e+129], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.9e+192], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7e+219], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if z < -3.5000000000000001e124

   1. Initial program 17.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 43.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 62.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 62.0%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 62.0%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 62.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if -3.5000000000000001e124 < z < -1.04999999999999994e-48

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 35.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 44.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 44.9%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 44.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 44.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 44.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   if -1.04999999999999994e-48 < z < -9.1999999999999998e-104

   1. Initial program 44.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 67.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 67.3%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 67.3%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -9.1999999999999998e-104 < z < -5.8999999999999998e-139

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 83.6%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 83.6%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -5.8999999999999998e-139 < z < 1.2999999999999999e-278

   1. Initial program 38.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 41.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 48.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 48.9%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 48.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if 1.2999999999999999e-278 < z < 3.0999999999999999e-52

   1. Initial program 36.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 43.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 3.0999999999999999e-52 < z < 5.0000000000000003e129

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 53.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 41.6%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 5.0000000000000003e129 < z < 2.9000000000000001e192

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 75.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in c around inf 83.3%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot \left(y0 \cdot z - y \cdot y4\right)\right)\right)} \]

   if 2.9000000000000001e192 < z < 7.0000000000000002e219

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 13.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 50.8%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 7.0000000000000002e219 < z

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 40.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in z around inf 67.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 60.7%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   6. Simplified 60.7%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 51.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.5 \cdot 10^{+124}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.05 \cdot 10^{-48}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -9.2 \cdot 10^{-104}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;z \leq -5.9 \cdot 10^{-139}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{-278}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{-52}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+129}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 2.9 \cdot 10^{+192}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{+219}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 19: 32.1% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y0 - i \cdot y1\\ \mathbf{if}\;z \leq -2.25 \cdot 10^{+123}:\\ \;\;\;\;k \cdot \left(z \cdot t_1\right)\\ \mathbf{elif}\;z \leq -7.2 \cdot 10^{-49}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -7.4 \cdot 10^{-107}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;z \leq -2.65 \cdot 10^{-140}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{-279}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.45 \cdot 10^{-51}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{+134}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 4.1 \cdot 10^{+194}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 4.4 \cdot 10^{+241}:\\ \;\;\;\;t_1 \cdot \left(z \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y0) (* i y1))))
   (if (<= z -2.25e+123)
     (* k (* z t_1))
     (if (<= z -7.2e-49)
       (* k (* y0 (- (* z b) (* y2 y5))))
       (if (<= z -7.4e-107)
         (* k (* y4 (- (* y1 y2) (* y b))))
         (if (<= z -2.65e-140)
           (* k (* y5 (- (* y i) (* y0 y2))))
           (if (<= z 6.5e-279)
             (* y3 (* y4 (- (* y c) (* j y1))))
             (if (<= z 1.45e-51)
               (* x (* y2 (- (* c y0) (* a y1))))
               (if (<= z 6.5e+134)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= z 4.1e+194)
                   (* c (* y3 (- (* y y4) (* z y0))))
                   (if (<= z 4.4e+241)
                     (* t_1 (* z k))
                     (* y0 (* y3 (- (* j y5) (* z c)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y0) - (i * y1);
	double tmp;
	if (z <= -2.25e+123) {
		tmp = k * (z * t_1);
	} else if (z <= -7.2e-49) {
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	} else if (z <= -7.4e-107) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (z <= -2.65e-140) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (z <= 6.5e-279) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 1.45e-51) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 6.5e+134) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 4.1e+194) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (z <= 4.4e+241) {
		tmp = t_1 * (z * k);
	} else {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (b * y0) - (i * y1)
    if (z <= (-2.25d+123)) then
        tmp = k * (z * t_1)
    else if (z <= (-7.2d-49)) then
        tmp = k * (y0 * ((z * b) - (y2 * y5)))
    else if (z <= (-7.4d-107)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (z <= (-2.65d-140)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (z <= 6.5d-279) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (z <= 1.45d-51) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (z <= 6.5d+134) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (z <= 4.1d+194) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (z <= 4.4d+241) then
        tmp = t_1 * (z * k)
    else
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y0) - (i * y1);
	double tmp;
	if (z <= -2.25e+123) {
		tmp = k * (z * t_1);
	} else if (z <= -7.2e-49) {
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	} else if (z <= -7.4e-107) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (z <= -2.65e-140) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (z <= 6.5e-279) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 1.45e-51) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 6.5e+134) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 4.1e+194) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (z <= 4.4e+241) {
		tmp = t_1 * (z * k);
	} else {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (b * y0) - (i * y1)
	tmp = 0
	if z <= -2.25e+123:
		tmp = k * (z * t_1)
	elif z <= -7.2e-49:
		tmp = k * (y0 * ((z * b) - (y2 * y5)))
	elif z <= -7.4e-107:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif z <= -2.65e-140:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif z <= 6.5e-279:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif z <= 1.45e-51:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif z <= 6.5e+134:
		tmp = x * (y * ((a * b) - (c * i)))
	elif z <= 4.1e+194:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif z <= 4.4e+241:
		tmp = t_1 * (z * k)
	else:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(b * y0) - Float64(i * y1))
	tmp = 0.0
	if (z <= -2.25e+123)
		tmp = Float64(k * Float64(z * t_1));
	elseif (z <= -7.2e-49)
		tmp = Float64(k * Float64(y0 * Float64(Float64(z * b) - Float64(y2 * y5))));
	elseif (z <= -7.4e-107)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (z <= -2.65e-140)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (z <= 6.5e-279)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (z <= 1.45e-51)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 6.5e+134)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (z <= 4.1e+194)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (z <= 4.4e+241)
		tmp = Float64(t_1 * Float64(z * k));
	else
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (b * y0) - (i * y1);
	tmp = 0.0;
	if (z <= -2.25e+123)
		tmp = k * (z * t_1);
	elseif (z <= -7.2e-49)
		tmp = k * (y0 * ((z * b) - (y2 * y5)));
	elseif (z <= -7.4e-107)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (z <= -2.65e-140)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (z <= 6.5e-279)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (z <= 1.45e-51)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (z <= 6.5e+134)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (z <= 4.1e+194)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (z <= 4.4e+241)
		tmp = t_1 * (z * k);
	else
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.25e+123], N[(k * N[(z * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.2e-49], N[(k * N[(y0 * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.4e-107], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.65e-140], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6.5e-279], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.45e-51], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6.5e+134], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.1e+194], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.4e+241], N[(t$95$1 * N[(z * k), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if z < -2.24999999999999991e123

   1. Initial program 17.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 43.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 62.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 62.0%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 62.0%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 62.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if -2.24999999999999991e123 < z < -7.19999999999999939e-49

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 35.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 44.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 44.9%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 44.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 44.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 44.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   if -7.19999999999999939e-49 < z < -7.4000000000000006e-107

   1. Initial program 44.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 67.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 67.3%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 67.3%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 67.3%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -7.4000000000000006e-107 < z < -2.64999999999999992e-140

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 83.6%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 83.6%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 83.6%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -2.64999999999999992e-140 < z < 6.4999999999999997e-279

   1. Initial program 38.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 41.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 48.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 48.9%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 48.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if 6.4999999999999997e-279 < z < 1.44999999999999986e-51

   1. Initial program 36.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 43.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.44999999999999986e-51 < z < 6.5e134

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 53.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 41.6%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 6.5e134 < z < 4.1e194

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 75.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in c around inf 83.3%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot \left(y0 \cdot z - y \cdot y4\right)\right)\right)} \]

   if 4.1e194 < z < 4.4e241

   1. Initial program 46.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 24.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 39.6%

         \[\leadsto \color{blue}{-k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

      2. associate-*r* 46.9%

         \[\leadsto -\color{blue}{\left(k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      3. distribute-lft-neg-in 46.9%

         \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      4. *-commutative 46.9%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      5. *-commutative 46.9%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   6. Simplified 46.9%

      \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   if 4.4e241 < z

   1. Initial program 20.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 40.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y0 around -inf 80.1%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) + j \cdot y5\right)\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 80.1%

         \[\leadsto -1 \cdot \color{blue}{\left(-y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) + j \cdot y5\right)\right)\right)} \]

      2. *-commutative 80.1%

         \[\leadsto -1 \cdot \left(-\color{blue}{\left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) + j \cdot y5\right)\right) \cdot y0}\right) \]

      3. distribute-rgt-neg-in 80.1%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) + j \cdot y5\right)\right) \cdot \left(-y0\right)\right)} \]

      4. +-commutative 80.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot \color{blue}{\left(j \cdot y5 + -1 \cdot \left(c \cdot z\right)\right)}\right) \cdot \left(-y0\right)\right) \]

      5. mul-1-neg 80.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot \left(j \cdot y5 + \color{blue}{\left(-c \cdot z\right)}\right)\right) \cdot \left(-y0\right)\right) \]

      6. unsub-neg 80.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot \color{blue}{\left(j \cdot y5 - c \cdot z\right)}\right) \cdot \left(-y0\right)\right) \]

      7. *-commutative 80.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot \left(\color{blue}{y5 \cdot j} - c \cdot z\right)\right) \cdot \left(-y0\right)\right) \]

      8. *-commutative 80.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot \left(y5 \cdot j - \color{blue}{z \cdot c}\right)\right) \cdot \left(-y0\right)\right) \]

   6. Simplified 80.1%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot \left(y5 \cdot j - z \cdot c\right)\right) \cdot \left(-y0\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 52.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.25 \cdot 10^{+123}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -7.2 \cdot 10^{-49}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -7.4 \cdot 10^{-107}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;z \leq -2.65 \cdot 10^{-140}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{-279}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.45 \cdot 10^{-51}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{+134}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 4.1 \cdot 10^{+194}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 4.4 \cdot 10^{+241}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 20: 30.5% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot y5 - c \cdot y4\\ \mathbf{if}\;c \leq -7.6 \cdot 10^{+134}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq -2.8 \cdot 10^{-59}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -1.18 \cdot 10^{-247}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq -2.15 \cdot 10^{-287}:\\ \;\;\;\;y2 \cdot \left(\left(x \cdot \left(c \cdot y0 - a \cdot y1\right) + k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot t_1\right)\\ \mathbf{elif}\;c \leq 1.05 \cdot 10^{-196}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 6.8 \cdot 10^{-129}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq 3.1 \cdot 10^{+75}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 6.4 \cdot 10^{+123}:\\ \;\;\;\;t \cdot \left(y2 \cdot t_1\right)\\ \mathbf{elif}\;c \leq 2.75 \cdot 10^{+196}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(c \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a y5) (* c y4))))
   (if (<= c -7.6e+134)
     (* y0 (* y2 (- (* x c) (* k y5))))
     (if (<= c -2.8e-59)
       (* y3 (* y4 (- (* y c) (* j y1))))
       (if (<= c -1.18e-247)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= c -2.15e-287)
           (*
            y2
            (+
             (+ (* x (- (* c y0) (* a y1))) (* k (- (* y1 y4) (* y0 y5))))
             (* t t_1)))
           (if (<= c 1.05e-196)
             (* y5 (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2)))))
             (if (<= c 6.8e-129)
               (* j (* y3 (- (* y0 y5) (* y1 y4))))
               (if (<= c 3.1e+75)
                 (* x (* y (- (* a b) (* c i))))
                 (if (<= c 6.4e+123)
                   (* t (* y2 t_1))
                   (if (<= c 2.75e+196)
                     (* i (* k (- (* y y5) (* z y1))))
                     (* y3 (* c (- (* y y4) (* z y0)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * y5) - (c * y4);
	double tmp;
	if (c <= -7.6e+134) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (c <= -2.8e-59) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (c <= -1.18e-247) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= -2.15e-287) {
		tmp = y2 * (((x * ((c * y0) - (a * y1))) + (k * ((y1 * y4) - (y0 * y5)))) + (t * t_1));
	} else if (c <= 1.05e-196) {
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	} else if (c <= 6.8e-129) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (c <= 3.1e+75) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (c <= 6.4e+123) {
		tmp = t * (y2 * t_1);
	} else if (c <= 2.75e+196) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = y3 * (c * ((y * y4) - (z * y0)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (a * y5) - (c * y4)
    if (c <= (-7.6d+134)) then
        tmp = y0 * (y2 * ((x * c) - (k * y5)))
    else if (c <= (-2.8d-59)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (c <= (-1.18d-247)) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (c <= (-2.15d-287)) then
        tmp = y2 * (((x * ((c * y0) - (a * y1))) + (k * ((y1 * y4) - (y0 * y5)))) + (t * t_1))
    else if (c <= 1.05d-196) then
        tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))))
    else if (c <= 6.8d-129) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (c <= 3.1d+75) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (c <= 6.4d+123) then
        tmp = t * (y2 * t_1)
    else if (c <= 2.75d+196) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else
        tmp = y3 * (c * ((y * y4) - (z * y0)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * y5) - (c * y4);
	double tmp;
	if (c <= -7.6e+134) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (c <= -2.8e-59) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (c <= -1.18e-247) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= -2.15e-287) {
		tmp = y2 * (((x * ((c * y0) - (a * y1))) + (k * ((y1 * y4) - (y0 * y5)))) + (t * t_1));
	} else if (c <= 1.05e-196) {
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	} else if (c <= 6.8e-129) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (c <= 3.1e+75) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (c <= 6.4e+123) {
		tmp = t * (y2 * t_1);
	} else if (c <= 2.75e+196) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = y3 * (c * ((y * y4) - (z * y0)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (a * y5) - (c * y4)
	tmp = 0
	if c <= -7.6e+134:
		tmp = y0 * (y2 * ((x * c) - (k * y5)))
	elif c <= -2.8e-59:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif c <= -1.18e-247:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif c <= -2.15e-287:
		tmp = y2 * (((x * ((c * y0) - (a * y1))) + (k * ((y1 * y4) - (y0 * y5)))) + (t * t_1))
	elif c <= 1.05e-196:
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))))
	elif c <= 6.8e-129:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif c <= 3.1e+75:
		tmp = x * (y * ((a * b) - (c * i)))
	elif c <= 6.4e+123:
		tmp = t * (y2 * t_1)
	elif c <= 2.75e+196:
		tmp = i * (k * ((y * y5) - (z * y1)))
	else:
		tmp = y3 * (c * ((y * y4) - (z * y0)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(a * y5) - Float64(c * y4))
	tmp = 0.0
	if (c <= -7.6e+134)
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (c <= -2.8e-59)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (c <= -1.18e-247)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (c <= -2.15e-287)
		tmp = Float64(y2 * Float64(Float64(Float64(x * Float64(Float64(c * y0) - Float64(a * y1))) + Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) + Float64(t * t_1)));
	elseif (c <= 1.05e-196)
		tmp = Float64(y5 * Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (c <= 6.8e-129)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (c <= 3.1e+75)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (c <= 6.4e+123)
		tmp = Float64(t * Float64(y2 * t_1));
	elseif (c <= 2.75e+196)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	else
		tmp = Float64(y3 * Float64(c * Float64(Float64(y * y4) - Float64(z * y0))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (a * y5) - (c * y4);
	tmp = 0.0;
	if (c <= -7.6e+134)
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	elseif (c <= -2.8e-59)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (c <= -1.18e-247)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (c <= -2.15e-287)
		tmp = y2 * (((x * ((c * y0) - (a * y1))) + (k * ((y1 * y4) - (y0 * y5)))) + (t * t_1));
	elseif (c <= 1.05e-196)
		tmp = y5 * ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2))));
	elseif (c <= 6.8e-129)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (c <= 3.1e+75)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (c <= 6.4e+123)
		tmp = t * (y2 * t_1);
	elseif (c <= 2.75e+196)
		tmp = i * (k * ((y * y5) - (z * y1)));
	else
		tmp = y3 * (c * ((y * y4) - (z * y0)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -7.6e+134], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2.8e-59], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.18e-247], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2.15e-287], N[(y2 * N[(N[(N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.05e-196], N[(y5 * N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 6.8e-129], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.1e+75], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 6.4e+123], N[(t * N[(y2 * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.75e+196], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y3 * N[(c * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if c < -7.59999999999999997e134

   1. Initial program 24.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 49.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 56.5%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 56.5%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 56.5%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 56.5%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 56.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 56.5%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 56.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 56.5%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 56.5%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   if -7.59999999999999997e134 < c < -2.79999999999999981e-59

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 37.4%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 52.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 52.0%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 52.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if -2.79999999999999981e-59 < c < -1.17999999999999997e-247

   1. Initial program 36.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 44.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 51.4%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 51.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 51.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 51.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 51.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 51.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 51.4%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if -1.17999999999999997e-247 < c < -2.14999999999999995e-287

   1. Initial program 39.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 61.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -2.14999999999999995e-287 < c < 1.04999999999999994e-196

   1. Initial program 45.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 72.4%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   4. Taylor expanded in a around 0 67.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y5 \cdot \left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} \]

   if 1.04999999999999994e-196 < c < 6.80000000000000026e-129

   1. Initial program 44.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y3 around inf 56.1%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 56.1%

         \[\leadsto \color{blue}{-j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 56.1%

         \[\leadsto \color{blue}{j \cdot \left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

      3. *-commutative 56.1%

         \[\leadsto j \cdot \left(-\color{blue}{\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot y3}\right) \]

      4. distribute-rgt-neg-in 56.1%

         \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot \left(-y3\right)\right)} \]

   6. Simplified 56.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(y1 \cdot y4 - y0 \cdot y5\right) \cdot \left(-y3\right)\right)} \]

   if 6.80000000000000026e-129 < c < 3.1000000000000001e75

   1. Initial program 44.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 57.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 38.2%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 3.1000000000000001e75 < c < 6.40000000000000009e123

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 75.2%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if 6.40000000000000009e123 < c < 2.74999999999999987e196

   1. Initial program 21.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 60.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 54.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 2.74999999999999987e196 < c

   1. Initial program 16.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 50.5%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in c around inf 68.5%

      \[\leadsto -1 \cdot \left(y3 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot z - y \cdot y4\right)\right)}\right) \]
   5. Step-by-step derivation

      1. *-commutative 68.5%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(c \cdot \left(\color{blue}{z \cdot y0} - y \cdot y4\right)\right)\right) \]

   6. Simplified 68.5%

      \[\leadsto -1 \cdot \left(y3 \cdot \color{blue}{\left(c \cdot \left(z \cdot y0 - y \cdot y4\right)\right)}\right) \]
3. Recombined 10 regimes into one program.

4. Final simplification 55.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -7.6 \cdot 10^{+134}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq -2.8 \cdot 10^{-59}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -1.18 \cdot 10^{-247}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq -2.15 \cdot 10^{-287}:\\ \;\;\;\;y2 \cdot \left(\left(x \cdot \left(c \cdot y0 - a \cdot y1\right) + k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq 1.05 \cdot 10^{-196}:\\ \;\;\;\;y5 \cdot \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 6.8 \cdot 10^{-129}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq 3.1 \cdot 10^{+75}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 6.4 \cdot 10^{+123}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq 2.75 \cdot 10^{+196}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(c \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 21: 31.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{if}\;y5 \leq -4.5 \cdot 10^{+106}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -1.6 \cdot 10^{-130}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 5.4 \cdot 10^{-269}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2.4 \cdot 10^{-107}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.6 \cdot 10^{-61}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 10^{-17}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \mathbf{elif}\;y5 \leq 4.6 \cdot 10^{+52}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 1.55 \cdot 10^{+65}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y5 (- (* t y2) (* y y3))))))
   (if (<= y5 -4.5e+106)
     t_1
     (if (<= y5 -1.6e-130)
       (* k (* y4 (- (* y1 y2) (* y b))))
       (if (<= y5 5.4e-269)
         (* k (* z (- (* b y0) (* i y1))))
         (if (<= y5 2.4e-107)
           (* x (* y (- (* a b) (* c i))))
           (if (<= y5 5.6e-61)
             (* k (* y1 (- (* y2 y4) (* z i))))
             (if (<= y5 1e-17)
               (* y0 (* y2 (* x c)))
               (if (<= y5 4.6e+52)
                 t_1
                 (if (<= y5 1.55e+65)
                   (* k (* y0 (* z b)))
                   (* j (* y5 (- (* y0 y3) (* t i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y5 * ((t * y2) - (y * y3)));
	double tmp;
	if (y5 <= -4.5e+106) {
		tmp = t_1;
	} else if (y5 <= -1.6e-130) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 5.4e-269) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 2.4e-107) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 5.6e-61) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y5 <= 1e-17) {
		tmp = y0 * (y2 * (x * c));
	} else if (y5 <= 4.6e+52) {
		tmp = t_1;
	} else if (y5 <= 1.55e+65) {
		tmp = k * (y0 * (z * b));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (y5 * ((t * y2) - (y * y3)))
    if (y5 <= (-4.5d+106)) then
        tmp = t_1
    else if (y5 <= (-1.6d-130)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (y5 <= 5.4d-269) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y5 <= 2.4d-107) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 5.6d-61) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (y5 <= 1d-17) then
        tmp = y0 * (y2 * (x * c))
    else if (y5 <= 4.6d+52) then
        tmp = t_1
    else if (y5 <= 1.55d+65) then
        tmp = k * (y0 * (z * b))
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y5 * ((t * y2) - (y * y3)));
	double tmp;
	if (y5 <= -4.5e+106) {
		tmp = t_1;
	} else if (y5 <= -1.6e-130) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 5.4e-269) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 2.4e-107) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 5.6e-61) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y5 <= 1e-17) {
		tmp = y0 * (y2 * (x * c));
	} else if (y5 <= 4.6e+52) {
		tmp = t_1;
	} else if (y5 <= 1.55e+65) {
		tmp = k * (y0 * (z * b));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (y5 * ((t * y2) - (y * y3)))
	tmp = 0
	if y5 <= -4.5e+106:
		tmp = t_1
	elif y5 <= -1.6e-130:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif y5 <= 5.4e-269:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y5 <= 2.4e-107:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 5.6e-61:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif y5 <= 1e-17:
		tmp = y0 * (y2 * (x * c))
	elif y5 <= 4.6e+52:
		tmp = t_1
	elif y5 <= 1.55e+65:
		tmp = k * (y0 * (z * b))
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))))
	tmp = 0.0
	if (y5 <= -4.5e+106)
		tmp = t_1;
	elseif (y5 <= -1.6e-130)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (y5 <= 5.4e-269)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y5 <= 2.4e-107)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 5.6e-61)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (y5 <= 1e-17)
		tmp = Float64(y0 * Float64(y2 * Float64(x * c)));
	elseif (y5 <= 4.6e+52)
		tmp = t_1;
	elseif (y5 <= 1.55e+65)
		tmp = Float64(k * Float64(y0 * Float64(z * b)));
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (y5 * ((t * y2) - (y * y3)));
	tmp = 0.0;
	if (y5 <= -4.5e+106)
		tmp = t_1;
	elseif (y5 <= -1.6e-130)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (y5 <= 5.4e-269)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y5 <= 2.4e-107)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 5.6e-61)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (y5 <= 1e-17)
		tmp = y0 * (y2 * (x * c));
	elseif (y5 <= 4.6e+52)
		tmp = t_1;
	elseif (y5 <= 1.55e+65)
		tmp = k * (y0 * (z * b));
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -4.5e+106], t$95$1, If[LessEqual[y5, -1.6e-130], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.4e-269], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.4e-107], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.6e-61], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1e-17], N[(y0 * N[(y2 * N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.6e+52], t$95$1, If[LessEqual[y5, 1.55e+65], N[(k * N[(y0 * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y5 < -4.4999999999999997e106 or 1.00000000000000007e-17 < y5 < 4.6e52

   1. Initial program 26.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 44.2%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 44.2%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 44.2%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 44.2%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 57.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -4.4999999999999997e106 < y5 < -1.6e-130

   1. Initial program 39.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 33.1%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 33.1%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -1.6e-130 < y5 < 5.40000000000000031e-269

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 5.40000000000000031e-269 < y5 < 2.39999999999999994e-107

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 2.39999999999999994e-107 < y5 < 5.6000000000000002e-61

   1. Initial program 33.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 43.8%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.8%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 43.8%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 43.8%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]

   if 5.6000000000000002e-61 < y5 < 1.00000000000000007e-17

   1. Initial program 27.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 19.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 65.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 65.6%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 65.6%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 65.6%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 65.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 65.6%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 65.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 65.6%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 65.6%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   7. Taylor expanded in y5 around 0 55.6%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]
   8. Step-by-step derivation

      1. mul-1-neg 55.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(-c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      2. distribute-lft-neg-out 55.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(\left(-c\right) \cdot x\right)}\right) \cdot \left(-y0\right) \]

      3. *-commutative 55.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   9. Simplified 55.6%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   if 4.6e52 < y5 < 1.54999999999999995e65

   1. Initial program 41.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 79.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 80.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 80.4%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 80.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 80.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 80.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 42.5%

      \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(-1 \cdot \left(b \cdot z\right)\right)}\right)\right) \]
   8. Step-by-step derivation

      1. mul-1-neg 42.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(-b \cdot z\right)}\right)\right) \]

      2. *-commutative 42.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(-\color{blue}{z \cdot b}\right)\right)\right) \]

      3. distribute-rgt-neg-in 42.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(z \cdot \left(-b\right)\right)}\right)\right) \]

   9. Simplified 42.5%

      \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(z \cdot \left(-b\right)\right)}\right)\right) \]

   if 1.54999999999999995e65 < y5

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 60.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 60.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 48.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -4.5 \cdot 10^{+106}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -1.6 \cdot 10^{-130}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 5.4 \cdot 10^{-269}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2.4 \cdot 10^{-107}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.6 \cdot 10^{-61}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 10^{-17}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \mathbf{elif}\;y5 \leq 4.6 \cdot 10^{+52}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 1.55 \cdot 10^{+65}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 22: 31.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{if}\;y5 \leq -1.5 \cdot 10^{+107}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -5.3 \cdot 10^{-129}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 5.6 \cdot 10^{-267}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 3.1 \cdot 10^{-104}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 3.8 \cdot 10^{-67}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2.1 \cdot 10^{-16}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 1.85 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 1.55 \cdot 10^{+65}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y5 (- (* t y2) (* y y3))))))
   (if (<= y5 -1.5e+107)
     t_1
     (if (<= y5 -5.3e-129)
       (* k (* y4 (- (* y1 y2) (* y b))))
       (if (<= y5 5.6e-267)
         (* k (* z (- (* b y0) (* i y1))))
         (if (<= y5 3.1e-104)
           (* x (* y (- (* a b) (* c i))))
           (if (<= y5 3.8e-67)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y5 2.1e-16)
               (* k (* y1 (- (* y2 y4) (* z i))))
               (if (<= y5 1.85e+43)
                 t_1
                 (if (<= y5 1.55e+65)
                   (* k (* y0 (* z b)))
                   (* j (* y5 (- (* y0 y3) (* t i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y5 * ((t * y2) - (y * y3)));
	double tmp;
	if (y5 <= -1.5e+107) {
		tmp = t_1;
	} else if (y5 <= -5.3e-129) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 5.6e-267) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 3.1e-104) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 3.8e-67) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 2.1e-16) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y5 <= 1.85e+43) {
		tmp = t_1;
	} else if (y5 <= 1.55e+65) {
		tmp = k * (y0 * (z * b));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (y5 * ((t * y2) - (y * y3)))
    if (y5 <= (-1.5d+107)) then
        tmp = t_1
    else if (y5 <= (-5.3d-129)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (y5 <= 5.6d-267) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y5 <= 3.1d-104) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 3.8d-67) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 2.1d-16) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (y5 <= 1.85d+43) then
        tmp = t_1
    else if (y5 <= 1.55d+65) then
        tmp = k * (y0 * (z * b))
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y5 * ((t * y2) - (y * y3)));
	double tmp;
	if (y5 <= -1.5e+107) {
		tmp = t_1;
	} else if (y5 <= -5.3e-129) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 5.6e-267) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 3.1e-104) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 3.8e-67) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 2.1e-16) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y5 <= 1.85e+43) {
		tmp = t_1;
	} else if (y5 <= 1.55e+65) {
		tmp = k * (y0 * (z * b));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (y5 * ((t * y2) - (y * y3)))
	tmp = 0
	if y5 <= -1.5e+107:
		tmp = t_1
	elif y5 <= -5.3e-129:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif y5 <= 5.6e-267:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y5 <= 3.1e-104:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 3.8e-67:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 2.1e-16:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif y5 <= 1.85e+43:
		tmp = t_1
	elif y5 <= 1.55e+65:
		tmp = k * (y0 * (z * b))
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))))
	tmp = 0.0
	if (y5 <= -1.5e+107)
		tmp = t_1;
	elseif (y5 <= -5.3e-129)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (y5 <= 5.6e-267)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y5 <= 3.1e-104)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 3.8e-67)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 2.1e-16)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (y5 <= 1.85e+43)
		tmp = t_1;
	elseif (y5 <= 1.55e+65)
		tmp = Float64(k * Float64(y0 * Float64(z * b)));
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (y5 * ((t * y2) - (y * y3)));
	tmp = 0.0;
	if (y5 <= -1.5e+107)
		tmp = t_1;
	elseif (y5 <= -5.3e-129)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (y5 <= 5.6e-267)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y5 <= 3.1e-104)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 3.8e-67)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 2.1e-16)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (y5 <= 1.85e+43)
		tmp = t_1;
	elseif (y5 <= 1.55e+65)
		tmp = k * (y0 * (z * b));
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -1.5e+107], t$95$1, If[LessEqual[y5, -5.3e-129], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.6e-267], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.1e-104], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.8e-67], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.1e-16], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.85e+43], t$95$1, If[LessEqual[y5, 1.55e+65], N[(k * N[(y0 * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y5 < -1.50000000000000012e107 or 2.1000000000000001e-16 < y5 < 1.85e43

   1. Initial program 26.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 44.2%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 44.2%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 44.2%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 44.2%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 57.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -1.50000000000000012e107 < y5 < -5.29999999999999974e-129

   1. Initial program 39.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 33.1%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 33.1%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 33.1%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -5.29999999999999974e-129 < y5 < 5.60000000000000009e-267

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 5.60000000000000009e-267 < y5 < 3.09999999999999976e-104

   1. Initial program 48.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 46.8%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 50.0%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 3.09999999999999976e-104 < y5 < 3.79999999999999988e-67

   1. Initial program 29.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 63.8%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 3.79999999999999988e-67 < y5 < 2.1000000000000001e-16

   1. Initial program 28.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 50.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 50.4%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 50.4%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 50.4%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 50.4%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]

   if 1.85e43 < y5 < 1.54999999999999995e65

   1. Initial program 41.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 79.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 80.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 80.4%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 80.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 80.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 80.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 42.5%

      \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(-1 \cdot \left(b \cdot z\right)\right)}\right)\right) \]
   8. Step-by-step derivation

      1. mul-1-neg 42.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(-b \cdot z\right)}\right)\right) \]

      2. *-commutative 42.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(-\color{blue}{z \cdot b}\right)\right)\right) \]

      3. distribute-rgt-neg-in 42.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(z \cdot \left(-b\right)\right)}\right)\right) \]

   9. Simplified 42.5%

      \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \color{blue}{\left(z \cdot \left(-b\right)\right)}\right)\right) \]

   if 1.54999999999999995e65 < y5

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 60.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 60.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 60.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 48.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -1.5 \cdot 10^{+107}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq -5.3 \cdot 10^{-129}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 5.6 \cdot 10^{-267}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 3.1 \cdot 10^{-104}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 3.8 \cdot 10^{-67}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 2.1 \cdot 10^{-16}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 1.85 \cdot 10^{+43}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 1.55 \cdot 10^{+65}:\\ \;\;\;\;k \cdot \left(y0 \cdot \left(z \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 23: 31.3% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{if}\;y5 \leq -2.7 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.4 \cdot 10^{+37}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -3.8 \cdot 10^{-134}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 1.1 \cdot 10^{-260}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 1.05 \cdot 10^{-103}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 10^{-64}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 4.5 \cdot 10^{-16}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{+26}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5))))))
   (if (<= y5 -2.7e+258)
     (* k (* y5 (- (* y i) (* y0 y2))))
     (if (<= y5 -1.4e+37)
       t_1
       (if (<= y5 -3.8e-134)
         (* k (* y4 (- (* y1 y2) (* y b))))
         (if (<= y5 1.1e-260)
           (* k (* z (- (* b y0) (* i y1))))
           (if (<= y5 1.05e-103)
             (* x (* y (- (* a b) (* c i))))
             (if (<= y5 1e-64)
               (* x (* y2 (- (* c y0) (* a y1))))
               (if (<= y5 4.5e-16)
                 (* k (* y1 (- (* y2 y4) (* z i))))
                 (if (<= y5 3.6e+26)
                   t_1
                   (* j (* y5 (- (* y0 y3) (* t i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double tmp;
	if (y5 <= -2.7e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -1.4e+37) {
		tmp = t_1;
	} else if (y5 <= -3.8e-134) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 1.1e-260) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 1.05e-103) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 1e-64) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 4.5e-16) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y5 <= 3.6e+26) {
		tmp = t_1;
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    if (y5 <= (-2.7d+258)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (y5 <= (-1.4d+37)) then
        tmp = t_1
    else if (y5 <= (-3.8d-134)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (y5 <= 1.1d-260) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y5 <= 1.05d-103) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 1d-64) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y5 <= 4.5d-16) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (y5 <= 3.6d+26) then
        tmp = t_1
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double tmp;
	if (y5 <= -2.7e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -1.4e+37) {
		tmp = t_1;
	} else if (y5 <= -3.8e-134) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 1.1e-260) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 1.05e-103) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 1e-64) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y5 <= 4.5e-16) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y5 <= 3.6e+26) {
		tmp = t_1;
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	tmp = 0
	if y5 <= -2.7e+258:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif y5 <= -1.4e+37:
		tmp = t_1
	elif y5 <= -3.8e-134:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif y5 <= 1.1e-260:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y5 <= 1.05e-103:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 1e-64:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y5 <= 4.5e-16:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif y5 <= 3.6e+26:
		tmp = t_1
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	tmp = 0.0
	if (y5 <= -2.7e+258)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (y5 <= -1.4e+37)
		tmp = t_1;
	elseif (y5 <= -3.8e-134)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (y5 <= 1.1e-260)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y5 <= 1.05e-103)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 1e-64)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y5 <= 4.5e-16)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (y5 <= 3.6e+26)
		tmp = t_1;
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	tmp = 0.0;
	if (y5 <= -2.7e+258)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (y5 <= -1.4e+37)
		tmp = t_1;
	elseif (y5 <= -3.8e-134)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (y5 <= 1.1e-260)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y5 <= 1.05e-103)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 1e-64)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y5 <= 4.5e-16)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (y5 <= 3.6e+26)
		tmp = t_1;
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -2.7e+258], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1.4e+37], t$95$1, If[LessEqual[y5, -3.8e-134], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.1e-260], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.05e-103], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1e-64], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 4.5e-16], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.6e+26], t$95$1, N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y5 < -2.69999999999999996e258

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 36.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -2.69999999999999996e258 < y5 < -1.3999999999999999e37 or 4.5000000000000002e-16 < y5 < 3.60000000000000024e26

   1. Initial program 30.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 35.8%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 51.7%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -1.3999999999999999e37 < y5 < -3.80000000000000003e-134

   1. Initial program 44.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 39.8%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 39.8%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -3.80000000000000003e-134 < y5 < 1.10000000000000008e-260

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 1.10000000000000008e-260 < y5 < 1.05000000000000002e-103

   1. Initial program 48.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 46.8%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 50.0%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 1.05000000000000002e-103 < y5 < 9.99999999999999965e-65

   1. Initial program 29.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 63.8%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 9.99999999999999965e-65 < y5 < 4.5000000000000002e-16

   1. Initial program 28.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 50.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 50.4%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 50.4%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 50.4%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 50.4%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]

   if 3.60000000000000024e26 < y5

   1. Initial program 24.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 34.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 57.1%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 57.1%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 57.1%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 57.1%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 57.1%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 57.1%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 57.1%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 50.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -2.7 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.4 \cdot 10^{+37}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -3.8 \cdot 10^{-134}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 1.1 \cdot 10^{-260}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 1.05 \cdot 10^{-103}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 10^{-64}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 4.5 \cdot 10^{-16}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{+26}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 24: 31.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{if}\;y5 \leq -3.1 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.95 \cdot 10^{+39}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -1.95 \cdot 10^{-132}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{-261}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 5.1 \cdot 10^{-110}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.6 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{+19}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 1.1 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y3 (- (* c y4) (* a y5))))))
   (if (<= y5 -3.1e+258)
     (* k (* y5 (- (* y i) (* y0 y2))))
     (if (<= y5 -1.95e+39)
       t_1
       (if (<= y5 -1.95e-132)
         (* k (* y4 (- (* y1 y2) (* y b))))
         (if (<= y5 3.6e-261)
           (* k (* z (- (* b y0) (* i y1))))
           (if (<= y5 5.1e-110)
             (* x (* y (- (* a b) (* c i))))
             (if (<= y5 5.6e-43)
               (* y1 (* y4 (- (* k y2) (* j y3))))
               (if (<= y5 3.6e+19)
                 t_1
                 (if (<= y5 1.1e+29)
                   (* c (* x (* y0 y2)))
                   (* j (* y5 (- (* y0 y3) (* t i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double tmp;
	if (y5 <= -3.1e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -1.95e+39) {
		tmp = t_1;
	} else if (y5 <= -1.95e-132) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 3.6e-261) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 5.1e-110) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 5.6e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 3.6e+19) {
		tmp = t_1;
	} else if (y5 <= 1.1e+29) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = y * (y3 * ((c * y4) - (a * y5)))
    if (y5 <= (-3.1d+258)) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else if (y5 <= (-1.95d+39)) then
        tmp = t_1
    else if (y5 <= (-1.95d-132)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (y5 <= 3.6d-261) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y5 <= 5.1d-110) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y5 <= 5.6d-43) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y5 <= 3.6d+19) then
        tmp = t_1
    else if (y5 <= 1.1d+29) then
        tmp = c * (x * (y0 * y2))
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y3 * ((c * y4) - (a * y5)));
	double tmp;
	if (y5 <= -3.1e+258) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else if (y5 <= -1.95e+39) {
		tmp = t_1;
	} else if (y5 <= -1.95e-132) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y5 <= 3.6e-261) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y5 <= 5.1e-110) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y5 <= 5.6e-43) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y5 <= 3.6e+19) {
		tmp = t_1;
	} else if (y5 <= 1.1e+29) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y3 * ((c * y4) - (a * y5)))
	tmp = 0
	if y5 <= -3.1e+258:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	elif y5 <= -1.95e+39:
		tmp = t_1
	elif y5 <= -1.95e-132:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif y5 <= 3.6e-261:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y5 <= 5.1e-110:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y5 <= 5.6e-43:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y5 <= 3.6e+19:
		tmp = t_1
	elif y5 <= 1.1e+29:
		tmp = c * (x * (y0 * y2))
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))))
	tmp = 0.0
	if (y5 <= -3.1e+258)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (y5 <= -1.95e+39)
		tmp = t_1;
	elseif (y5 <= -1.95e-132)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (y5 <= 3.6e-261)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y5 <= 5.1e-110)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y5 <= 5.6e-43)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y5 <= 3.6e+19)
		tmp = t_1;
	elseif (y5 <= 1.1e+29)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y * (y3 * ((c * y4) - (a * y5)));
	tmp = 0.0;
	if (y5 <= -3.1e+258)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	elseif (y5 <= -1.95e+39)
		tmp = t_1;
	elseif (y5 <= -1.95e-132)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (y5 <= 3.6e-261)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y5 <= 5.1e-110)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y5 <= 5.6e-43)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y5 <= 3.6e+19)
		tmp = t_1;
	elseif (y5 <= 1.1e+29)
		tmp = c * (x * (y0 * y2));
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -3.1e+258], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1.95e+39], t$95$1, If[LessEqual[y5, -1.95e-132], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.6e-261], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.1e-110], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 5.6e-43], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 3.6e+19], t$95$1, If[LessEqual[y5, 1.1e+29], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y5 < -3.0999999999999998e258

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 36.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 72.8%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 72.8%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if -3.0999999999999998e258 < y5 < -1.95e39 or 5.5999999999999996e-43 < y5 < 3.6e19

   1. Initial program 30.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 37.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 50.8%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -1.95e39 < y5 < -1.94999999999999991e-132

   1. Initial program 44.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 39.8%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 39.8%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 39.8%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -1.94999999999999991e-132 < y5 < 3.59999999999999999e-261

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.1%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 42.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 3.59999999999999999e-261 < y5 < 5.1000000000000002e-110

   1. Initial program 48.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 49.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 52.8%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 5.1000000000000002e-110 < y5 < 5.5999999999999996e-43

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 52.2%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 3.6e19 < y5 < 1.1000000000000001e29

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 100.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 67.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 100.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 100.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if 1.1000000000000001e29 < y5

   1. Initial program 25.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 34.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 58.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 58.0%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 58.0%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 51.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -3.1 \cdot 10^{+258}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq -1.95 \cdot 10^{+39}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -1.95 \cdot 10^{-132}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{-261}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y5 \leq 5.1 \cdot 10^{-110}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 5.6 \cdot 10^{-43}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y5 \leq 3.6 \cdot 10^{+19}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 1.1 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 25: 31.7% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y0 - i \cdot y1\\ \mathbf{if}\;z \leq -1.4 \cdot 10^{+137}:\\ \;\;\;\;k \cdot \left(z \cdot t_1\right)\\ \mathbf{elif}\;z \leq -6.5 \cdot 10^{-101}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{-278}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{-51}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{+133}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+196} \lor \neg \left(z \leq 2.4 \cdot 10^{+241}\right):\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1 \cdot \left(z \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y0) (* i y1))))
   (if (<= z -1.4e+137)
     (* k (* z t_1))
     (if (<= z -6.5e-101)
       (* y (* y3 (- (* c y4) (* a y5))))
       (if (<= z 3.5e-278)
         (* y3 (* y4 (- (* y c) (* j y1))))
         (if (<= z 1.05e-51)
           (* x (* y2 (- (* c y0) (* a y1))))
           (if (<= z 1.35e+133)
             (* x (* y (- (* a b) (* c i))))
             (if (or (<= z 3.1e+196) (not (<= z 2.4e+241)))
               (* c (* y3 (- (* y y4) (* z y0))))
               (* t_1 (* z k))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y0) - (i * y1);
	double tmp;
	if (z <= -1.4e+137) {
		tmp = k * (z * t_1);
	} else if (z <= -6.5e-101) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (z <= 3.5e-278) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 1.05e-51) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 1.35e+133) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if ((z <= 3.1e+196) || !(z <= 2.4e+241)) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else {
		tmp = t_1 * (z * k);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = (b * y0) - (i * y1)
    if (z <= (-1.4d+137)) then
        tmp = k * (z * t_1)
    else if (z <= (-6.5d-101)) then
        tmp = y * (y3 * ((c * y4) - (a * y5)))
    else if (z <= 3.5d-278) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (z <= 1.05d-51) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (z <= 1.35d+133) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if ((z <= 3.1d+196) .or. (.not. (z <= 2.4d+241))) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else
        tmp = t_1 * (z * k)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y0) - (i * y1);
	double tmp;
	if (z <= -1.4e+137) {
		tmp = k * (z * t_1);
	} else if (z <= -6.5e-101) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (z <= 3.5e-278) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 1.05e-51) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 1.35e+133) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if ((z <= 3.1e+196) || !(z <= 2.4e+241)) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else {
		tmp = t_1 * (z * k);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (b * y0) - (i * y1)
	tmp = 0
	if z <= -1.4e+137:
		tmp = k * (z * t_1)
	elif z <= -6.5e-101:
		tmp = y * (y3 * ((c * y4) - (a * y5)))
	elif z <= 3.5e-278:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif z <= 1.05e-51:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif z <= 1.35e+133:
		tmp = x * (y * ((a * b) - (c * i)))
	elif (z <= 3.1e+196) or not (z <= 2.4e+241):
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	else:
		tmp = t_1 * (z * k)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(b * y0) - Float64(i * y1))
	tmp = 0.0
	if (z <= -1.4e+137)
		tmp = Float64(k * Float64(z * t_1));
	elseif (z <= -6.5e-101)
		tmp = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))));
	elseif (z <= 3.5e-278)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (z <= 1.05e-51)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 1.35e+133)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif ((z <= 3.1e+196) || !(z <= 2.4e+241))
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	else
		tmp = Float64(t_1 * Float64(z * k));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (b * y0) - (i * y1);
	tmp = 0.0;
	if (z <= -1.4e+137)
		tmp = k * (z * t_1);
	elseif (z <= -6.5e-101)
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	elseif (z <= 3.5e-278)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (z <= 1.05e-51)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (z <= 1.35e+133)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif ((z <= 3.1e+196) || ~((z <= 2.4e+241)))
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	else
		tmp = t_1 * (z * k);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.4e+137], N[(k * N[(z * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -6.5e-101], N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.5e-278], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.05e-51], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.35e+133], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[z, 3.1e+196], N[Not[LessEqual[z, 2.4e+241]], $MachinePrecision]], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t$95$1 * N[(z * k), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if z < -1.4e137

   1. Initial program 18.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 43.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 62.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 62.6%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 62.6%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 62.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if -1.4e137 < z < -6.4999999999999996e-101

   1. Initial program 35.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 40.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 40.9%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -6.4999999999999996e-101 < z < 3.4999999999999997e-278

   1. Initial program 35.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 39.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 47.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 47.2%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 47.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if 3.4999999999999997e-278 < z < 1.05000000000000001e-51

   1. Initial program 36.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 43.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.05000000000000001e-51 < z < 1.3500000000000001e133

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 53.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 41.6%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 1.3500000000000001e133 < z < 3.1000000000000001e196 or 2.3999999999999999e241 < z

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 59.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in c around inf 77.4%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot \left(y0 \cdot z - y \cdot y4\right)\right)\right)} \]

   if 3.1000000000000001e196 < z < 2.3999999999999999e241

   1. Initial program 46.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 24.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 39.6%

         \[\leadsto \color{blue}{-k \cdot \left(z \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

      2. associate-*r* 46.9%

         \[\leadsto -\color{blue}{\left(k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      3. distribute-lft-neg-in 46.9%

         \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      4. *-commutative 46.9%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      5. *-commutative 46.9%

         \[\leadsto \left(-k \cdot z\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   6. Simplified 46.9%

      \[\leadsto \color{blue}{\left(-k \cdot z\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 49.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.4 \cdot 10^{+137}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -6.5 \cdot 10^{-101}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{-278}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{-51}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{+133}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+196} \lor \neg \left(z \leq 2.4 \cdot 10^{+241}\right):\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 26: 28.4% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{if}\;c \leq -3 \cdot 10^{+105}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \mathbf{elif}\;c \leq -5.3 \cdot 10^{-14}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -1.15 \cdot 10^{-247}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 1.8 \cdot 10^{-256}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 6 \cdot 10^{-168}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 8.5 \cdot 10^{-96}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;c \leq 8.2 \cdot 10^{+176}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* k (- (* y y5) (* z y1))))))
   (if (<= c -3e+105)
     (* y0 (* y2 (* x c)))
     (if (<= c -5.3e-14)
       t_1
       (if (<= c -1.15e-247)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= c 1.8e-256)
           (* k (* y1 (- (* y2 y4) (* z i))))
           (if (<= c 6e-168)
             (* a (* y5 (- (* t y2) (* y y3))))
             (if (<= c 8.5e-96)
               (* x (* (* a y1) (- y2)))
               (if (<= c 8.2e+176)
                 t_1
                 (* c (* y2 (- (* x y0) (* t y4)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (c <= -3e+105) {
		tmp = y0 * (y2 * (x * c));
	} else if (c <= -5.3e-14) {
		tmp = t_1;
	} else if (c <= -1.15e-247) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= 1.8e-256) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (c <= 6e-168) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (c <= 8.5e-96) {
		tmp = x * ((a * y1) * -y2);
	} else if (c <= 8.2e+176) {
		tmp = t_1;
	} else {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = i * (k * ((y * y5) - (z * y1)))
    if (c <= (-3d+105)) then
        tmp = y0 * (y2 * (x * c))
    else if (c <= (-5.3d-14)) then
        tmp = t_1
    else if (c <= (-1.15d-247)) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (c <= 1.8d-256) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (c <= 6d-168) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (c <= 8.5d-96) then
        tmp = x * ((a * y1) * -y2)
    else if (c <= 8.2d+176) then
        tmp = t_1
    else
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (c <= -3e+105) {
		tmp = y0 * (y2 * (x * c));
	} else if (c <= -5.3e-14) {
		tmp = t_1;
	} else if (c <= -1.15e-247) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= 1.8e-256) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (c <= 6e-168) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (c <= 8.5e-96) {
		tmp = x * ((a * y1) * -y2);
	} else if (c <= 8.2e+176) {
		tmp = t_1;
	} else {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (k * ((y * y5) - (z * y1)))
	tmp = 0
	if c <= -3e+105:
		tmp = y0 * (y2 * (x * c))
	elif c <= -5.3e-14:
		tmp = t_1
	elif c <= -1.15e-247:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif c <= 1.8e-256:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif c <= 6e-168:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif c <= 8.5e-96:
		tmp = x * ((a * y1) * -y2)
	elif c <= 8.2e+176:
		tmp = t_1
	else:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))))
	tmp = 0.0
	if (c <= -3e+105)
		tmp = Float64(y0 * Float64(y2 * Float64(x * c)));
	elseif (c <= -5.3e-14)
		tmp = t_1;
	elseif (c <= -1.15e-247)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (c <= 1.8e-256)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (c <= 6e-168)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (c <= 8.5e-96)
		tmp = Float64(x * Float64(Float64(a * y1) * Float64(-y2)));
	elseif (c <= 8.2e+176)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (k * ((y * y5) - (z * y1)));
	tmp = 0.0;
	if (c <= -3e+105)
		tmp = y0 * (y2 * (x * c));
	elseif (c <= -5.3e-14)
		tmp = t_1;
	elseif (c <= -1.15e-247)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (c <= 1.8e-256)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (c <= 6e-168)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (c <= 8.5e-96)
		tmp = x * ((a * y1) * -y2);
	elseif (c <= 8.2e+176)
		tmp = t_1;
	else
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -3e+105], N[(y0 * N[(y2 * N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -5.3e-14], t$95$1, If[LessEqual[c, -1.15e-247], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.8e-256], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 6e-168], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 8.5e-96], N[(x * N[(N[(a * y1), $MachinePrecision] * (-y2)), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 8.2e+176], t$95$1, N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if c < -3.0000000000000001e105

   1. Initial program 21.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 52.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 52.7%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 52.7%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 52.7%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 52.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 52.7%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 52.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 52.7%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 52.7%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   7. Taylor expanded in y5 around 0 44.5%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]
   8. Step-by-step derivation

      1. mul-1-neg 44.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(-c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      2. distribute-lft-neg-out 44.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(\left(-c\right) \cdot x\right)}\right) \cdot \left(-y0\right) \]

      3. *-commutative 44.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   9. Simplified 44.5%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   if -3.0000000000000001e105 < c < -5.3000000000000001e-14 or 8.49999999999999983e-96 < c < 8.1999999999999998e176

   1. Initial program 35.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 45.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 42.6%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -5.3000000000000001e-14 < c < -1.15e-247

   1. Initial program 35.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 47.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 47.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 47.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 47.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 47.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 47.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 47.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if -1.15e-247 < c < 1.8000000000000001e-256

   1. Initial program 38.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 46.7%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 46.7%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 46.7%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 46.7%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]

   if 1.8000000000000001e-256 < c < 5.99999999999999983e-168

   1. Initial program 38.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.7%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.7%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.7%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.7%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 47.9%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 5.99999999999999983e-168 < c < 8.49999999999999983e-96

   1. Initial program 54.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 55.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 48.5%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around 0 47.9%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   6. Step-by-step derivation

      1. neg-mul-1 47.9%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 47.9%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 47.9%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   7. Simplified 47.9%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if 8.1999999999999998e176 < c

   1. Initial program 15.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 23.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 43.2%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 45.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -3 \cdot 10^{+105}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \mathbf{elif}\;c \leq -5.3 \cdot 10^{-14}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -1.15 \cdot 10^{-247}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 1.8 \cdot 10^{-256}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 6 \cdot 10^{-168}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 8.5 \cdot 10^{-96}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;c \leq 8.2 \cdot 10^{+176}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 27: 28.2% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ t_2 := k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{if}\;y4 \leq -1.15 \cdot 10^{+171}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq -4.3 \cdot 10^{+131}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -1.52 \cdot 10^{-21}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq 1.05 \cdot 10^{-280}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 3.5 \cdot 10^{-208}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;y4 \leq 2.25 \cdot 10^{-153}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 2 \cdot 10^{+79}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* k (- (* y y5) (* z y1)))))
        (t_2 (* k (* y4 (- (* y1 y2) (* y b))))))
   (if (<= y4 -1.15e+171)
     t_2
     (if (<= y4 -4.3e+131)
       (* a (* y5 (- (* t y2) (* y y3))))
       (if (<= y4 -1.52e-21)
         t_2
         (if (<= y4 1.05e-280)
           t_1
           (if (<= y4 3.5e-208)
             (* x (* (* a y1) (- y2)))
             (if (<= y4 2.25e-153)
               t_1
               (if (<= y4 2e+79)
                 (* k (* y5 (- (* y i) (* y0 y2))))
                 (* j (* y5 (- (* y0 y3) (* t i)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (k * ((y * y5) - (z * y1)));
	double t_2 = k * (y4 * ((y1 * y2) - (y * b)));
	double tmp;
	if (y4 <= -1.15e+171) {
		tmp = t_2;
	} else if (y4 <= -4.3e+131) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y4 <= -1.52e-21) {
		tmp = t_2;
	} else if (y4 <= 1.05e-280) {
		tmp = t_1;
	} else if (y4 <= 3.5e-208) {
		tmp = x * ((a * y1) * -y2);
	} else if (y4 <= 2.25e-153) {
		tmp = t_1;
	} else if (y4 <= 2e+79) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = i * (k * ((y * y5) - (z * y1)))
    t_2 = k * (y4 * ((y1 * y2) - (y * b)))
    if (y4 <= (-1.15d+171)) then
        tmp = t_2
    else if (y4 <= (-4.3d+131)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (y4 <= (-1.52d-21)) then
        tmp = t_2
    else if (y4 <= 1.05d-280) then
        tmp = t_1
    else if (y4 <= 3.5d-208) then
        tmp = x * ((a * y1) * -y2)
    else if (y4 <= 2.25d-153) then
        tmp = t_1
    else if (y4 <= 2d+79) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (k * ((y * y5) - (z * y1)));
	double t_2 = k * (y4 * ((y1 * y2) - (y * b)));
	double tmp;
	if (y4 <= -1.15e+171) {
		tmp = t_2;
	} else if (y4 <= -4.3e+131) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y4 <= -1.52e-21) {
		tmp = t_2;
	} else if (y4 <= 1.05e-280) {
		tmp = t_1;
	} else if (y4 <= 3.5e-208) {
		tmp = x * ((a * y1) * -y2);
	} else if (y4 <= 2.25e-153) {
		tmp = t_1;
	} else if (y4 <= 2e+79) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (k * ((y * y5) - (z * y1)))
	t_2 = k * (y4 * ((y1 * y2) - (y * b)))
	tmp = 0
	if y4 <= -1.15e+171:
		tmp = t_2
	elif y4 <= -4.3e+131:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif y4 <= -1.52e-21:
		tmp = t_2
	elif y4 <= 1.05e-280:
		tmp = t_1
	elif y4 <= 3.5e-208:
		tmp = x * ((a * y1) * -y2)
	elif y4 <= 2.25e-153:
		tmp = t_1
	elif y4 <= 2e+79:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	else:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))))
	t_2 = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))))
	tmp = 0.0
	if (y4 <= -1.15e+171)
		tmp = t_2;
	elseif (y4 <= -4.3e+131)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (y4 <= -1.52e-21)
		tmp = t_2;
	elseif (y4 <= 1.05e-280)
		tmp = t_1;
	elseif (y4 <= 3.5e-208)
		tmp = Float64(x * Float64(Float64(a * y1) * Float64(-y2)));
	elseif (y4 <= 2.25e-153)
		tmp = t_1;
	elseif (y4 <= 2e+79)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	else
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (k * ((y * y5) - (z * y1)));
	t_2 = k * (y4 * ((y1 * y2) - (y * b)));
	tmp = 0.0;
	if (y4 <= -1.15e+171)
		tmp = t_2;
	elseif (y4 <= -4.3e+131)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (y4 <= -1.52e-21)
		tmp = t_2;
	elseif (y4 <= 1.05e-280)
		tmp = t_1;
	elseif (y4 <= 3.5e-208)
		tmp = x * ((a * y1) * -y2);
	elseif (y4 <= 2.25e-153)
		tmp = t_1;
	elseif (y4 <= 2e+79)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	else
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.15e+171], t$95$2, If[LessEqual[y4, -4.3e+131], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.52e-21], t$95$2, If[LessEqual[y4, 1.05e-280], t$95$1, If[LessEqual[y4, 3.5e-208], N[(x * N[(N[(a * y1), $MachinePrecision] * (-y2)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 2.25e-153], t$95$1, If[LessEqual[y4, 2e+79], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y4 < -1.15000000000000009e171 or -4.3000000000000001e131 < y4 < -1.52000000000000009e-21

   1. Initial program 34.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 44.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 47.4%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 47.4%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 47.4%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 47.4%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 47.4%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 47.4%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -1.15000000000000009e171 < y4 < -4.3000000000000001e131

   1. Initial program 57.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 43.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 43.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 43.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 71.7%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -1.52000000000000009e-21 < y4 < 1.05e-280 or 3.49999999999999991e-208 < y4 < 2.25e-153

   1. Initial program 36.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 39.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 1.05e-280 < y4 < 3.49999999999999991e-208

   1. Initial program 61.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 57.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 62.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around 0 46.1%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   6. Step-by-step derivation

      1. neg-mul-1 46.1%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 46.1%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 46.1%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   7. Simplified 46.1%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if 2.25e-153 < y4 < 1.99999999999999993e79

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 43.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 43.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]

   if 1.99999999999999993e79 < y4

   1. Initial program 14.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 40.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 45.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 45.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 45.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 45.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 45.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 45.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 45.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 44.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.15 \cdot 10^{+171}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq -4.3 \cdot 10^{+131}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -1.52 \cdot 10^{-21}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 1.05 \cdot 10^{-280}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 3.5 \cdot 10^{-208}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;y4 \leq 2.25 \cdot 10^{-153}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 2 \cdot 10^{+79}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 28: 28.9% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ t_2 := j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{if}\;y4 \leq -1.06 \cdot 10^{+171}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq -1.5 \cdot 10^{+130}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -40000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq -9.6 \cdot 10^{-204}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 9 \cdot 10^{-215}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq 4.2 \cdot 10^{-158}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 2.15 \cdot 10^{+79}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y4 (- (* y1 y2) (* y b)))))
        (t_2 (* j (* y5 (- (* y0 y3) (* t i))))))
   (if (<= y4 -1.06e+171)
     t_1
     (if (<= y4 -1.5e+130)
       (* a (* y5 (- (* t y2) (* y y3))))
       (if (<= y4 -40000000.0)
         t_1
         (if (<= y4 -9.6e-204)
           (* k (* z (- (* b y0) (* i y1))))
           (if (<= y4 9e-215)
             t_2
             (if (<= y4 4.2e-158)
               (* i (* k (- (* y y5) (* z y1))))
               (if (<= y4 2.15e+79)
                 (* k (* y5 (- (* y i) (* y0 y2))))
                 t_2)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y4 * ((y1 * y2) - (y * b)));
	double t_2 = j * (y5 * ((y0 * y3) - (t * i)));
	double tmp;
	if (y4 <= -1.06e+171) {
		tmp = t_1;
	} else if (y4 <= -1.5e+130) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y4 <= -40000000.0) {
		tmp = t_1;
	} else if (y4 <= -9.6e-204) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y4 <= 9e-215) {
		tmp = t_2;
	} else if (y4 <= 4.2e-158) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (y4 <= 2.15e+79) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = k * (y4 * ((y1 * y2) - (y * b)))
    t_2 = j * (y5 * ((y0 * y3) - (t * i)))
    if (y4 <= (-1.06d+171)) then
        tmp = t_1
    else if (y4 <= (-1.5d+130)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (y4 <= (-40000000.0d0)) then
        tmp = t_1
    else if (y4 <= (-9.6d-204)) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (y4 <= 9d-215) then
        tmp = t_2
    else if (y4 <= 4.2d-158) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (y4 <= 2.15d+79) then
        tmp = k * (y5 * ((y * i) - (y0 * y2)))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y4 * ((y1 * y2) - (y * b)));
	double t_2 = j * (y5 * ((y0 * y3) - (t * i)));
	double tmp;
	if (y4 <= -1.06e+171) {
		tmp = t_1;
	} else if (y4 <= -1.5e+130) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y4 <= -40000000.0) {
		tmp = t_1;
	} else if (y4 <= -9.6e-204) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (y4 <= 9e-215) {
		tmp = t_2;
	} else if (y4 <= 4.2e-158) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (y4 <= 2.15e+79) {
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y4 * ((y1 * y2) - (y * b)))
	t_2 = j * (y5 * ((y0 * y3) - (t * i)))
	tmp = 0
	if y4 <= -1.06e+171:
		tmp = t_1
	elif y4 <= -1.5e+130:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif y4 <= -40000000.0:
		tmp = t_1
	elif y4 <= -9.6e-204:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif y4 <= 9e-215:
		tmp = t_2
	elif y4 <= 4.2e-158:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif y4 <= 2.15e+79:
		tmp = k * (y5 * ((y * i) - (y0 * y2)))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))))
	t_2 = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))))
	tmp = 0.0
	if (y4 <= -1.06e+171)
		tmp = t_1;
	elseif (y4 <= -1.5e+130)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (y4 <= -40000000.0)
		tmp = t_1;
	elseif (y4 <= -9.6e-204)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (y4 <= 9e-215)
		tmp = t_2;
	elseif (y4 <= 4.2e-158)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (y4 <= 2.15e+79)
		tmp = Float64(k * Float64(y5 * Float64(Float64(y * i) - Float64(y0 * y2))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (y4 * ((y1 * y2) - (y * b)));
	t_2 = j * (y5 * ((y0 * y3) - (t * i)));
	tmp = 0.0;
	if (y4 <= -1.06e+171)
		tmp = t_1;
	elseif (y4 <= -1.5e+130)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (y4 <= -40000000.0)
		tmp = t_1;
	elseif (y4 <= -9.6e-204)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (y4 <= 9e-215)
		tmp = t_2;
	elseif (y4 <= 4.2e-158)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (y4 <= 2.15e+79)
		tmp = k * (y5 * ((y * i) - (y0 * y2)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.06e+171], t$95$1, If[LessEqual[y4, -1.5e+130], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -40000000.0], t$95$1, If[LessEqual[y4, -9.6e-204], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 9e-215], t$95$2, If[LessEqual[y4, 4.2e-158], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 2.15e+79], N[(k * N[(y5 * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y4 < -1.06000000000000001e171 or -1.5e130 < y4 < -4e7

   1. Initial program 37.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 47.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 51.3%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 51.3%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 51.3%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 51.3%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 51.3%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 51.3%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if -1.06000000000000001e171 < y4 < -1.5e130

   1. Initial program 57.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 43.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 43.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 43.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 71.7%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -4e7 < y4 < -9.6e-204

   1. Initial program 31.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 29.2%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 34.7%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 34.7%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 34.7%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 34.7%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if -9.6e-204 < y4 < 9e-215 or 2.1500000000000002e79 < y4

   1. Initial program 31.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 37.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 42.4%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 42.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 42.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 42.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 42.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 42.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 42.4%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if 9e-215 < y4 < 4.19999999999999983e-158

   1. Initial program 33.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 59.5%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 59.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 4.19999999999999983e-158 < y4 < 2.1500000000000002e79

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 43.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y + -1 \cdot \left(y0 \cdot y2\right)\right)}\right) \]

      2. mul-1-neg 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \left(i \cdot y + \color{blue}{\left(-y0 \cdot y2\right)}\right)\right) \]

      3. unsub-neg 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \color{blue}{\left(i \cdot y - y0 \cdot y2\right)}\right) \]

      4. *-commutative 43.7%

         \[\leadsto k \cdot \left(y5 \cdot \left(\color{blue}{y \cdot i} - y0 \cdot y2\right)\right) \]

   6. Simplified 43.7%

      \[\leadsto k \cdot \color{blue}{\left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 45.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.06 \cdot 10^{+171}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq -1.5 \cdot 10^{+130}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -40000000:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq -9.6 \cdot 10^{-204}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 9 \cdot 10^{-215}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y4 \leq 4.2 \cdot 10^{-158}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 2.15 \cdot 10^{+79}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 29: 32.0% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.65 \cdot 10^{+137}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -6.5 \cdot 10^{-101}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-278}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.4 \cdot 10^{-52}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{+130}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 1.65 \cdot 10^{+194}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 5.6 \cdot 10^{+221}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.65e+137)
   (* k (* z (- (* b y0) (* i y1))))
   (if (<= z -6.5e-101)
     (* y (* y3 (- (* c y4) (* a y5))))
     (if (<= z 1.8e-278)
       (* y3 (* y4 (- (* y c) (* j y1))))
       (if (<= z 2.4e-52)
         (* x (* y2 (- (* c y0) (* a y1))))
         (if (<= z 2.2e+130)
           (* x (* y (- (* a b) (* c i))))
           (if (<= z 1.65e+194)
             (* c (* y3 (- (* y y4) (* z y0))))
             (if (<= z 5.6e+221)
               (* i (* k (- (* y y5) (* z y1))))
               (* (* z y3) (- (* a y1) (* c y0)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.65e+137) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (z <= -6.5e-101) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (z <= 1.8e-278) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 2.4e-52) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 2.2e+130) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 1.65e+194) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (z <= 5.6e+221) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.65d+137)) then
        tmp = k * (z * ((b * y0) - (i * y1)))
    else if (z <= (-6.5d-101)) then
        tmp = y * (y3 * ((c * y4) - (a * y5)))
    else if (z <= 1.8d-278) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (z <= 2.4d-52) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (z <= 2.2d+130) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (z <= 1.65d+194) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (z <= 5.6d+221) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else
        tmp = (z * y3) * ((a * y1) - (c * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.65e+137) {
		tmp = k * (z * ((b * y0) - (i * y1)));
	} else if (z <= -6.5e-101) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (z <= 1.8e-278) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (z <= 2.4e-52) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 2.2e+130) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 1.65e+194) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (z <= 5.6e+221) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.65e+137:
		tmp = k * (z * ((b * y0) - (i * y1)))
	elif z <= -6.5e-101:
		tmp = y * (y3 * ((c * y4) - (a * y5)))
	elif z <= 1.8e-278:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif z <= 2.4e-52:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif z <= 2.2e+130:
		tmp = x * (y * ((a * b) - (c * i)))
	elif z <= 1.65e+194:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif z <= 5.6e+221:
		tmp = i * (k * ((y * y5) - (z * y1)))
	else:
		tmp = (z * y3) * ((a * y1) - (c * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.65e+137)
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	elseif (z <= -6.5e-101)
		tmp = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))));
	elseif (z <= 1.8e-278)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (z <= 2.4e-52)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 2.2e+130)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (z <= 1.65e+194)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (z <= 5.6e+221)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	else
		tmp = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.65e+137)
		tmp = k * (z * ((b * y0) - (i * y1)));
	elseif (z <= -6.5e-101)
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	elseif (z <= 1.8e-278)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (z <= 2.4e-52)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (z <= 2.2e+130)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (z <= 1.65e+194)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (z <= 5.6e+221)
		tmp = i * (k * ((y * y5) - (z * y1)));
	else
		tmp = (z * y3) * ((a * y1) - (c * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.65e+137], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -6.5e-101], N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e-278], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.4e-52], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.2e+130], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.65e+194], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.6e+221], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if z < -1.65000000000000001e137

   1. Initial program 18.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 43.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 62.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 62.6%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 62.6%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 62.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if -1.65000000000000001e137 < z < -6.4999999999999996e-101

   1. Initial program 35.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 40.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y3 around inf 40.9%

      \[\leadsto \color{blue}{y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -6.4999999999999996e-101 < z < 1.79999999999999998e-278

   1. Initial program 35.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 39.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 47.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(j \cdot y1 - c \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 47.2%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y4 \cdot \left(\color{blue}{y1 \cdot j} - c \cdot y\right)\right)\right) \]

   6. Simplified 47.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(y4 \cdot \left(y1 \cdot j - c \cdot y\right)\right)\right)} \]

   if 1.79999999999999998e-278 < z < 2.4000000000000002e-52

   1. Initial program 36.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 43.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 2.4000000000000002e-52 < z < 2.19999999999999993e130

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 53.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 41.6%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 2.19999999999999993e130 < z < 1.64999999999999992e194

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 75.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in c around inf 83.3%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot \left(y0 \cdot z - y \cdot y4\right)\right)\right)} \]

   if 1.64999999999999992e194 < z < 5.59999999999999978e221

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 13.7%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 50.8%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 5.59999999999999978e221 < z

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 40.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in z around inf 67.0%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 60.7%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   6. Simplified 60.7%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 49.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.65 \cdot 10^{+137}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -6.5 \cdot 10^{-101}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-278}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.4 \cdot 10^{-52}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{+130}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 1.65 \cdot 10^{+194}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 5.6 \cdot 10^{+221}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 30: 22.2% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{if}\;y0 \leq -3.1 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -4.8 \cdot 10^{+25}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -2.5 \cdot 10^{-232}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq 1.75 \cdot 10^{-236}:\\ \;\;\;\;\left(-i\right) \cdot \left(y5 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 5.8 \cdot 10^{-10}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq 1.15 \cdot 10^{+66}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 6.5 \cdot 10^{+182}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y5 (* t y2)))))
   (if (<= y0 -3.1e+150)
     (* j (* y5 (* y0 y3)))
     (if (<= y0 -4.8e+25)
       (* c (* x (* y0 y2)))
       (if (<= y0 -2.5e-232)
         t_1
         (if (<= y0 1.75e-236)
           (* (- i) (* y5 (* t j)))
           (if (<= y0 5.8e-10)
             t_1
             (if (<= y0 1.15e+66)
               (* i (* y5 (* y k)))
               (if (<= y0 6.5e+182)
                 (* j (* y5 (* t (- i))))
                 (* b (* k (* z y0))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y5 * (t * y2));
	double tmp;
	if (y0 <= -3.1e+150) {
		tmp = j * (y5 * (y0 * y3));
	} else if (y0 <= -4.8e+25) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -2.5e-232) {
		tmp = t_1;
	} else if (y0 <= 1.75e-236) {
		tmp = -i * (y5 * (t * j));
	} else if (y0 <= 5.8e-10) {
		tmp = t_1;
	} else if (y0 <= 1.15e+66) {
		tmp = i * (y5 * (y * k));
	} else if (y0 <= 6.5e+182) {
		tmp = j * (y5 * (t * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (y5 * (t * y2))
    if (y0 <= (-3.1d+150)) then
        tmp = j * (y5 * (y0 * y3))
    else if (y0 <= (-4.8d+25)) then
        tmp = c * (x * (y0 * y2))
    else if (y0 <= (-2.5d-232)) then
        tmp = t_1
    else if (y0 <= 1.75d-236) then
        tmp = -i * (y5 * (t * j))
    else if (y0 <= 5.8d-10) then
        tmp = t_1
    else if (y0 <= 1.15d+66) then
        tmp = i * (y5 * (y * k))
    else if (y0 <= 6.5d+182) then
        tmp = j * (y5 * (t * -i))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y5 * (t * y2));
	double tmp;
	if (y0 <= -3.1e+150) {
		tmp = j * (y5 * (y0 * y3));
	} else if (y0 <= -4.8e+25) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -2.5e-232) {
		tmp = t_1;
	} else if (y0 <= 1.75e-236) {
		tmp = -i * (y5 * (t * j));
	} else if (y0 <= 5.8e-10) {
		tmp = t_1;
	} else if (y0 <= 1.15e+66) {
		tmp = i * (y5 * (y * k));
	} else if (y0 <= 6.5e+182) {
		tmp = j * (y5 * (t * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (y5 * (t * y2))
	tmp = 0
	if y0 <= -3.1e+150:
		tmp = j * (y5 * (y0 * y3))
	elif y0 <= -4.8e+25:
		tmp = c * (x * (y0 * y2))
	elif y0 <= -2.5e-232:
		tmp = t_1
	elif y0 <= 1.75e-236:
		tmp = -i * (y5 * (t * j))
	elif y0 <= 5.8e-10:
		tmp = t_1
	elif y0 <= 1.15e+66:
		tmp = i * (y5 * (y * k))
	elif y0 <= 6.5e+182:
		tmp = j * (y5 * (t * -i))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(y5 * Float64(t * y2)))
	tmp = 0.0
	if (y0 <= -3.1e+150)
		tmp = Float64(j * Float64(y5 * Float64(y0 * y3)));
	elseif (y0 <= -4.8e+25)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y0 <= -2.5e-232)
		tmp = t_1;
	elseif (y0 <= 1.75e-236)
		tmp = Float64(Float64(-i) * Float64(y5 * Float64(t * j)));
	elseif (y0 <= 5.8e-10)
		tmp = t_1;
	elseif (y0 <= 1.15e+66)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (y0 <= 6.5e+182)
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (y5 * (t * y2));
	tmp = 0.0;
	if (y0 <= -3.1e+150)
		tmp = j * (y5 * (y0 * y3));
	elseif (y0 <= -4.8e+25)
		tmp = c * (x * (y0 * y2));
	elseif (y0 <= -2.5e-232)
		tmp = t_1;
	elseif (y0 <= 1.75e-236)
		tmp = -i * (y5 * (t * j));
	elseif (y0 <= 5.8e-10)
		tmp = t_1;
	elseif (y0 <= 1.15e+66)
		tmp = i * (y5 * (y * k));
	elseif (y0 <= 6.5e+182)
		tmp = j * (y5 * (t * -i));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(y5 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -3.1e+150], N[(j * N[(y5 * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -4.8e+25], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -2.5e-232], t$95$1, If[LessEqual[y0, 1.75e-236], N[((-i) * N[(y5 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.8e-10], t$95$1, If[LessEqual[y0, 1.15e+66], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 6.5e+182], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y0 < -3.10000000000000014e150

   1. Initial program 12.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 50.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 50.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   7. Taylor expanded in y3 around inf 47.5%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 47.5%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y3 \cdot y0\right)}\right) \]

   9. Simplified 47.5%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y3 \cdot y0\right)}\right) \]

   if -3.10000000000000014e150 < y0 < -4.79999999999999992e25

   1. Initial program 14.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 36.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 47.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 43.8%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 43.8%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 43.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if -4.79999999999999992e25 < y0 < -2.5e-232 or 1.74999999999999997e-236 < y0 < 5.79999999999999962e-10

   1. Initial program 38.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 33.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 33.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 33.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 33.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 30.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 24.9%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(t \cdot y2\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 24.9%

         \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   9. Simplified 24.9%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   if -2.5e-232 < y0 < 1.74999999999999997e-236

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 77.3%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 77.3%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 77.3%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 77.3%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 66.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 66.0%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 66.0%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 66.0%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 66.0%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 66.0%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 66.0%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around inf 36.4%

      \[\leadsto i \cdot \color{blue}{\left(-1 \cdot \left(j \cdot \left(t \cdot y5\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 36.4%

          \[\leadsto i \cdot \color{blue}{\left(-j \cdot \left(t \cdot y5\right)\right)} \]

       2. associate-*r* 39.8%

          \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t\right) \cdot y5}\right) \]

       3. distribute-rgt-neg-in 39.8%

          \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot \left(-y5\right)\right)} \]

   11. Simplified 39.8%

       \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot \left(-y5\right)\right)} \]

   if 5.79999999999999962e-10 < y0 < 1.15e66

   1. Initial program 39.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 35.6%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 35.6%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 35.6%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 35.6%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 40.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 40.7%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 40.7%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 40.7%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 40.7%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 40.7%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 40.7%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 32.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. associate-*r* 40.9%

          \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   11. Simplified 40.9%

       \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   if 1.15e66 < y0 < 6.4999999999999998e182

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 33.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 33.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   7. Taylor expanded in y3 around 0 41.6%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 41.6%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-i \cdot t\right)}\right) \]

      2. distribute-rgt-neg-in 41.6%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   9. Simplified 41.6%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   if 6.4999999999999998e182 < y0

   1. Initial program 34.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 58.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 58.9%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 58.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 58.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 58.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 55.4%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 37.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -3.1 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -4.8 \cdot 10^{+25}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -2.5 \cdot 10^{-232}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 1.75 \cdot 10^{-236}:\\ \;\;\;\;\left(-i\right) \cdot \left(y5 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 5.8 \cdot 10^{-10}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 1.15 \cdot 10^{+66}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 6.5 \cdot 10^{+182}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 31: 21.8% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -2.15 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -9.2 \cdot 10^{+30}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -2.7 \cdot 10^{-76}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;y0 \leq 2.9 \cdot 10^{-235}:\\ \;\;\;\;i \cdot \left(\left(t \cdot y5\right) \cdot \left(-j\right)\right)\\ \mathbf{elif}\;y0 \leq 3.4 \cdot 10^{-12}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 7 \cdot 10^{+62}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 1.9 \cdot 10^{+182}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y0 -2.15e+150)
   (* j (* y5 (* y0 y3)))
   (if (<= y0 -9.2e+30)
     (* c (* x (* y0 y2)))
     (if (<= y0 -2.7e-76)
       (* x (* (* a y1) (- y2)))
       (if (<= y0 2.9e-235)
         (* i (* (* t y5) (- j)))
         (if (<= y0 3.4e-12)
           (* a (* y5 (* t y2)))
           (if (<= y0 7e+62)
             (* i (* y5 (* y k)))
             (if (<= y0 1.9e+182)
               (* j (* y5 (* t (- i))))
               (* b (* k (* z y0)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y0 <= -2.15e+150) {
		tmp = j * (y5 * (y0 * y3));
	} else if (y0 <= -9.2e+30) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -2.7e-76) {
		tmp = x * ((a * y1) * -y2);
	} else if (y0 <= 2.9e-235) {
		tmp = i * ((t * y5) * -j);
	} else if (y0 <= 3.4e-12) {
		tmp = a * (y5 * (t * y2));
	} else if (y0 <= 7e+62) {
		tmp = i * (y5 * (y * k));
	} else if (y0 <= 1.9e+182) {
		tmp = j * (y5 * (t * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y0 <= (-2.15d+150)) then
        tmp = j * (y5 * (y0 * y3))
    else if (y0 <= (-9.2d+30)) then
        tmp = c * (x * (y0 * y2))
    else if (y0 <= (-2.7d-76)) then
        tmp = x * ((a * y1) * -y2)
    else if (y0 <= 2.9d-235) then
        tmp = i * ((t * y5) * -j)
    else if (y0 <= 3.4d-12) then
        tmp = a * (y5 * (t * y2))
    else if (y0 <= 7d+62) then
        tmp = i * (y5 * (y * k))
    else if (y0 <= 1.9d+182) then
        tmp = j * (y5 * (t * -i))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y0 <= -2.15e+150) {
		tmp = j * (y5 * (y0 * y3));
	} else if (y0 <= -9.2e+30) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -2.7e-76) {
		tmp = x * ((a * y1) * -y2);
	} else if (y0 <= 2.9e-235) {
		tmp = i * ((t * y5) * -j);
	} else if (y0 <= 3.4e-12) {
		tmp = a * (y5 * (t * y2));
	} else if (y0 <= 7e+62) {
		tmp = i * (y5 * (y * k));
	} else if (y0 <= 1.9e+182) {
		tmp = j * (y5 * (t * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y0 <= -2.15e+150:
		tmp = j * (y5 * (y0 * y3))
	elif y0 <= -9.2e+30:
		tmp = c * (x * (y0 * y2))
	elif y0 <= -2.7e-76:
		tmp = x * ((a * y1) * -y2)
	elif y0 <= 2.9e-235:
		tmp = i * ((t * y5) * -j)
	elif y0 <= 3.4e-12:
		tmp = a * (y5 * (t * y2))
	elif y0 <= 7e+62:
		tmp = i * (y5 * (y * k))
	elif y0 <= 1.9e+182:
		tmp = j * (y5 * (t * -i))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y0 <= -2.15e+150)
		tmp = Float64(j * Float64(y5 * Float64(y0 * y3)));
	elseif (y0 <= -9.2e+30)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y0 <= -2.7e-76)
		tmp = Float64(x * Float64(Float64(a * y1) * Float64(-y2)));
	elseif (y0 <= 2.9e-235)
		tmp = Float64(i * Float64(Float64(t * y5) * Float64(-j)));
	elseif (y0 <= 3.4e-12)
		tmp = Float64(a * Float64(y5 * Float64(t * y2)));
	elseif (y0 <= 7e+62)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (y0 <= 1.9e+182)
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y0 <= -2.15e+150)
		tmp = j * (y5 * (y0 * y3));
	elseif (y0 <= -9.2e+30)
		tmp = c * (x * (y0 * y2));
	elseif (y0 <= -2.7e-76)
		tmp = x * ((a * y1) * -y2);
	elseif (y0 <= 2.9e-235)
		tmp = i * ((t * y5) * -j);
	elseif (y0 <= 3.4e-12)
		tmp = a * (y5 * (t * y2));
	elseif (y0 <= 7e+62)
		tmp = i * (y5 * (y * k));
	elseif (y0 <= 1.9e+182)
		tmp = j * (y5 * (t * -i));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y0, -2.15e+150], N[(j * N[(y5 * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -9.2e+30], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -2.7e-76], N[(x * N[(N[(a * y1), $MachinePrecision] * (-y2)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.9e-235], N[(i * N[(N[(t * y5), $MachinePrecision] * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3.4e-12], N[(a * N[(y5 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 7e+62], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.9e+182], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y0 < -2.14999999999999999e150

   1. Initial program 12.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 50.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 50.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 50.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   7. Taylor expanded in y3 around inf 47.5%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 47.5%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y3 \cdot y0\right)}\right) \]

   9. Simplified 47.5%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y3 \cdot y0\right)}\right) \]

   if -2.14999999999999999e150 < y0 < -9.2e30

   1. Initial program 15.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 35.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 47.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 47.0%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 47.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if -9.2e30 < y0 < -2.7e-76

   1. Initial program 37.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 38.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 31.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around 0 30.0%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   6. Step-by-step derivation

      1. neg-mul-1 30.0%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 30.0%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 30.0%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   7. Simplified 30.0%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if -2.7e-76 < y0 < 2.90000000000000009e-235

   1. Initial program 42.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 53.5%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 53.5%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 53.5%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 53.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 45.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 45.3%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 45.3%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 45.3%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 45.3%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 45.3%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 45.3%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around inf 27.0%

      \[\leadsto i \cdot \color{blue}{\left(-1 \cdot \left(j \cdot \left(t \cdot y5\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 27.0%

          \[\leadsto i \cdot \color{blue}{\left(-j \cdot \left(t \cdot y5\right)\right)} \]

       2. *-commutative 27.0%

          \[\leadsto i \cdot \left(-j \cdot \color{blue}{\left(y5 \cdot t\right)}\right) \]

   11. Simplified 27.0%

       \[\leadsto i \cdot \color{blue}{\left(-j \cdot \left(y5 \cdot t\right)\right)} \]

   if 2.90000000000000009e-235 < y0 < 3.4000000000000001e-12

   1. Initial program 38.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 34.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 34.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 34.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 34.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 36.9%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 30.8%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(t \cdot y2\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 30.8%

         \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   9. Simplified 30.8%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   if 3.4000000000000001e-12 < y0 < 6.99999999999999967e62

   1. Initial program 39.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 35.6%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 35.6%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 35.6%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 35.6%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 40.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 40.7%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 40.7%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 40.7%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 40.7%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 40.7%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 40.7%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 32.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. associate-*r* 40.9%

          \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   11. Simplified 40.9%

       \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   if 6.99999999999999967e62 < y0 < 1.90000000000000006e182

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 33.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 33.8%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   7. Taylor expanded in y3 around 0 41.6%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 41.6%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-i \cdot t\right)}\right) \]

      2. distribute-rgt-neg-in 41.6%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   9. Simplified 41.6%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   if 1.90000000000000006e182 < y0

   1. Initial program 34.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 34.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 58.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 58.9%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 58.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 58.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 58.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 55.4%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 37.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -2.15 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -9.2 \cdot 10^{+30}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -2.7 \cdot 10^{-76}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;y0 \leq 2.9 \cdot 10^{-235}:\\ \;\;\;\;i \cdot \left(\left(t \cdot y5\right) \cdot \left(-j\right)\right)\\ \mathbf{elif}\;y0 \leq 3.4 \cdot 10^{-12}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 7 \cdot 10^{+62}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 1.9 \cdot 10^{+182}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 32: 29.8% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{if}\;y0 \leq -2.15 \cdot 10^{+150}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq -4.6 \cdot 10^{+51}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq -0.039:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq -1.15 \cdot 10^{-181}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 1.02 \cdot 10^{-243}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq 9 \cdot 10^{-11}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y5 (- (* y0 y3) (* t i))))))
   (if (<= y0 -2.15e+150)
     t_1
     (if (<= y0 -4.6e+51)
       (* c (* y2 (- (* x y0) (* t y4))))
       (if (<= y0 -0.039)
         t_1
         (if (<= y0 -1.15e-181)
           (* k (* y1 (- (* y2 y4) (* z i))))
           (if (<= y0 1.02e-243)
             (* k (* y4 (- (* y1 y2) (* y b))))
             (if (<= y0 9e-11)
               (* t (* y2 (- (* a y5) (* c y4))))
               (* k (* z (- (* b y0) (* i y1))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y5 * ((y0 * y3) - (t * i)));
	double tmp;
	if (y0 <= -2.15e+150) {
		tmp = t_1;
	} else if (y0 <= -4.6e+51) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y0 <= -0.039) {
		tmp = t_1;
	} else if (y0 <= -1.15e-181) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y0 <= 1.02e-243) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y0 <= 9e-11) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else {
		tmp = k * (z * ((b * y0) - (i * y1)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (y5 * ((y0 * y3) - (t * i)))
    if (y0 <= (-2.15d+150)) then
        tmp = t_1
    else if (y0 <= (-4.6d+51)) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (y0 <= (-0.039d0)) then
        tmp = t_1
    else if (y0 <= (-1.15d-181)) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (y0 <= 1.02d-243) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (y0 <= 9d-11) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else
        tmp = k * (z * ((b * y0) - (i * y1)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y5 * ((y0 * y3) - (t * i)));
	double tmp;
	if (y0 <= -2.15e+150) {
		tmp = t_1;
	} else if (y0 <= -4.6e+51) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y0 <= -0.039) {
		tmp = t_1;
	} else if (y0 <= -1.15e-181) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y0 <= 1.02e-243) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (y0 <= 9e-11) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else {
		tmp = k * (z * ((b * y0) - (i * y1)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y5 * ((y0 * y3) - (t * i)))
	tmp = 0
	if y0 <= -2.15e+150:
		tmp = t_1
	elif y0 <= -4.6e+51:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif y0 <= -0.039:
		tmp = t_1
	elif y0 <= -1.15e-181:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif y0 <= 1.02e-243:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif y0 <= 9e-11:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	else:
		tmp = k * (z * ((b * y0) - (i * y1)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))))
	tmp = 0.0
	if (y0 <= -2.15e+150)
		tmp = t_1;
	elseif (y0 <= -4.6e+51)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (y0 <= -0.039)
		tmp = t_1;
	elseif (y0 <= -1.15e-181)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (y0 <= 1.02e-243)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (y0 <= 9e-11)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	else
		tmp = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y5 * ((y0 * y3) - (t * i)));
	tmp = 0.0;
	if (y0 <= -2.15e+150)
		tmp = t_1;
	elseif (y0 <= -4.6e+51)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (y0 <= -0.039)
		tmp = t_1;
	elseif (y0 <= -1.15e-181)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (y0 <= 1.02e-243)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (y0 <= 9e-11)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	else
		tmp = k * (z * ((b * y0) - (i * y1)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -2.15e+150], t$95$1, If[LessEqual[y0, -4.6e+51], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -0.039], t$95$1, If[LessEqual[y0, -1.15e-181], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.02e-243], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 9e-11], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y0 < -2.14999999999999999e150 or -4.6000000000000001e51 < y0 < -0.0389999999999999999

   1. Initial program 17.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 33.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 48.4%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 48.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 48.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 48.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 48.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 48.4%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 48.4%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if -2.14999999999999999e150 < y0 < -4.6000000000000001e51

   1. Initial program 16.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 37.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 58.8%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if -0.0389999999999999999 < y0 < -1.14999999999999995e-181

   1. Initial program 36.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 35.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y1 around inf 37.7%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.7%

         \[\leadsto k \cdot \left(y1 \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right)\right) \]

      2. *-commutative 37.7%

         \[\leadsto k \cdot \left(y1 \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right)\right) \]

   6. Simplified 37.7%

      \[\leadsto k \cdot \color{blue}{\left(y1 \cdot \left(y4 \cdot y2 - z \cdot i\right)\right)} \]

   if -1.14999999999999995e-181 < y0 < 1.01999999999999996e-243

   1. Initial program 45.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 61.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y4 around inf 43.5%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 43.5%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 43.5%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 43.5%

         \[\leadsto k \cdot \left(y4 \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

      4. *-commutative 43.5%

         \[\leadsto k \cdot \left(y4 \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right)\right) \]

   6. Simplified 43.5%

      \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)} \]

   if 1.01999999999999996e-243 < y0 < 8.9999999999999999e-11

   1. Initial program 38.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 43.2%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if 8.9999999999999999e-11 < y0

   1. Initial program 35.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 38.5%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in z around inf 45.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 45.6%

         \[\leadsto k \cdot \left(z \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 45.6%

         \[\leadsto k \cdot \left(z \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   6. Simplified 45.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 45.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -2.15 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq -4.6 \cdot 10^{+51}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq -0.039:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq -1.15 \cdot 10^{-181}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 1.02 \cdot 10^{-243}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq 9 \cdot 10^{-11}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 33: 20.8% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -3.1 \cdot 10^{+154}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -7.5 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(-y \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -7.8 \cdot 10^{-175}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq -1.18 \cdot 10^{-293}:\\ \;\;\;\;i \cdot \left(\left(t \cdot y5\right) \cdot \left(-j\right)\right)\\ \mathbf{elif}\;z \leq 3.8 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 9.5 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -3.1e+154)
   (* k (* z (* b y0)))
   (if (<= z -7.5e-101)
     (* a (- (* y (* y3 y5))))
     (if (<= z -7.8e-175)
       (* a (* y5 (* t y2)))
       (if (<= z -1.18e-293)
         (* i (* (* t y5) (- j)))
         (if (<= z 3.8e-54)
           (* a (* t (* y2 y5)))
           (if (<= z 9.5e+178) (* i (* k (* y y5))) (* b (* k (* z y0))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.1e+154) {
		tmp = k * (z * (b * y0));
	} else if (z <= -7.5e-101) {
		tmp = a * -(y * (y3 * y5));
	} else if (z <= -7.8e-175) {
		tmp = a * (y5 * (t * y2));
	} else if (z <= -1.18e-293) {
		tmp = i * ((t * y5) * -j);
	} else if (z <= 3.8e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 9.5e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-3.1d+154)) then
        tmp = k * (z * (b * y0))
    else if (z <= (-7.5d-101)) then
        tmp = a * -(y * (y3 * y5))
    else if (z <= (-7.8d-175)) then
        tmp = a * (y5 * (t * y2))
    else if (z <= (-1.18d-293)) then
        tmp = i * ((t * y5) * -j)
    else if (z <= 3.8d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 9.5d+178) then
        tmp = i * (k * (y * y5))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.1e+154) {
		tmp = k * (z * (b * y0));
	} else if (z <= -7.5e-101) {
		tmp = a * -(y * (y3 * y5));
	} else if (z <= -7.8e-175) {
		tmp = a * (y5 * (t * y2));
	} else if (z <= -1.18e-293) {
		tmp = i * ((t * y5) * -j);
	} else if (z <= 3.8e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 9.5e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -3.1e+154:
		tmp = k * (z * (b * y0))
	elif z <= -7.5e-101:
		tmp = a * -(y * (y3 * y5))
	elif z <= -7.8e-175:
		tmp = a * (y5 * (t * y2))
	elif z <= -1.18e-293:
		tmp = i * ((t * y5) * -j)
	elif z <= 3.8e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 9.5e+178:
		tmp = i * (k * (y * y5))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -3.1e+154)
		tmp = Float64(k * Float64(z * Float64(b * y0)));
	elseif (z <= -7.5e-101)
		tmp = Float64(a * Float64(-Float64(y * Float64(y3 * y5))));
	elseif (z <= -7.8e-175)
		tmp = Float64(a * Float64(y5 * Float64(t * y2)));
	elseif (z <= -1.18e-293)
		tmp = Float64(i * Float64(Float64(t * y5) * Float64(-j)));
	elseif (z <= 3.8e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 9.5e+178)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -3.1e+154)
		tmp = k * (z * (b * y0));
	elseif (z <= -7.5e-101)
		tmp = a * -(y * (y3 * y5));
	elseif (z <= -7.8e-175)
		tmp = a * (y5 * (t * y2));
	elseif (z <= -1.18e-293)
		tmp = i * ((t * y5) * -j);
	elseif (z <= 3.8e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 9.5e+178)
		tmp = i * (k * (y * y5));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -3.1e+154], N[(k * N[(z * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.5e-101], N[(a * (-N[(y * N[(y3 * y5), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], If[LessEqual[z, -7.8e-175], N[(a * N[(y5 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.18e-293], N[(i * N[(N[(t * y5), $MachinePrecision] * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.8e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.5e+178], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if z < -3.1000000000000001e154

   1. Initial program 21.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 52.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 52.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 46.4%

      \[\leadsto k \cdot \color{blue}{\left(b \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 46.4%

         \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   9. Simplified 46.4%

      \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   if -3.1000000000000001e154 < z < -7.5000000000000001e-101

   1. Initial program 32.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 28.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 28.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 28.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 25.3%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around 0 27.2%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 27.2%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 27.2%

         \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

   9. Simplified 27.2%

      \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

   if -7.5000000000000001e-101 < z < -7.79999999999999997e-175

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 29.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 29.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 29.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 29.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 25.9%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 38.5%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(t \cdot y2\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 38.5%

         \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   9. Simplified 38.5%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   if -7.79999999999999997e-175 < z < -1.17999999999999999e-293

   1. Initial program 57.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 53.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 53.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 53.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 53.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 44.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 44.3%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 44.3%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 44.3%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 44.3%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 44.3%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 44.3%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around inf 34.6%

      \[\leadsto i \cdot \color{blue}{\left(-1 \cdot \left(j \cdot \left(t \cdot y5\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 34.6%

          \[\leadsto i \cdot \color{blue}{\left(-j \cdot \left(t \cdot y5\right)\right)} \]

       2. *-commutative 34.6%

          \[\leadsto i \cdot \left(-j \cdot \color{blue}{\left(y5 \cdot t\right)}\right) \]

   11. Simplified 34.6%

       \[\leadsto i \cdot \color{blue}{\left(-j \cdot \left(y5 \cdot t\right)\right)} \]

   if -1.17999999999999999e-293 < z < 3.8000000000000002e-54

   1. Initial program 32.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 37.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 34.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 33.3%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 3.8000000000000002e-54 < z < 9.5e178

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]

   if 9.5e178 < z

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 25.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 39.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 34.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.1 \cdot 10^{+154}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -7.5 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(-y \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -7.8 \cdot 10^{-175}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq -1.18 \cdot 10^{-293}:\\ \;\;\;\;i \cdot \left(\left(t \cdot y5\right) \cdot \left(-j\right)\right)\\ \mathbf{elif}\;z \leq 3.8 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 9.5 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 34: 20.8% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -3.1 \cdot 10^{+155}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -6.6 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(-y \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -6.6 \cdot 10^{-175}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq -1 \cdot 10^{-293}:\\ \;\;\;\;\left(-i\right) \cdot \left(y5 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 1.5 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -3.1e+155)
   (* k (* z (* b y0)))
   (if (<= z -6.6e-101)
     (* a (- (* y (* y3 y5))))
     (if (<= z -6.6e-175)
       (* a (* y5 (* t y2)))
       (if (<= z -1e-293)
         (* (- i) (* y5 (* t j)))
         (if (<= z 1.5e-54)
           (* a (* t (* y2 y5)))
           (if (<= z 3.5e+178) (* i (* k (* y y5))) (* b (* k (* z y0))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.1e+155) {
		tmp = k * (z * (b * y0));
	} else if (z <= -6.6e-101) {
		tmp = a * -(y * (y3 * y5));
	} else if (z <= -6.6e-175) {
		tmp = a * (y5 * (t * y2));
	} else if (z <= -1e-293) {
		tmp = -i * (y5 * (t * j));
	} else if (z <= 1.5e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 3.5e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-3.1d+155)) then
        tmp = k * (z * (b * y0))
    else if (z <= (-6.6d-101)) then
        tmp = a * -(y * (y3 * y5))
    else if (z <= (-6.6d-175)) then
        tmp = a * (y5 * (t * y2))
    else if (z <= (-1d-293)) then
        tmp = -i * (y5 * (t * j))
    else if (z <= 1.5d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 3.5d+178) then
        tmp = i * (k * (y * y5))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.1e+155) {
		tmp = k * (z * (b * y0));
	} else if (z <= -6.6e-101) {
		tmp = a * -(y * (y3 * y5));
	} else if (z <= -6.6e-175) {
		tmp = a * (y5 * (t * y2));
	} else if (z <= -1e-293) {
		tmp = -i * (y5 * (t * j));
	} else if (z <= 1.5e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 3.5e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -3.1e+155:
		tmp = k * (z * (b * y0))
	elif z <= -6.6e-101:
		tmp = a * -(y * (y3 * y5))
	elif z <= -6.6e-175:
		tmp = a * (y5 * (t * y2))
	elif z <= -1e-293:
		tmp = -i * (y5 * (t * j))
	elif z <= 1.5e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 3.5e+178:
		tmp = i * (k * (y * y5))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -3.1e+155)
		tmp = Float64(k * Float64(z * Float64(b * y0)));
	elseif (z <= -6.6e-101)
		tmp = Float64(a * Float64(-Float64(y * Float64(y3 * y5))));
	elseif (z <= -6.6e-175)
		tmp = Float64(a * Float64(y5 * Float64(t * y2)));
	elseif (z <= -1e-293)
		tmp = Float64(Float64(-i) * Float64(y5 * Float64(t * j)));
	elseif (z <= 1.5e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 3.5e+178)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -3.1e+155)
		tmp = k * (z * (b * y0));
	elseif (z <= -6.6e-101)
		tmp = a * -(y * (y3 * y5));
	elseif (z <= -6.6e-175)
		tmp = a * (y5 * (t * y2));
	elseif (z <= -1e-293)
		tmp = -i * (y5 * (t * j));
	elseif (z <= 1.5e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 3.5e+178)
		tmp = i * (k * (y * y5));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -3.1e+155], N[(k * N[(z * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -6.6e-101], N[(a * (-N[(y * N[(y3 * y5), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], If[LessEqual[z, -6.6e-175], N[(a * N[(y5 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1e-293], N[((-i) * N[(y5 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.5e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.5e+178], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if z < -3.09999999999999989e155

   1. Initial program 21.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 52.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 52.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 46.4%

      \[\leadsto k \cdot \color{blue}{\left(b \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 46.4%

         \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   9. Simplified 46.4%

      \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   if -3.09999999999999989e155 < z < -6.59999999999999968e-101

   1. Initial program 32.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 28.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 28.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 28.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 25.3%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around 0 27.2%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 27.2%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 27.2%

         \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

   9. Simplified 27.2%

      \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

   if -6.59999999999999968e-101 < z < -6.59999999999999997e-175

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 29.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 29.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 29.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 29.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 25.9%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 38.5%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(t \cdot y2\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 38.5%

         \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   9. Simplified 38.5%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   if -6.59999999999999997e-175 < z < -1.0000000000000001e-293

   1. Initial program 57.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 53.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 53.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 53.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 53.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 44.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 44.3%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 44.3%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 44.3%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 44.3%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 44.3%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 44.3%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around inf 34.6%

      \[\leadsto i \cdot \color{blue}{\left(-1 \cdot \left(j \cdot \left(t \cdot y5\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 34.6%

          \[\leadsto i \cdot \color{blue}{\left(-j \cdot \left(t \cdot y5\right)\right)} \]

       2. associate-*r* 34.7%

          \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t\right) \cdot y5}\right) \]

       3. distribute-rgt-neg-in 34.7%

          \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot \left(-y5\right)\right)} \]

   11. Simplified 34.7%

       \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot \left(-y5\right)\right)} \]

   if -1.0000000000000001e-293 < z < 1.50000000000000005e-54

   1. Initial program 32.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 37.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 34.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 33.3%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 1.50000000000000005e-54 < z < 3.5e178

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]

   if 3.5e178 < z

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 25.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 39.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 34.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.1 \cdot 10^{+155}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -6.6 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(-y \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -6.6 \cdot 10^{-175}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq -1 \cdot 10^{-293}:\\ \;\;\;\;\left(-i\right) \cdot \left(y5 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 1.5 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 35: 28.6% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{if}\;c \leq -2.8 \cdot 10^{+104}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \mathbf{elif}\;c \leq -8.8 \cdot 10^{-18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 5.2 \cdot 10^{-168}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 3.6 \cdot 10^{-95}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;c \leq 6.5 \cdot 10^{+177}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* k (- (* y y5) (* z y1))))))
   (if (<= c -2.8e+104)
     (* y0 (* y2 (* x c)))
     (if (<= c -8.8e-18)
       t_1
       (if (<= c 5.2e-168)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= c 3.6e-95)
           (* x (* (* a y1) (- y2)))
           (if (<= c 6.5e+177) t_1 (* c (* y2 (- (* x y0) (* t y4)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (c <= -2.8e+104) {
		tmp = y0 * (y2 * (x * c));
	} else if (c <= -8.8e-18) {
		tmp = t_1;
	} else if (c <= 5.2e-168) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= 3.6e-95) {
		tmp = x * ((a * y1) * -y2);
	} else if (c <= 6.5e+177) {
		tmp = t_1;
	} else {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = i * (k * ((y * y5) - (z * y1)))
    if (c <= (-2.8d+104)) then
        tmp = y0 * (y2 * (x * c))
    else if (c <= (-8.8d-18)) then
        tmp = t_1
    else if (c <= 5.2d-168) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (c <= 3.6d-95) then
        tmp = x * ((a * y1) * -y2)
    else if (c <= 6.5d+177) then
        tmp = t_1
    else
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (c <= -2.8e+104) {
		tmp = y0 * (y2 * (x * c));
	} else if (c <= -8.8e-18) {
		tmp = t_1;
	} else if (c <= 5.2e-168) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (c <= 3.6e-95) {
		tmp = x * ((a * y1) * -y2);
	} else if (c <= 6.5e+177) {
		tmp = t_1;
	} else {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (k * ((y * y5) - (z * y1)))
	tmp = 0
	if c <= -2.8e+104:
		tmp = y0 * (y2 * (x * c))
	elif c <= -8.8e-18:
		tmp = t_1
	elif c <= 5.2e-168:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif c <= 3.6e-95:
		tmp = x * ((a * y1) * -y2)
	elif c <= 6.5e+177:
		tmp = t_1
	else:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))))
	tmp = 0.0
	if (c <= -2.8e+104)
		tmp = Float64(y0 * Float64(y2 * Float64(x * c)));
	elseif (c <= -8.8e-18)
		tmp = t_1;
	elseif (c <= 5.2e-168)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (c <= 3.6e-95)
		tmp = Float64(x * Float64(Float64(a * y1) * Float64(-y2)));
	elseif (c <= 6.5e+177)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (k * ((y * y5) - (z * y1)));
	tmp = 0.0;
	if (c <= -2.8e+104)
		tmp = y0 * (y2 * (x * c));
	elseif (c <= -8.8e-18)
		tmp = t_1;
	elseif (c <= 5.2e-168)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (c <= 3.6e-95)
		tmp = x * ((a * y1) * -y2);
	elseif (c <= 6.5e+177)
		tmp = t_1;
	else
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -2.8e+104], N[(y0 * N[(y2 * N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -8.8e-18], t$95$1, If[LessEqual[c, 5.2e-168], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.6e-95], N[(x * N[(N[(a * y1), $MachinePrecision] * (-y2)), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 6.5e+177], t$95$1, N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if c < -2.8e104

   1. Initial program 21.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 52.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 52.7%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 52.7%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 52.7%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 52.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 52.7%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 52.7%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 52.7%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 52.7%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   7. Taylor expanded in y5 around 0 44.5%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]
   8. Step-by-step derivation

      1. mul-1-neg 44.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(-c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      2. distribute-lft-neg-out 44.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(\left(-c\right) \cdot x\right)}\right) \cdot \left(-y0\right) \]

      3. *-commutative 44.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   9. Simplified 44.5%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   if -2.8e104 < c < -8.7999999999999994e-18 or 3.6e-95 < c < 6.5000000000000002e177

   1. Initial program 35.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 45.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 42.6%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -8.7999999999999994e-18 < c < 5.2000000000000002e-168

   1. Initial program 36.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 40.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 40.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 40.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 40.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 40.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 40.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 40.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   if 5.2000000000000002e-168 < c < 3.6e-95

   1. Initial program 54.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 55.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 48.5%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around 0 47.9%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   6. Step-by-step derivation

      1. neg-mul-1 47.9%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 47.9%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 47.9%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   7. Simplified 47.9%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if 6.5000000000000002e177 < c

   1. Initial program 15.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 23.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 43.2%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 42.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -2.8 \cdot 10^{+104}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \mathbf{elif}\;c \leq -8.8 \cdot 10^{-18}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 5.2 \cdot 10^{-168}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;c \leq 3.6 \cdot 10^{-95}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;c \leq 6.5 \cdot 10^{+177}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 36: 20.6% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -6.5 \cdot 10^{+124}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -2 \cdot 10^{-151}:\\ \;\;\;\;k \cdot \left(\left(-y0\right) \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -1.16 \cdot 10^{-293}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.45 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 3.9 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -6.5e+124)
   (* k (* z (* b y0)))
   (if (<= z -2e-151)
     (* k (* (- y0) (* y2 y5)))
     (if (<= z -1.16e-293)
       (* j (* y5 (* t (- i))))
       (if (<= z 1.45e-54)
         (* a (* t (* y2 y5)))
         (if (<= z 3.9e+178) (* i (* k (* y y5))) (* b (* k (* z y0)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -6.5e+124) {
		tmp = k * (z * (b * y0));
	} else if (z <= -2e-151) {
		tmp = k * (-y0 * (y2 * y5));
	} else if (z <= -1.16e-293) {
		tmp = j * (y5 * (t * -i));
	} else if (z <= 1.45e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 3.9e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-6.5d+124)) then
        tmp = k * (z * (b * y0))
    else if (z <= (-2d-151)) then
        tmp = k * (-y0 * (y2 * y5))
    else if (z <= (-1.16d-293)) then
        tmp = j * (y5 * (t * -i))
    else if (z <= 1.45d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 3.9d+178) then
        tmp = i * (k * (y * y5))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -6.5e+124) {
		tmp = k * (z * (b * y0));
	} else if (z <= -2e-151) {
		tmp = k * (-y0 * (y2 * y5));
	} else if (z <= -1.16e-293) {
		tmp = j * (y5 * (t * -i));
	} else if (z <= 1.45e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 3.9e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -6.5e+124:
		tmp = k * (z * (b * y0))
	elif z <= -2e-151:
		tmp = k * (-y0 * (y2 * y5))
	elif z <= -1.16e-293:
		tmp = j * (y5 * (t * -i))
	elif z <= 1.45e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 3.9e+178:
		tmp = i * (k * (y * y5))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -6.5e+124)
		tmp = Float64(k * Float64(z * Float64(b * y0)));
	elseif (z <= -2e-151)
		tmp = Float64(k * Float64(Float64(-y0) * Float64(y2 * y5)));
	elseif (z <= -1.16e-293)
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	elseif (z <= 1.45e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 3.9e+178)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -6.5e+124)
		tmp = k * (z * (b * y0));
	elseif (z <= -2e-151)
		tmp = k * (-y0 * (y2 * y5));
	elseif (z <= -1.16e-293)
		tmp = j * (y5 * (t * -i));
	elseif (z <= 1.45e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 3.9e+178)
		tmp = i * (k * (y * y5));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -6.5e+124], N[(k * N[(z * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2e-151], N[(k * N[((-y0) * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.16e-293], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.45e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.9e+178], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if z < -6.50000000000000008e124

   1. Initial program 17.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 43.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 49.3%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 49.3%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 49.3%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 49.3%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 49.3%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 44.4%

      \[\leadsto k \cdot \color{blue}{\left(b \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 44.4%

         \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   9. Simplified 44.4%

      \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   if -6.50000000000000008e124 < z < -1.9999999999999999e-151

   1. Initial program 35.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 41.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 38.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 38.4%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 38.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 38.4%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 38.4%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around inf 30.5%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 30.5%

         \[\leadsto \color{blue}{-k \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 30.5%

         \[\leadsto \color{blue}{k \cdot \left(-y0 \cdot \left(y2 \cdot y5\right)\right)} \]

      3. distribute-rgt-neg-in 30.5%

         \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-y2 \cdot y5\right)\right)} \]

   9. Simplified 30.5%

      \[\leadsto \color{blue}{k \cdot \left(y0 \cdot \left(-y2 \cdot y5\right)\right)} \]

   if -1.9999999999999999e-151 < z < -1.16e-293

   1. Initial program 48.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 27.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 38.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 38.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 38.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 38.2%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 38.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 38.2%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 38.2%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   7. Taylor expanded in y3 around 0 38.4%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 38.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-i \cdot t\right)}\right) \]

      2. distribute-rgt-neg-in 38.4%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   9. Simplified 38.4%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   if -1.16e-293 < z < 1.45000000000000007e-54

   1. Initial program 32.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 37.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 34.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 33.3%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 1.45000000000000007e-54 < z < 3.8999999999999997e178

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]

   if 3.8999999999999997e178 < z

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 25.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 39.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 35.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -6.5 \cdot 10^{+124}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -2 \cdot 10^{-151}:\\ \;\;\;\;k \cdot \left(\left(-y0\right) \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -1.16 \cdot 10^{-293}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.45 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 3.9 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 37: 27.4% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -750000000000:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(x \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;x \leq -5.2 \cdot 10^{-191}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;x \leq 2.15 \cdot 10^{+21}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 7 \cdot 10^{+75}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq 3.7 \cdot 10^{+90}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -750000000000.0)
   (* a (* y2 (* x (- y1))))
   (if (<= x -5.2e-191)
     (* a (* y5 (- (* t y2) (* y y3))))
     (if (<= x 2.15e+21)
       (* i (* k (- (* y y5) (* z y1))))
       (if (<= x 7e+75)
         (* b (* k (* z y0)))
         (if (<= x 3.7e+90) (* i (* y5 (* y k))) (* y0 (* y2 (* x c)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -750000000000.0) {
		tmp = a * (y2 * (x * -y1));
	} else if (x <= -5.2e-191) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (x <= 2.15e+21) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (x <= 7e+75) {
		tmp = b * (k * (z * y0));
	} else if (x <= 3.7e+90) {
		tmp = i * (y5 * (y * k));
	} else {
		tmp = y0 * (y2 * (x * c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (x <= (-750000000000.0d0)) then
        tmp = a * (y2 * (x * -y1))
    else if (x <= (-5.2d-191)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (x <= 2.15d+21) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (x <= 7d+75) then
        tmp = b * (k * (z * y0))
    else if (x <= 3.7d+90) then
        tmp = i * (y5 * (y * k))
    else
        tmp = y0 * (y2 * (x * c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -750000000000.0) {
		tmp = a * (y2 * (x * -y1));
	} else if (x <= -5.2e-191) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (x <= 2.15e+21) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (x <= 7e+75) {
		tmp = b * (k * (z * y0));
	} else if (x <= 3.7e+90) {
		tmp = i * (y5 * (y * k));
	} else {
		tmp = y0 * (y2 * (x * c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if x <= -750000000000.0:
		tmp = a * (y2 * (x * -y1))
	elif x <= -5.2e-191:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif x <= 2.15e+21:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif x <= 7e+75:
		tmp = b * (k * (z * y0))
	elif x <= 3.7e+90:
		tmp = i * (y5 * (y * k))
	else:
		tmp = y0 * (y2 * (x * c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (x <= -750000000000.0)
		tmp = Float64(a * Float64(y2 * Float64(x * Float64(-y1))));
	elseif (x <= -5.2e-191)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (x <= 2.15e+21)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (x <= 7e+75)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (x <= 3.7e+90)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	else
		tmp = Float64(y0 * Float64(y2 * Float64(x * c)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (x <= -750000000000.0)
		tmp = a * (y2 * (x * -y1));
	elseif (x <= -5.2e-191)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (x <= 2.15e+21)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (x <= 7e+75)
		tmp = b * (k * (z * y0));
	elseif (x <= 3.7e+90)
		tmp = i * (y5 * (y * k));
	else
		tmp = y0 * (y2 * (x * c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[x, -750000000000.0], N[(a * N[(y2 * N[(x * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -5.2e-191], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 2.15e+21], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 7e+75], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.7e+90], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(y2 * N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if x < -7.5e11

   1. Initial program 35.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 44.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 48.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around 0 42.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 42.5%

         \[\leadsto \color{blue}{-a \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)} \]

      2. *-commutative 42.5%

         \[\leadsto -\color{blue}{\left(x \cdot \left(y1 \cdot y2\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 42.5%

         \[\leadsto \color{blue}{\left(x \cdot \left(y1 \cdot y2\right)\right) \cdot \left(-a\right)} \]

      4. associate-*r* 46.5%

         \[\leadsto \color{blue}{\left(\left(x \cdot y1\right) \cdot y2\right)} \cdot \left(-a\right) \]

   7. Simplified 46.5%

      \[\leadsto \color{blue}{\left(\left(x \cdot y1\right) \cdot y2\right) \cdot \left(-a\right)} \]

   if -7.5e11 < x < -5.19999999999999972e-191

   1. Initial program 43.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 50.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 50.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 50.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 50.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 46.7%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -5.19999999999999972e-191 < x < 2.15e21

   1. Initial program 37.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 35.5%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in i around inf 33.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 2.15e21 < x < 6.9999999999999997e75

   1. Initial program 17.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 49.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 59.6%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 59.6%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 59.6%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 59.6%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 59.6%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 51.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 6.9999999999999997e75 < x < 3.7e90

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 0.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 0.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 0.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 0.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 33.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 33.3%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 33.3%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 33.3%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 33.3%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 33.3%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 33.3%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 35.4%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. associate-*r* 38.4%

          \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   11. Simplified 38.4%

       \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   if 3.7e90 < x

   1. Initial program 17.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 36.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y0 around -inf 49.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 49.6%

         \[\leadsto \color{blue}{-y0 \cdot \left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]

      2. *-commutative 49.6%

         \[\leadsto -\color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot y0} \]

      3. distribute-rgt-neg-in 49.6%

         \[\leadsto \color{blue}{\left(y2 \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right) \cdot \left(-y0\right)} \]

      4. +-commutative 49.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 + -1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]

      5. mul-1-neg 49.6%

         \[\leadsto \left(y2 \cdot \left(k \cdot y5 + \color{blue}{\left(-c \cdot x\right)}\right)\right) \cdot \left(-y0\right) \]

      6. unsub-neg 49.6%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(k \cdot y5 - c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      7. *-commutative 49.6%

         \[\leadsto \left(y2 \cdot \left(\color{blue}{y5 \cdot k} - c \cdot x\right)\right) \cdot \left(-y0\right) \]

   6. Simplified 49.6%

      \[\leadsto \color{blue}{\left(y2 \cdot \left(y5 \cdot k - c \cdot x\right)\right) \cdot \left(-y0\right)} \]

   7. Taylor expanded in y5 around 0 45.5%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot x\right)\right)}\right) \cdot \left(-y0\right) \]
   8. Step-by-step derivation

      1. mul-1-neg 45.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(-c \cdot x\right)}\right) \cdot \left(-y0\right) \]

      2. distribute-lft-neg-out 45.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(\left(-c\right) \cdot x\right)}\right) \cdot \left(-y0\right) \]

      3. *-commutative 45.5%

         \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]

   9. Simplified 45.5%

      \[\leadsto \left(y2 \cdot \color{blue}{\left(x \cdot \left(-c\right)\right)}\right) \cdot \left(-y0\right) \]
3. Recombined 6 regimes into one program.

4. Final simplification 41.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -750000000000:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(x \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;x \leq -5.2 \cdot 10^{-191}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;x \leq 2.15 \cdot 10^{+21}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 7 \cdot 10^{+75}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq 3.7 \cdot 10^{+90}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 38: 25.1% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y1 \leq -1.55 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;y1 \leq -1.7 \cdot 10^{-162} \lor \neg \left(y1 \leq 1.1 \cdot 10^{-213}\right) \land y1 \leq 4.5 \cdot 10^{+214}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y1 -1.55e+62)
   (* x (* (* a y1) (- y2)))
   (if (or (<= y1 -1.7e-162) (and (not (<= y1 1.1e-213)) (<= y1 4.5e+214)))
     (* a (* y5 (- (* t y2) (* y y3))))
     (* j (* y5 (* t (- i)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y1 <= -1.55e+62) {
		tmp = x * ((a * y1) * -y2);
	} else if ((y1 <= -1.7e-162) || (!(y1 <= 1.1e-213) && (y1 <= 4.5e+214))) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else {
		tmp = j * (y5 * (t * -i));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y1 <= (-1.55d+62)) then
        tmp = x * ((a * y1) * -y2)
    else if ((y1 <= (-1.7d-162)) .or. (.not. (y1 <= 1.1d-213)) .and. (y1 <= 4.5d+214)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else
        tmp = j * (y5 * (t * -i))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y1 <= -1.55e+62) {
		tmp = x * ((a * y1) * -y2);
	} else if ((y1 <= -1.7e-162) || (!(y1 <= 1.1e-213) && (y1 <= 4.5e+214))) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else {
		tmp = j * (y5 * (t * -i));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y1 <= -1.55e+62:
		tmp = x * ((a * y1) * -y2)
	elif (y1 <= -1.7e-162) or (not (y1 <= 1.1e-213) and (y1 <= 4.5e+214)):
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	else:
		tmp = j * (y5 * (t * -i))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y1 <= -1.55e+62)
		tmp = Float64(x * Float64(Float64(a * y1) * Float64(-y2)));
	elseif ((y1 <= -1.7e-162) || (!(y1 <= 1.1e-213) && (y1 <= 4.5e+214)))
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	else
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y1 <= -1.55e+62)
		tmp = x * ((a * y1) * -y2);
	elseif ((y1 <= -1.7e-162) || (~((y1 <= 1.1e-213)) && (y1 <= 4.5e+214)))
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	else
		tmp = j * (y5 * (t * -i));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y1, -1.55e+62], N[(x * N[(N[(a * y1), $MachinePrecision] * (-y2)), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[y1, -1.7e-162], And[N[Not[LessEqual[y1, 1.1e-213]], $MachinePrecision], LessEqual[y1, 4.5e+214]]], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if y1 < -1.55000000000000007e62

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 39.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 43.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around 0 40.6%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   6. Step-by-step derivation

      1. neg-mul-1 40.6%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 40.6%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 40.6%

         \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   7. Simplified 40.6%

      \[\leadsto x \cdot \left(y2 \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if -1.55000000000000007e62 < y1 < -1.7e-162 or 1.10000000000000005e-213 < y1 < 4.49999999999999968e214

   1. Initial program 32.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 38.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 34.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -1.7e-162 < y1 < 1.10000000000000005e-213 or 4.49999999999999968e214 < y1

   1. Initial program 32.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 37.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y5 around inf 42.3%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) + y0 \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 42.3%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 + -1 \cdot \left(i \cdot t\right)\right)}\right) \]

      2. mul-1-neg 42.3%

         \[\leadsto j \cdot \left(y5 \cdot \left(y0 \cdot y3 + \color{blue}{\left(-i \cdot t\right)}\right)\right) \]

      3. unsub-neg 42.3%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(y0 \cdot y3 - i \cdot t\right)}\right) \]

      4. *-commutative 42.3%

         \[\leadsto j \cdot \left(y5 \cdot \left(\color{blue}{y3 \cdot y0} - i \cdot t\right)\right) \]

      5. *-commutative 42.3%

         \[\leadsto j \cdot \left(y5 \cdot \left(y3 \cdot y0 - \color{blue}{t \cdot i}\right)\right) \]

   6. Simplified 42.3%

      \[\leadsto j \cdot \color{blue}{\left(y5 \cdot \left(y3 \cdot y0 - t \cdot i\right)\right)} \]

   7. Taylor expanded in y3 around 0 33.8%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(-i \cdot t\right)}\right) \]

      2. distribute-rgt-neg-in 33.8%

         \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]

   9. Simplified 33.8%

      \[\leadsto j \cdot \left(y5 \cdot \color{blue}{\left(i \cdot \left(-t\right)\right)}\right) \]
3. Recombined 3 regimes into one program.

4. Final simplification 35.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -1.55 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(a \cdot y1\right) \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;y1 \leq -1.7 \cdot 10^{-162} \lor \neg \left(y1 \leq 1.1 \cdot 10^{-213}\right) \land y1 \leq 4.5 \cdot 10^{+214}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 39: 21.3% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{if}\;z \leq -8.2 \cdot 10^{+127}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{-136}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;z \leq 2.15 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* k (* z y0)))))
   (if (<= z -8.2e+127)
     t_1
     (if (<= z -1.4e-136)
       (* i (* y5 (* y k)))
       (if (<= z 2.15e-54)
         (* a (* t (* y2 y5)))
         (if (<= z 7e+178) (* i (* k (* y y5))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (k * (z * y0));
	double tmp;
	if (z <= -8.2e+127) {
		tmp = t_1;
	} else if (z <= -1.4e-136) {
		tmp = i * (y5 * (y * k));
	} else if (z <= 2.15e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 7e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (k * (z * y0))
    if (z <= (-8.2d+127)) then
        tmp = t_1
    else if (z <= (-1.4d-136)) then
        tmp = i * (y5 * (y * k))
    else if (z <= 2.15d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 7d+178) then
        tmp = i * (k * (y * y5))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (k * (z * y0));
	double tmp;
	if (z <= -8.2e+127) {
		tmp = t_1;
	} else if (z <= -1.4e-136) {
		tmp = i * (y5 * (y * k));
	} else if (z <= 2.15e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 7e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (k * (z * y0))
	tmp = 0
	if z <= -8.2e+127:
		tmp = t_1
	elif z <= -1.4e-136:
		tmp = i * (y5 * (y * k))
	elif z <= 2.15e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 7e+178:
		tmp = i * (k * (y * y5))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(k * Float64(z * y0)))
	tmp = 0.0
	if (z <= -8.2e+127)
		tmp = t_1;
	elseif (z <= -1.4e-136)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (z <= 2.15e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 7e+178)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (k * (z * y0));
	tmp = 0.0;
	if (z <= -8.2e+127)
		tmp = t_1;
	elseif (z <= -1.4e-136)
		tmp = i * (y5 * (y * k));
	elseif (z <= 2.15e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 7e+178)
		tmp = i * (k * (y * y5));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -8.2e+127], t$95$1, If[LessEqual[z, -1.4e-136], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.15e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7e+178], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if z < -8.19999999999999965e127 or 7.00000000000000001e178 < z

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 35.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 44.6%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 44.6%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 44.6%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 44.6%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 44.6%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 41.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if -8.19999999999999965e127 < z < -1.4e-136

   1. Initial program 35.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 29.5%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 29.5%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 29.5%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 29.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 27.8%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 27.8%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 27.8%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 27.8%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 27.8%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 27.8%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 27.8%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 17.9%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. associate-*r* 23.8%

          \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   11. Simplified 23.8%

       \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   if -1.4e-136 < z < 2.15e-54

   1. Initial program 36.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 40.2%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 40.2%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 40.2%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 40.2%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 29.5%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 28.6%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 2.15e-54 < z < 7.00000000000000001e178

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 31.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -8.2 \cdot 10^{+127}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{-136}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;z \leq 2.15 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 40: 21.3% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -7.8 \cdot 10^{+152}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -7.5 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(-y \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.85 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 4.2 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -7.8e+152)
   (* k (* z (* b y0)))
   (if (<= z -7.5e-101)
     (* a (- (* y (* y3 y5))))
     (if (<= z 1.85e-54)
       (* a (* t (* y2 y5)))
       (if (<= z 4.2e+178) (* i (* k (* y y5))) (* b (* k (* z y0))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -7.8e+152) {
		tmp = k * (z * (b * y0));
	} else if (z <= -7.5e-101) {
		tmp = a * -(y * (y3 * y5));
	} else if (z <= 1.85e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 4.2e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-7.8d+152)) then
        tmp = k * (z * (b * y0))
    else if (z <= (-7.5d-101)) then
        tmp = a * -(y * (y3 * y5))
    else if (z <= 1.85d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 4.2d+178) then
        tmp = i * (k * (y * y5))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -7.8e+152) {
		tmp = k * (z * (b * y0));
	} else if (z <= -7.5e-101) {
		tmp = a * -(y * (y3 * y5));
	} else if (z <= 1.85e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 4.2e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -7.8e+152:
		tmp = k * (z * (b * y0))
	elif z <= -7.5e-101:
		tmp = a * -(y * (y3 * y5))
	elif z <= 1.85e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 4.2e+178:
		tmp = i * (k * (y * y5))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -7.8e+152)
		tmp = Float64(k * Float64(z * Float64(b * y0)));
	elseif (z <= -7.5e-101)
		tmp = Float64(a * Float64(-Float64(y * Float64(y3 * y5))));
	elseif (z <= 1.85e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 4.2e+178)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -7.8e+152)
		tmp = k * (z * (b * y0));
	elseif (z <= -7.5e-101)
		tmp = a * -(y * (y3 * y5));
	elseif (z <= 1.85e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 4.2e+178)
		tmp = i * (k * (y * y5));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -7.8e+152], N[(k * N[(z * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.5e-101], N[(a * (-N[(y * N[(y3 * y5), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], If[LessEqual[z, 1.85e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.2e+178], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -7.80000000000000022e152

   1. Initial program 21.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 39.8%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 52.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 52.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 52.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 46.4%

      \[\leadsto k \cdot \color{blue}{\left(b \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 46.4%

         \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   9. Simplified 46.4%

      \[\leadsto k \cdot \color{blue}{\left(\left(b \cdot y0\right) \cdot z\right)} \]

   if -7.80000000000000022e152 < z < -7.5000000000000001e-101

   1. Initial program 32.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 28.8%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 28.8%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 28.8%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 25.3%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around 0 27.2%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 27.2%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 27.2%

         \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

   9. Simplified 27.2%

      \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

   if -7.5000000000000001e-101 < z < 1.8500000000000001e-54

   1. Initial program 36.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.4%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.4%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.4%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.4%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 28.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 27.6%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 1.8500000000000001e-54 < z < 4.1999999999999997e178

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]

   if 4.1999999999999997e178 < z

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 25.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 39.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 31.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7.8 \cdot 10^{+152}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -7.5 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(-y \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.85 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 4.2 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 41: 21.9% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{if}\;z \leq -6.8 \cdot 10^{+99}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.28 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{+179}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* k (* z y0)))))
   (if (<= z -6.8e+99)
     t_1
     (if (<= z 1.28e-54)
       (* a (* t (* y2 y5)))
       (if (<= z 1.3e+179) (* i (* k (* y y5))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (k * (z * y0));
	double tmp;
	if (z <= -6.8e+99) {
		tmp = t_1;
	} else if (z <= 1.28e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 1.3e+179) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (k * (z * y0))
    if (z <= (-6.8d+99)) then
        tmp = t_1
    else if (z <= 1.28d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 1.3d+179) then
        tmp = i * (k * (y * y5))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (k * (z * y0));
	double tmp;
	if (z <= -6.8e+99) {
		tmp = t_1;
	} else if (z <= 1.28e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 1.3e+179) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (k * (z * y0))
	tmp = 0
	if z <= -6.8e+99:
		tmp = t_1
	elif z <= 1.28e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 1.3e+179:
		tmp = i * (k * (y * y5))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(k * Float64(z * y0)))
	tmp = 0.0
	if (z <= -6.8e+99)
		tmp = t_1;
	elseif (z <= 1.28e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 1.3e+179)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (k * (z * y0));
	tmp = 0.0;
	if (z <= -6.8e+99)
		tmp = t_1;
	elseif (z <= 1.28e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 1.3e+179)
		tmp = i * (k * (y * y5));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -6.8e+99], t$95$1, If[LessEqual[z, 1.28e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.3e+179], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if z < -6.79999999999999968e99 or 1.3000000000000001e179 < z

   1. Initial program 22.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 37.1%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 44.3%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 44.3%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 44.3%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 44.3%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 44.3%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 40.3%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if -6.79999999999999968e99 < z < 1.2800000000000001e-54

   1. Initial program 36.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 36.5%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 36.5%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 36.5%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 36.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 28.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 23.7%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 1.2800000000000001e-54 < z < 1.3000000000000001e179

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 29.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -6.8 \cdot 10^{+99}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 1.28 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{+179}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 42: 21.3% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.8 \cdot 10^{-109}:\\ \;\;\;\;k \cdot \left(b \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 2.35 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 4.2 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.8e-109)
   (* k (* b (* z y0)))
   (if (<= z 2.35e-54)
     (* a (* t (* y2 y5)))
     (if (<= z 4.2e+178) (* i (* k (* y y5))) (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.8e-109) {
		tmp = k * (b * (z * y0));
	} else if (z <= 2.35e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 4.2e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.8d-109)) then
        tmp = k * (b * (z * y0))
    else if (z <= 2.35d-54) then
        tmp = a * (t * (y2 * y5))
    else if (z <= 4.2d+178) then
        tmp = i * (k * (y * y5))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.8e-109) {
		tmp = k * (b * (z * y0));
	} else if (z <= 2.35e-54) {
		tmp = a * (t * (y2 * y5));
	} else if (z <= 4.2e+178) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.8e-109:
		tmp = k * (b * (z * y0))
	elif z <= 2.35e-54:
		tmp = a * (t * (y2 * y5))
	elif z <= 4.2e+178:
		tmp = i * (k * (y * y5))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.8e-109)
		tmp = Float64(k * Float64(b * Float64(z * y0)));
	elseif (z <= 2.35e-54)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (z <= 4.2e+178)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.8e-109)
		tmp = k * (b * (z * y0));
	elseif (z <= 2.35e-54)
		tmp = a * (t * (y2 * y5));
	elseif (z <= 4.2e+178)
		tmp = i * (k * (y * y5));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.8e-109], N[(k * N[(b * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.35e-54], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.2e+178], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -1.8e-109

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 42.6%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 43.1%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 43.1%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 43.1%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 43.1%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 43.1%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 29.0%

      \[\leadsto k \cdot \color{blue}{\left(b \cdot \left(y0 \cdot z\right)\right)} \]

   if -1.8e-109 < z < 2.35e-54

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 40.6%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 40.6%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 40.6%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 40.6%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 29.4%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 28.4%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if 2.35e-54 < z < 4.1999999999999997e178

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 39.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in i around inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.9%

         \[\leadsto \color{blue}{-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 32.9%

         \[\leadsto -i \cdot \left(y5 \cdot \left(j \cdot t - \color{blue}{y \cdot k}\right)\right) \]

      3. distribute-rgt-neg-out 32.9%

         \[\leadsto \color{blue}{i \cdot \left(-y5 \cdot \left(j \cdot t - y \cdot k\right)\right)} \]

      4. *-commutative 32.9%

         \[\leadsto i \cdot \left(-\color{blue}{\left(j \cdot t - y \cdot k\right) \cdot y5}\right) \]

      5. distribute-rgt-neg-in 32.9%

         \[\leadsto i \cdot \color{blue}{\left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 32.9%

      \[\leadsto \color{blue}{i \cdot \left(\left(j \cdot t - y \cdot k\right) \cdot \left(-y5\right)\right)} \]

   9. Taylor expanded in j around 0 30.6%

      \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.6%

          \[\leadsto i \cdot \left(k \cdot \color{blue}{\left(y5 \cdot y\right)}\right) \]

   11. Simplified 30.6%

       \[\leadsto i \cdot \color{blue}{\left(k \cdot \left(y5 \cdot y\right)\right)} \]

   if 4.1999999999999997e178 < z

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 25.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 36.5%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 36.5%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 39.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 30.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.8 \cdot 10^{-109}:\\ \;\;\;\;k \cdot \left(b \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 2.35 \cdot 10^{-54}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 4.2 \cdot 10^{+178}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 43: 22.5% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.15 \cdot 10^{+100} \lor \neg \left(z \leq 2.8 \cdot 10^{+19}\right):\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= z -1.15e+100) (not (<= z 2.8e+19)))
   (* b (* k (* z y0)))
   (* a (* t (* y2 y5)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((z <= -1.15e+100) || !(z <= 2.8e+19)) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if ((z <= (-1.15d+100)) .or. (.not. (z <= 2.8d+19))) then
        tmp = b * (k * (z * y0))
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((z <= -1.15e+100) || !(z <= 2.8e+19)) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (z <= -1.15e+100) or not (z <= 2.8e+19):
		tmp = b * (k * (z * y0))
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if ((z <= -1.15e+100) || !(z <= 2.8e+19))
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if ((z <= -1.15e+100) || ~((z <= 2.8e+19)))
		tmp = b * (k * (z * y0));
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[Or[LessEqual[z, -1.15e+100], N[Not[LessEqual[z, 2.8e+19]], $MachinePrecision]], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if z < -1.14999999999999995e100 or 2.8e19 < z

   1. Initial program 24.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 40.9%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 39.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 39.2%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 39.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 39.2%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 39.2%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 34.5%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if -1.14999999999999995e100 < z < 2.8e19

   1. Initial program 38.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 37.9%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.9%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.9%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.9%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 27.1%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 22.0%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 26.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.15 \cdot 10^{+100} \lor \neg \left(z \leq 2.8 \cdot 10^{+19}\right):\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 44: 22.1% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -8 \cdot 10^{+27}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 215000000:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y0 -8e+27)
   (* c (* x (* y0 y2)))
   (if (<= y0 215000000.0) (* a (* y5 (* t y2))) (* b (* k (* z y0))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y0 <= -8e+27) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= 215000000.0) {
		tmp = a * (y5 * (t * y2));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y0 <= (-8d+27)) then
        tmp = c * (x * (y0 * y2))
    else if (y0 <= 215000000.0d0) then
        tmp = a * (y5 * (t * y2))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y0 <= -8e+27) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= 215000000.0) {
		tmp = a * (y5 * (t * y2));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y0 <= -8e+27:
		tmp = c * (x * (y0 * y2))
	elif y0 <= 215000000.0:
		tmp = a * (y5 * (t * y2))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y0 <= -8e+27)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y0 <= 215000000.0)
		tmp = Float64(a * Float64(y5 * Float64(t * y2)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y0 <= -8e+27)
		tmp = c * (x * (y0 * y2));
	elseif (y0 <= 215000000.0)
		tmp = a * (y5 * (t * y2));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y0, -8e+27], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 215000000.0], N[(a * N[(y5 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if y0 < -8.0000000000000001e27

   1. Initial program 13.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 24.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 35.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 34.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 34.1%

         \[\leadsto c \cdot \color{blue}{\left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   7. Simplified 34.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot y2\right) \cdot x\right)} \]

   if -8.0000000000000001e27 < y0 < 2.15e8

   1. Initial program 42.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around inf 42.0%

      \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 42.0%

         \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 42.0%

         \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 42.0%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in a around inf 29.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 21.4%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(t \cdot y2\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 21.4%

         \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   9. Simplified 21.4%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   if 2.15e8 < y0

   1. Initial program 31.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 35.3%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 48.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. distribute-lft-out-- 48.9%

         \[\leadsto k \cdot \left(y0 \cdot \color{blue}{\left(-1 \cdot \left(y2 \cdot y5 - b \cdot z\right)\right)}\right) \]

      2. *-commutative 48.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right)\right) \]

      3. *-commutative 48.9%

         \[\leadsto k \cdot \left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right)\right) \]

   6. Simplified 48.9%

      \[\leadsto k \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)\right)} \]

   7. Taylor expanded in y5 around 0 36.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 27.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -8 \cdot 10^{+27}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 215000000:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 45: 16.9% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* t (* y2 y5))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (t * (y2 * y5));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = a * (t * (y2 * y5))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (t * (y2 * y5));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (t * (y2 * y5))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(t * Float64(y2 * y5)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (t * (y2 * y5));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 33.1%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
2. Add Preprocessing

3. Taylor expanded in y5 around inf 37.5%

   \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
4. Step-by-step derivation

   1. mul-1-neg 37.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. *-commutative 37.5%

      \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

5. Simplified 37.5%

   \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

6. Taylor expanded in a around inf 27.3%

   \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

7. Taylor expanded in t around inf 18.0%

   \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

8. Final simplification 18.0%

   \[\leadsto a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right) \]
9. Add Preprocessing

Alternative 46: 17.2% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* y5 (* t y2))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (y5 * (t * y2));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = a * (y5 * (t * y2))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (y5 * (t * y2));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (y5 * (t * y2))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(y5 * Float64(t * y2)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (y5 * (t * y2));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(y5 * N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 33.1%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
2. Add Preprocessing

3. Taylor expanded in y5 around inf 37.5%

   \[\leadsto \left(\color{blue}{-1 \cdot \left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
4. Step-by-step derivation

   1. mul-1-neg 37.5%

      \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. *-commutative 37.5%

      \[\leadsto \left(\left(-i \cdot \left(y5 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

5. Simplified 37.5%

   \[\leadsto \left(\color{blue}{\left(-i \cdot \left(y5 \cdot \left(t \cdot j - k \cdot y\right)\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

6. Taylor expanded in a around inf 27.3%

   \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

7. Taylor expanded in t around inf 18.7%

   \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(t \cdot y2\right)}\right) \]
8. Step-by-step derivation

   1. *-commutative 18.7%

      \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

9. Simplified 18.7%

   \[\leadsto a \cdot \left(y5 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

10. Final simplification 18.7%

    \[\leadsto a \cdot \left(y5 \cdot \left(t \cdot y2\right)\right) \]
11. Add Preprocessing

Developer target: 27.7% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t_9\\ t_11 := t_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t_4 \cdot t_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t_3 \cdot t_1 - t_14\right)\right) + \left(t_8 - \left(t_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t_13\right)\right) + \left(t_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t_10 - \left(y \cdot x - z \cdot t\right) \cdot t_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t_8 - \left(t_11 - t_6\right)\right) - \left(\frac{t_3}{\frac{1}{t_1}} - t_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t_2 - \left(t_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t_5\right) - t_17 \cdot t_1\right) + t_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2024019 
(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
  :name "Linear.Matrix:det44 from linear-1.19.1.3"
  :precision binary64

  :herbie-target
  (if (< y4 -7.206256231996481e+60) (- (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))))) (- (/ (- (* y2 t) (* y3 y)) (/ 1.0 (- (* y4 c) (* y5 a)))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (if (< y4 -3.364603505246317e-66) (+ (- (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x))) (* (- (* b y0) (* i y1)) (- (* j x) (* k z)))) (- (* (- (* y0 c) (* a y1)) (- (* x y2) (* z y3))) (- (* (- (* t y2) (* y y3)) (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) (- (* k y2) (* j y3)))))) (if (< y4 -1.2000065055686116e-105) (+ (+ (- (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))) (* (* y3 y) (- (* y5 a) (* y4 c)))) (+ (* (* y5 a) (* t y2)) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))) (- (* (- (* b y0) (* i y1)) (- (* j x) (* k z))) (* (- (* y x) (* z t)) (- (* b a) (* i c)))))) (if (< y4 6.718963124057495e-279) (+ (- (- (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k))) (* (* y5 t) (* i j))) (- (* (- (* y2 t) (* y3 y)) (- (* y4 c) (* y5 a))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))) (if (< y4 4.77962681403792e-222) (+ (+ (- (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))) (* (* y3 y) (- (* y5 a) (* y4 c)))) (+ (* (* y5 a) (* t y2)) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))) (- (* (- (* b y0) (* i y1)) (- (* j x) (* k z))) (* (- (* y x) (* z t)) (- (* b a) (* i c)))))) (if (< y4 2.2852241541266835e-175) (+ (- (- (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k))) (* (* y5 t) (* i j))) (- (* (- (* y2 t) (* y3 y)) (- (* y4 c) (* y5 a))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))) (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (- (* k (* i (* z y1))) (+ (* j (* i (* x y1))) (* y0 (* k (* z b)))))) (- (* z (* y3 (* a y1))) (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3)))))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))))))))

  (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i)))) (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a)))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))