Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.9% → 40.0%

Time: 1.9min

Alternatives: 40

Speedup: 3.5×

• 89.2% 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: 30.9% 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: 40.0% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot t - x \cdot y\\ t_2 := y \cdot k - t \cdot j\\ t_3 := k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_4 := z \cdot k - x \cdot j\\ t_5 := x \cdot y2 - z \cdot y3\\ t_6 := t \cdot y2 - y \cdot y3\\ t_7 := c \cdot \left(\left(y0 \cdot t_5 + i \cdot t_1\right) - y4 \cdot t_6\right)\\ \mathbf{if}\;y0 \leq -8.5 \cdot 10^{+136}:\\ \;\;\;\;t_7\\ \mathbf{elif}\;y0 \leq -3.35 \cdot 10^{+100}:\\ \;\;\;\;y5 \cdot \left(a \cdot t_6 + \left(i \cdot t_2 - y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -3.4 \cdot 10^{+85}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq -5.8 \cdot 10^{-61}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y0 \leq -6.8 \cdot 10^{-97}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_6\right)\\ \mathbf{elif}\;y0 \leq -1.75 \cdot 10^{-224}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y0 \leq 6.2 \cdot 10^{-245}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot t_4\right)\\ \mathbf{elif}\;y0 \leq 3.1 \cdot 10^{-103}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot t_1 + y5 \cdot t_2\right)\right)\\ \mathbf{elif}\;y0 \leq 0.0018:\\ \;\;\;\;t_7\\ \mathbf{elif}\;y0 \leq 5 \cdot 10^{+24}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(c \cdot t_5 + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right) + b \cdot t_4\right)\\ \end{array} \end{array} \]

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 k) (* t j)))
        (t_3
         (*
          k
          (+
           (+ (* y2 (- (* y1 y4) (* y0 y5))) (* y (- (* i y5) (* b y4))))
           (* z (- (* b y0) (* i y1))))))
        (t_4 (- (* z k) (* x j)))
        (t_5 (- (* x y2) (* z y3)))
        (t_6 (- (* t y2) (* y y3)))
        (t_7 (* c (- (+ (* y0 t_5) (* i t_1)) (* y4 t_6)))))
   (if (<= y0 -8.5e+136)
     t_7
     (if (<= y0 -3.35e+100)
       (* y5 (+ (* a t_6) (- (* i t_2) (* y0 (- (* k y2) (* j y3))))))
       (if (<= y0 -3.4e+85)
         (* y0 (* x (- (* c y2) (* b j))))
         (if (<= y0 -5.8e-61)
           t_3
           (if (<= y0 -6.8e-97)
             (* a (* y5 t_6))
             (if (<= y0 -1.75e-224)
               t_3
               (if (<= y0 6.2e-245)
                 (*
                  b
                  (+
                   (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
                   (* y0 t_4)))
                 (if (<= y0 3.1e-103)
                   (*
                    i
                    (+ (* y1 (- (* x j) (* z k))) (+ (* c t_1) (* y5 t_2))))
                   (if (<= y0 0.0018)
                     t_7
                     (if (<= y0 5e+24)
                       (*
                        x
                        (+
                         (+
                          (* y (- (* a b) (* c i)))
                          (* y2 (- (* c y0) (* a y1))))
                         (* j (- (* i y1) (* b y0)))))
                       (*
                        y0
                        (+
                         (+ (* c t_5) (* y5 (- (* j y3) (* k y2))))
                         (* b t_4)))))))))))))))

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 * k) - (t * j);
	double t_3 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	double t_4 = (z * k) - (x * j);
	double t_5 = (x * y2) - (z * y3);
	double t_6 = (t * y2) - (y * y3);
	double t_7 = c * (((y0 * t_5) + (i * t_1)) - (y4 * t_6));
	double tmp;
	if (y0 <= -8.5e+136) {
		tmp = t_7;
	} else if (y0 <= -3.35e+100) {
		tmp = y5 * ((a * t_6) + ((i * t_2) - (y0 * ((k * y2) - (j * y3)))));
	} else if (y0 <= -3.4e+85) {
		tmp = y0 * (x * ((c * y2) - (b * j)));
	} else if (y0 <= -5.8e-61) {
		tmp = t_3;
	} else if (y0 <= -6.8e-97) {
		tmp = a * (y5 * t_6);
	} else if (y0 <= -1.75e-224) {
		tmp = t_3;
	} else if (y0 <= 6.2e-245) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_4));
	} else if (y0 <= 3.1e-103) {
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * t_2)));
	} else if (y0 <= 0.0018) {
		tmp = t_7;
	} else if (y0 <= 5e+24) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = y0 * (((c * t_5) + (y5 * ((j * y3) - (k * y2)))) + (b * t_4));
	}
	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 * k) - (t * j)
    t_3 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
    t_4 = (z * k) - (x * j)
    t_5 = (x * y2) - (z * y3)
    t_6 = (t * y2) - (y * y3)
    t_7 = c * (((y0 * t_5) + (i * t_1)) - (y4 * t_6))
    if (y0 <= (-8.5d+136)) then
        tmp = t_7
    else if (y0 <= (-3.35d+100)) then
        tmp = y5 * ((a * t_6) + ((i * t_2) - (y0 * ((k * y2) - (j * y3)))))
    else if (y0 <= (-3.4d+85)) then
        tmp = y0 * (x * ((c * y2) - (b * j)))
    else if (y0 <= (-5.8d-61)) then
        tmp = t_3
    else if (y0 <= (-6.8d-97)) then
        tmp = a * (y5 * t_6)
    else if (y0 <= (-1.75d-224)) then
        tmp = t_3
    else if (y0 <= 6.2d-245) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_4))
    else if (y0 <= 3.1d-103) then
        tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * t_2)))
    else if (y0 <= 0.0018d0) then
        tmp = t_7
    else if (y0 <= 5d+24) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
    else
        tmp = y0 * (((c * t_5) + (y5 * ((j * y3) - (k * y2)))) + (b * t_4))
    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 * k) - (t * j);
	double t_3 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	double t_4 = (z * k) - (x * j);
	double t_5 = (x * y2) - (z * y3);
	double t_6 = (t * y2) - (y * y3);
	double t_7 = c * (((y0 * t_5) + (i * t_1)) - (y4 * t_6));
	double tmp;
	if (y0 <= -8.5e+136) {
		tmp = t_7;
	} else if (y0 <= -3.35e+100) {
		tmp = y5 * ((a * t_6) + ((i * t_2) - (y0 * ((k * y2) - (j * y3)))));
	} else if (y0 <= -3.4e+85) {
		tmp = y0 * (x * ((c * y2) - (b * j)));
	} else if (y0 <= -5.8e-61) {
		tmp = t_3;
	} else if (y0 <= -6.8e-97) {
		tmp = a * (y5 * t_6);
	} else if (y0 <= -1.75e-224) {
		tmp = t_3;
	} else if (y0 <= 6.2e-245) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_4));
	} else if (y0 <= 3.1e-103) {
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * t_2)));
	} else if (y0 <= 0.0018) {
		tmp = t_7;
	} else if (y0 <= 5e+24) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = y0 * (((c * t_5) + (y5 * ((j * y3) - (k * y2)))) + (b * t_4));
	}
	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 * k) - (t * j)
	t_3 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
	t_4 = (z * k) - (x * j)
	t_5 = (x * y2) - (z * y3)
	t_6 = (t * y2) - (y * y3)
	t_7 = c * (((y0 * t_5) + (i * t_1)) - (y4 * t_6))
	tmp = 0
	if y0 <= -8.5e+136:
		tmp = t_7
	elif y0 <= -3.35e+100:
		tmp = y5 * ((a * t_6) + ((i * t_2) - (y0 * ((k * y2) - (j * y3)))))
	elif y0 <= -3.4e+85:
		tmp = y0 * (x * ((c * y2) - (b * j)))
	elif y0 <= -5.8e-61:
		tmp = t_3
	elif y0 <= -6.8e-97:
		tmp = a * (y5 * t_6)
	elif y0 <= -1.75e-224:
		tmp = t_3
	elif y0 <= 6.2e-245:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_4))
	elif y0 <= 3.1e-103:
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * t_2)))
	elif y0 <= 0.0018:
		tmp = t_7
	elif y0 <= 5e+24:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
	else:
		tmp = y0 * (((c * t_5) + (y5 * ((j * y3) - (k * y2)))) + (b * t_4))
	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 * k) - Float64(t * j))
	t_3 = Float64(k * Float64(Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_4 = Float64(Float64(z * k) - Float64(x * j))
	t_5 = Float64(Float64(x * y2) - Float64(z * y3))
	t_6 = Float64(Float64(t * y2) - Float64(y * y3))
	t_7 = Float64(c * Float64(Float64(Float64(y0 * t_5) + Float64(i * t_1)) - Float64(y4 * t_6)))
	tmp = 0.0
	if (y0 <= -8.5e+136)
		tmp = t_7;
	elseif (y0 <= -3.35e+100)
		tmp = Float64(y5 * Float64(Float64(a * t_6) + Float64(Float64(i * t_2) - Float64(y0 * Float64(Float64(k * y2) - Float64(j * y3))))));
	elseif (y0 <= -3.4e+85)
		tmp = Float64(y0 * Float64(x * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (y0 <= -5.8e-61)
		tmp = t_3;
	elseif (y0 <= -6.8e-97)
		tmp = Float64(a * Float64(y5 * t_6));
	elseif (y0 <= -1.75e-224)
		tmp = t_3;
	elseif (y0 <= 6.2e-245)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * t_4)));
	elseif (y0 <= 3.1e-103)
		tmp = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(c * t_1) + Float64(y5 * t_2))));
	elseif (y0 <= 0.0018)
		tmp = t_7;
	elseif (y0 <= 5e+24)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	else
		tmp = Float64(y0 * Float64(Float64(Float64(c * t_5) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))) + Float64(b * t_4)));
	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 * k) - (t * j);
	t_3 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	t_4 = (z * k) - (x * j);
	t_5 = (x * y2) - (z * y3);
	t_6 = (t * y2) - (y * y3);
	t_7 = c * (((y0 * t_5) + (i * t_1)) - (y4 * t_6));
	tmp = 0.0;
	if (y0 <= -8.5e+136)
		tmp = t_7;
	elseif (y0 <= -3.35e+100)
		tmp = y5 * ((a * t_6) + ((i * t_2) - (y0 * ((k * y2) - (j * y3)))));
	elseif (y0 <= -3.4e+85)
		tmp = y0 * (x * ((c * y2) - (b * j)));
	elseif (y0 <= -5.8e-61)
		tmp = t_3;
	elseif (y0 <= -6.8e-97)
		tmp = a * (y5 * t_6);
	elseif (y0 <= -1.75e-224)
		tmp = t_3;
	elseif (y0 <= 6.2e-245)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_4));
	elseif (y0 <= 3.1e-103)
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * t_2)));
	elseif (y0 <= 0.0018)
		tmp = t_7;
	elseif (y0 <= 5e+24)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	else
		tmp = y0 * (((c * t_5) + (y5 * ((j * y3) - (k * y2)))) + (b * t_4));
	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 * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(k * N[(N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(c * N[(N[(N[(y0 * t$95$5), $MachinePrecision] + N[(i * t$95$1), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -8.5e+136], t$95$7, If[LessEqual[y0, -3.35e+100], N[(y5 * N[(N[(a * t$95$6), $MachinePrecision] + N[(N[(i * t$95$2), $MachinePrecision] - N[(y0 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -3.4e+85], N[(y0 * N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -5.8e-61], t$95$3, If[LessEqual[y0, -6.8e-97], N[(a * N[(y5 * t$95$6), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -1.75e-224], t$95$3, If[LessEqual[y0, 6.2e-245], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3.1e-103], N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(c * t$95$1), $MachinePrecision] + N[(y5 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 0.0018], t$95$7, If[LessEqual[y0, 5e+24], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(N[(N[(c * t$95$5), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y0 < -8.49999999999999966e136 or 3.1000000000000001e-103 < y0 < 0.0018

   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. Taylor expanded in c around inf 61.8%

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

      1. +-commutative 61.8%

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

      2. mul-1-neg 61.8%

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

      3. unsub-neg 61.8%

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

      4. *-commutative 61.8%

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

      5. *-commutative 61.8%

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

      6. *-commutative 61.8%

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

      7. *-commutative 61.8%

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

   4. Simplified 61.8%

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

   if -8.49999999999999966e136 < y0 < -3.3499999999999998e100

   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. Taylor expanded in y5 around -inf 100.0%

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

   if -3.3499999999999998e100 < y0 < -3.4000000000000003e85

   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. Taylor expanded in y0 around inf 60.9%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 60.9%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 60.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 60.9%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 60.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 60.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 60.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 60.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 60.9%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in x around inf 92.2%

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

   if -3.4000000000000003e85 < y0 < -5.7999999999999999e-61 or -6.7999999999999998e-97 < y0 < -1.75000000000000009e-224

   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. Taylor expanded in k around inf 60.5%

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

      1. sub-neg 60.5%

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

      2. +-commutative 60.5%

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

      3. mul-1-neg 60.5%

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

      4. unsub-neg 60.5%

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

      5. *-commutative 60.5%

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

      6. mul-1-neg 60.5%

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

      7. remove-double-neg 60.5%

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

   4. Simplified 60.5%

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

   if -5.7999999999999999e-61 < y0 < -6.7999999999999998e-97

   1. Initial program 27.3%

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

   2. Taylor expanded in a around -inf 63.7%

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

      1. mul-1-neg 63.7%

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

      2. *-commutative 63.7%

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

      3. distribute-rgt-neg-in 63.7%

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

   4. Simplified 63.7%

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

   5. Taylor expanded in y5 around -inf 72.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 72.8%

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

      2. *-commutative 72.8%

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

   7. Simplified 72.8%

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

   if -1.75000000000000009e-224 < y0 < 6.20000000000000006e-245

   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. Taylor expanded in b around inf 50.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 6.20000000000000006e-245 < y0 < 3.1000000000000001e-103

   1. Initial program 34.6%

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

   2. Taylor expanded in i around -inf 65.6%

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

   if 0.0018 < y0 < 5.00000000000000045e24

   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. Taylor expanded in x around inf 80.5%

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

   if 5.00000000000000045e24 < y0

   1. Initial program 34.8%

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

   2. Taylor expanded in y0 around inf 60.5%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 60.5%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 60.5%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 60.5%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 60.5%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 60.5%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 60.5%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 60.5%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 60.5%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 62.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -8.5 \cdot 10^{+136}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -3.35 \cdot 10^{+100}:\\ \;\;\;\;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(k \cdot y2 - j \cdot y3\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -3.4 \cdot 10^{+85}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq -5.8 \cdot 10^{-61}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq -6.8 \cdot 10^{-97}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -1.75 \cdot 10^{-224}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 6.2 \cdot 10^{-245}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 3.1 \cdot 10^{-103}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 0.0018:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq 5 \cdot 10^{+24}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - z \cdot y3\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]

Alternative 2: 53.2% accurate, 0.5× speedup

Math

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

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t y2) (* y y3)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3
         (+
          (+
           (+
            (+
             (-
              (* (- (* a b) (* c i)) (- (* x y) (* z t)))
              (* (- (* b y0) (* i y1)) (- (* x j) (* z k))))
             (* (- (* c y0) (* a y1)) t_2))
            (* (- (* b y4) (* i y5)) (- (* t j) (* y k))))
           (* t_1 (- (* a y5) (* c y4))))
          (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5))))))
   (if (<= t_3 INFINITY)
     t_3
     (* c (- (+ (* y0 t_2) (* i (- (* z t) (* x y)))) (* y4 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 = (t * y2) - (y * y3);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (((c * y0) - (a * y1)) * t_2)) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_3 <= ((double) INFINITY)) {
		tmp = t_3;
	} else {
		tmp = c * (((y0 * t_2) + (i * ((z * t) - (x * y)))) - (y4 * t_1));
	}
	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 = (t * y2) - (y * y3);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (((c * y0) - (a * y1)) * t_2)) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_3 <= Double.POSITIVE_INFINITY) {
		tmp = t_3;
	} else {
		tmp = c * (((y0 * t_2) + (i * ((z * t) - (x * y)))) - (y4 * 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 = (t * y2) - (y * y3)
	t_2 = (x * y2) - (z * y3)
	t_3 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (((c * y0) - (a * y1)) * t_2)) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if t_3 <= math.inf:
		tmp = t_3
	else:
		tmp = c * (((y0 * t_2) + (i * ((z * t) - (x * y)))) - (y4 * 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(Float64(t * y2) - Float64(y * y3))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t))) - Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(Float64(x * j) - Float64(z * k)))) + Float64(Float64(Float64(c * y0) - Float64(a * y1)) * t_2)) + Float64(Float64(Float64(b * y4) - Float64(i * y5)) * Float64(Float64(t * j) - Float64(y * k)))) + Float64(t_1 * 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_3 <= Inf)
		tmp = t_3;
	else
		tmp = Float64(c * Float64(Float64(Float64(y0 * t_2) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * 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 = (t * y2) - (y * y3);
	t_2 = (x * y2) - (z * y3);
	t_3 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (((c * y0) - (a * y1)) * t_2)) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (t_3 <= Inf)
		tmp = t_3;
	else
		tmp = c * (((y0 * t_2) + (i * ((z * t) - (x * y)))) - (y4 * 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[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = 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[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision] * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * 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$3, Infinity], t$95$3, N[(c * N[(N[(N[(y0 * t$95$2), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$1), $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 90.3%

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

   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. Taylor expanded in c around inf 40.0%

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

      1. +-commutative 40.0%

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

      2. mul-1-neg 40.0%

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

      3. unsub-neg 40.0%

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

      4. *-commutative 40.0%

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

      5. *-commutative 40.0%

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

      6. *-commutative 40.0%

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

      7. *-commutative 40.0%

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

   4. Simplified 40.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 57.5%

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

Alternative 3: 39.6% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot y1 - b \cdot y0\\ t_2 := k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_3 := x \cdot y2 - z \cdot y3\\ t_4 := t \cdot y2 - y \cdot y3\\ t_5 := z \cdot k - x \cdot j\\ \mathbf{if}\;y0 \leq -2.4 \cdot 10^{+176}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot t_3 + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot t_4\right)\\ \mathbf{elif}\;y0 \leq -5 \cdot 10^{-62}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq -8 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_4\right)\\ \mathbf{elif}\;y0 \leq -2.05 \cdot 10^{-223}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq 1.16 \cdot 10^{-117}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot t_5\right)\\ \mathbf{elif}\;y0 \leq 3.55 \cdot 10^{-40}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq 1.16 \cdot 10^{-7}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot t_1\right)\\ \mathbf{elif}\;y0 \leq 1.6 \cdot 10^{+23}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot t_1\right)\\ \mathbf{elif}\;y0 \leq 1.25 \cdot 10^{+80}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq 6 \cdot 10^{+117}:\\ \;\;\;\;\left(y \cdot b - y1 \cdot y2\right) \cdot \left(x \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(c \cdot t_3 + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right) + b \cdot t_5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* i y1) (* b y0)))
        (t_2
         (*
          k
          (+
           (+ (* y2 (- (* y1 y4) (* y0 y5))) (* y (- (* i y5) (* b y4))))
           (* z (- (* b y0) (* i y1))))))
        (t_3 (- (* x y2) (* z y3)))
        (t_4 (- (* t y2) (* y y3)))
        (t_5 (- (* z k) (* x j))))
   (if (<= y0 -2.4e+176)
     (* c (- (+ (* y0 t_3) (* i (- (* z t) (* x y)))) (* y4 t_4)))
     (if (<= y0 -5e-62)
       t_2
       (if (<= y0 -8e-101)
         (* a (* y5 t_4))
         (if (<= y0 -2.05e-223)
           t_2
           (if (<= y0 1.16e-117)
             (*
              b
              (+
               (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
               (* y0 t_5)))
             (if (<= y0 3.55e-40)
               t_2
               (if (<= y0 1.16e-7)
                 (*
                  j
                  (+
                   (+
                    (* t (- (* b y4) (* i y5)))
                    (* y3 (- (* y0 y5) (* y1 y4))))
                   (* x t_1)))
                 (if (<= y0 1.6e+23)
                   (*
                    x
                    (+
                     (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1))))
                     (* j t_1)))
                   (if (<= y0 1.25e+80)
                     t_2
                     (if (<= y0 6e+117)
                       (* (- (* y b) (* y1 y2)) (* x a))
                       (*
                        y0
                        (+
                         (+ (* c t_3) (* y5 (- (* j y3) (* k y2))))
                         (* b 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 = (i * y1) - (b * y0);
	double t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	double t_3 = (x * y2) - (z * y3);
	double t_4 = (t * y2) - (y * y3);
	double t_5 = (z * k) - (x * j);
	double tmp;
	if (y0 <= -2.4e+176) {
		tmp = c * (((y0 * t_3) + (i * ((z * t) - (x * y)))) - (y4 * t_4));
	} else if (y0 <= -5e-62) {
		tmp = t_2;
	} else if (y0 <= -8e-101) {
		tmp = a * (y5 * t_4);
	} else if (y0 <= -2.05e-223) {
		tmp = t_2;
	} else if (y0 <= 1.16e-117) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_5));
	} else if (y0 <= 3.55e-40) {
		tmp = t_2;
	} else if (y0 <= 1.16e-7) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_1));
	} else if (y0 <= 1.6e+23) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * t_1));
	} else if (y0 <= 1.25e+80) {
		tmp = t_2;
	} else if (y0 <= 6e+117) {
		tmp = ((y * b) - (y1 * y2)) * (x * a);
	} else {
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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) :: tmp
    t_1 = (i * y1) - (b * y0)
    t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
    t_3 = (x * y2) - (z * y3)
    t_4 = (t * y2) - (y * y3)
    t_5 = (z * k) - (x * j)
    if (y0 <= (-2.4d+176)) then
        tmp = c * (((y0 * t_3) + (i * ((z * t) - (x * y)))) - (y4 * t_4))
    else if (y0 <= (-5d-62)) then
        tmp = t_2
    else if (y0 <= (-8d-101)) then
        tmp = a * (y5 * t_4)
    else if (y0 <= (-2.05d-223)) then
        tmp = t_2
    else if (y0 <= 1.16d-117) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_5))
    else if (y0 <= 3.55d-40) then
        tmp = t_2
    else if (y0 <= 1.16d-7) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_1))
    else if (y0 <= 1.6d+23) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * t_1))
    else if (y0 <= 1.25d+80) then
        tmp = t_2
    else if (y0 <= 6d+117) then
        tmp = ((y * b) - (y1 * y2)) * (x * a)
    else
        tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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 = (i * y1) - (b * y0);
	double t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	double t_3 = (x * y2) - (z * y3);
	double t_4 = (t * y2) - (y * y3);
	double t_5 = (z * k) - (x * j);
	double tmp;
	if (y0 <= -2.4e+176) {
		tmp = c * (((y0 * t_3) + (i * ((z * t) - (x * y)))) - (y4 * t_4));
	} else if (y0 <= -5e-62) {
		tmp = t_2;
	} else if (y0 <= -8e-101) {
		tmp = a * (y5 * t_4);
	} else if (y0 <= -2.05e-223) {
		tmp = t_2;
	} else if (y0 <= 1.16e-117) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_5));
	} else if (y0 <= 3.55e-40) {
		tmp = t_2;
	} else if (y0 <= 1.16e-7) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_1));
	} else if (y0 <= 1.6e+23) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * t_1));
	} else if (y0 <= 1.25e+80) {
		tmp = t_2;
	} else if (y0 <= 6e+117) {
		tmp = ((y * b) - (y1 * y2)) * (x * a);
	} else {
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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 = (i * y1) - (b * y0)
	t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
	t_3 = (x * y2) - (z * y3)
	t_4 = (t * y2) - (y * y3)
	t_5 = (z * k) - (x * j)
	tmp = 0
	if y0 <= -2.4e+176:
		tmp = c * (((y0 * t_3) + (i * ((z * t) - (x * y)))) - (y4 * t_4))
	elif y0 <= -5e-62:
		tmp = t_2
	elif y0 <= -8e-101:
		tmp = a * (y5 * t_4)
	elif y0 <= -2.05e-223:
		tmp = t_2
	elif y0 <= 1.16e-117:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_5))
	elif y0 <= 3.55e-40:
		tmp = t_2
	elif y0 <= 1.16e-7:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_1))
	elif y0 <= 1.6e+23:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * t_1))
	elif y0 <= 1.25e+80:
		tmp = t_2
	elif y0 <= 6e+117:
		tmp = ((y * b) - (y1 * y2)) * (x * a)
	else:
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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(i * y1) - Float64(b * y0))
	t_2 = Float64(k * Float64(Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_3 = Float64(Float64(x * y2) - Float64(z * y3))
	t_4 = Float64(Float64(t * y2) - Float64(y * y3))
	t_5 = Float64(Float64(z * k) - Float64(x * j))
	tmp = 0.0
	if (y0 <= -2.4e+176)
		tmp = Float64(c * Float64(Float64(Float64(y0 * t_3) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * t_4)));
	elseif (y0 <= -5e-62)
		tmp = t_2;
	elseif (y0 <= -8e-101)
		tmp = Float64(a * Float64(y5 * t_4));
	elseif (y0 <= -2.05e-223)
		tmp = t_2;
	elseif (y0 <= 1.16e-117)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * t_5)));
	elseif (y0 <= 3.55e-40)
		tmp = t_2;
	elseif (y0 <= 1.16e-7)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * t_1)));
	elseif (y0 <= 1.6e+23)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(j * t_1)));
	elseif (y0 <= 1.25e+80)
		tmp = t_2;
	elseif (y0 <= 6e+117)
		tmp = Float64(Float64(Float64(y * b) - Float64(y1 * y2)) * Float64(x * a));
	else
		tmp = Float64(y0 * Float64(Float64(Float64(c * t_3) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))) + Float64(b * 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 = (i * y1) - (b * y0);
	t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	t_3 = (x * y2) - (z * y3);
	t_4 = (t * y2) - (y * y3);
	t_5 = (z * k) - (x * j);
	tmp = 0.0;
	if (y0 <= -2.4e+176)
		tmp = c * (((y0 * t_3) + (i * ((z * t) - (x * y)))) - (y4 * t_4));
	elseif (y0 <= -5e-62)
		tmp = t_2;
	elseif (y0 <= -8e-101)
		tmp = a * (y5 * t_4);
	elseif (y0 <= -2.05e-223)
		tmp = t_2;
	elseif (y0 <= 1.16e-117)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_5));
	elseif (y0 <= 3.55e-40)
		tmp = t_2;
	elseif (y0 <= 1.16e-7)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_1));
	elseif (y0 <= 1.6e+23)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * t_1));
	elseif (y0 <= 1.25e+80)
		tmp = t_2;
	elseif (y0 <= 6e+117)
		tmp = ((y * b) - (y1 * y2)) * (x * a);
	else
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -2.4e+176], N[(c * N[(N[(N[(y0 * t$95$3), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -5e-62], t$95$2, If[LessEqual[y0, -8e-101], N[(a * N[(y5 * t$95$4), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -2.05e-223], t$95$2, If[LessEqual[y0, 1.16e-117], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3.55e-40], t$95$2, If[LessEqual[y0, 1.16e-7], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.6e+23], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.25e+80], t$95$2, If[LessEqual[y0, 6e+117], N[(N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision] * N[(x * a), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(N[(N[(c * t$95$3), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y0 < -2.4000000000000001e176

   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. Taylor expanded in c around inf 65.0%

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

      1. +-commutative 65.0%

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

      2. mul-1-neg 65.0%

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

      3. unsub-neg 65.0%

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

      4. *-commutative 65.0%

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

      5. *-commutative 65.0%

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

      6. *-commutative 65.0%

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

      7. *-commutative 65.0%

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

   4. Simplified 65.0%

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

   if -2.4000000000000001e176 < y0 < -5.0000000000000002e-62 or -8.00000000000000041e-101 < y0 < -2.05000000000000007e-223 or 1.15999999999999992e-117 < y0 < 3.55000000000000012e-40 or 1.6e23 < y0 < 1.2499999999999999e80

   1. Initial program 29.2%

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

   2. Taylor expanded in k around inf 63.3%

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

      1. sub-neg 63.3%

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

      2. +-commutative 63.3%

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

      3. mul-1-neg 63.3%

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

      4. unsub-neg 63.3%

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

      5. *-commutative 63.3%

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

      6. mul-1-neg 63.3%

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

      7. remove-double-neg 63.3%

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

   4. Simplified 63.3%

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

   if -5.0000000000000002e-62 < y0 < -8.00000000000000041e-101

   1. Initial program 30.8%

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

   2. Taylor expanded in a around -inf 69.3%

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

      1. mul-1-neg 69.3%

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

      2. *-commutative 69.3%

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

      3. distribute-rgt-neg-in 69.3%

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

   4. Simplified 69.3%

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

   5. Taylor expanded in y5 around -inf 69.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 69.6%

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

      2. *-commutative 69.6%

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

   7. Simplified 69.6%

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

   if -2.05000000000000007e-223 < y0 < 1.15999999999999992e-117

   1. Initial program 42.6%

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

   2. Taylor expanded in b around inf 49.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 3.55000000000000012e-40 < y0 < 1.1600000000000001e-7

   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. Taylor expanded in j around inf 57.0%

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

      1. +-commutative 57.0%

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

      2. mul-1-neg 57.0%

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

      3. unsub-neg 57.0%

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

      4. *-commutative 57.0%

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

   4. Simplified 57.0%

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

   if 1.1600000000000001e-7 < y0 < 1.6e23

   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. Taylor expanded in x around inf 80.5%

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

   if 1.2499999999999999e80 < y0 < 6e117

   1. Initial program 23.8%

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

   2. Taylor expanded in x around inf 44.6%

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

   3. Taylor expanded in a around inf 46.5%

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

      1. associate-*r* 46.6%

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

      2. +-commutative 46.6%

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

      3. mul-1-neg 46.6%

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

      4. unsub-neg 46.6%

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

      5. *-commutative 46.6%

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

   5. Simplified 46.6%

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

   if 6e117 < y0

   1. Initial program 35.1%

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

   2. Taylor expanded in y0 around inf 68.0%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 68.0%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 68.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 68.0%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 68.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 68.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 68.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 68.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 68.0%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 61.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -2.4 \cdot 10^{+176}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -5 \cdot 10^{-62}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq -8 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -2.05 \cdot 10^{-223}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 1.16 \cdot 10^{-117}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 3.55 \cdot 10^{-40}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 1.16 \cdot 10^{-7}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 1.6 \cdot 10^{+23}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 1.25 \cdot 10^{+80}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 6 \cdot 10^{+117}:\\ \;\;\;\;\left(y \cdot b - y1 \cdot y2\right) \cdot \left(x \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - z \cdot y3\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]

Alternative 4: 39.8% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{if}\;c \leq -1.02 \cdot 10^{+83}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -1.08 \cdot 10^{+39}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;c \leq -1 \cdot 10^{-21}:\\ \;\;\;\;t \cdot \left(j \cdot \left(b \cdot y4 - i \cdot y5\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -1.25 \cdot 10^{-146}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq -5.7 \cdot 10^{-238}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;c \leq -2.6 \cdot 10^{-257}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq -4.4 \cdot 10^{-286}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;c \leq 6.2 \cdot 10^{-114}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 2.45 \cdot 10^{-84}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          c
          (-
           (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
           (* y4 (- (* t y2) (* y y3)))))))
   (if (<= c -1.02e+83)
     t_1
     (if (<= c -1.08e+39)
       (* (* b j) (- (* t y4) (* x y0)))
       (if (<= c -1e-21)
         (* t (+ (* j (- (* b y4) (* i y5))) (* y2 (- (* a y5) (* c y4)))))
         (if (<= c -1.25e-146)
           (* a (* y3 (- (* z y1) (* y y5))))
           (if (<= c -5.7e-238)
             (* y0 (* b (- (* z k) (* x j))))
             (if (<= c -2.6e-257)
               (* b (* x (- (* y a) (* j y0))))
               (if (<= c -4.4e-286)
                 (* j (* y0 (- (* y3 y5) (* x b))))
                 (if (<= c 6.2e-114)
                   (*
                    k
                    (+
                     (+
                      (* y2 (- (* y1 y4) (* y0 y5)))
                      (* y (- (* i y5) (* b y4))))
                     (* z (- (* b y0) (* i y1)))))
                   (if (<= c 2.45e-84)
                     (* a (* y (- (* x b) (* y3 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 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * ((t * y2) - (y * y3))));
	double tmp;
	if (c <= -1.02e+83) {
		tmp = t_1;
	} else if (c <= -1.08e+39) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (c <= -1e-21) {
		tmp = t * ((j * ((b * y4) - (i * y5))) + (y2 * ((a * y5) - (c * y4))));
	} else if (c <= -1.25e-146) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (c <= -5.7e-238) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else if (c <= -2.6e-257) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (c <= -4.4e-286) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (c <= 6.2e-114) {
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	} else if (c <= 2.45e-84) {
		tmp = a * (y * ((x * b) - (y3 * 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 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * ((t * y2) - (y * y3))))
    if (c <= (-1.02d+83)) then
        tmp = t_1
    else if (c <= (-1.08d+39)) then
        tmp = (b * j) * ((t * y4) - (x * y0))
    else if (c <= (-1d-21)) then
        tmp = t * ((j * ((b * y4) - (i * y5))) + (y2 * ((a * y5) - (c * y4))))
    else if (c <= (-1.25d-146)) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (c <= (-5.7d-238)) then
        tmp = y0 * (b * ((z * k) - (x * j)))
    else if (c <= (-2.6d-257)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (c <= (-4.4d-286)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (c <= 6.2d-114) then
        tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
    else if (c <= 2.45d-84) then
        tmp = a * (y * ((x * b) - (y3 * 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 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * ((t * y2) - (y * y3))));
	double tmp;
	if (c <= -1.02e+83) {
		tmp = t_1;
	} else if (c <= -1.08e+39) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (c <= -1e-21) {
		tmp = t * ((j * ((b * y4) - (i * y5))) + (y2 * ((a * y5) - (c * y4))));
	} else if (c <= -1.25e-146) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (c <= -5.7e-238) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else if (c <= -2.6e-257) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (c <= -4.4e-286) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (c <= 6.2e-114) {
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	} else if (c <= 2.45e-84) {
		tmp = a * (y * ((x * b) - (y3 * 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 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * ((t * y2) - (y * y3))))
	tmp = 0
	if c <= -1.02e+83:
		tmp = t_1
	elif c <= -1.08e+39:
		tmp = (b * j) * ((t * y4) - (x * y0))
	elif c <= -1e-21:
		tmp = t * ((j * ((b * y4) - (i * y5))) + (y2 * ((a * y5) - (c * y4))))
	elif c <= -1.25e-146:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif c <= -5.7e-238:
		tmp = y0 * (b * ((z * k) - (x * j)))
	elif c <= -2.6e-257:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif c <= -4.4e-286:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif c <= 6.2e-114:
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
	elif c <= 2.45e-84:
		tmp = a * (y * ((x * b) - (y3 * 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(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * Float64(Float64(t * y2) - Float64(y * y3)))))
	tmp = 0.0
	if (c <= -1.02e+83)
		tmp = t_1;
	elseif (c <= -1.08e+39)
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	elseif (c <= -1e-21)
		tmp = Float64(t * Float64(Float64(j * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (c <= -1.25e-146)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (c <= -5.7e-238)
		tmp = Float64(y0 * Float64(b * Float64(Float64(z * k) - Float64(x * j))));
	elseif (c <= -2.6e-257)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (c <= -4.4e-286)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (c <= 6.2e-114)
		tmp = Float64(k * Float64(Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))));
	elseif (c <= 2.45e-84)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * 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 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * ((t * y2) - (y * y3))));
	tmp = 0.0;
	if (c <= -1.02e+83)
		tmp = t_1;
	elseif (c <= -1.08e+39)
		tmp = (b * j) * ((t * y4) - (x * y0));
	elseif (c <= -1e-21)
		tmp = t * ((j * ((b * y4) - (i * y5))) + (y2 * ((a * y5) - (c * y4))));
	elseif (c <= -1.25e-146)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (c <= -5.7e-238)
		tmp = y0 * (b * ((z * k) - (x * j)));
	elseif (c <= -2.6e-257)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (c <= -4.4e-286)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (c <= 6.2e-114)
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	elseif (c <= 2.45e-84)
		tmp = a * (y * ((x * b) - (y3 * 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[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.02e+83], t$95$1, If[LessEqual[c, -1.08e+39], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1e-21], N[(t * N[(N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.25e-146], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -5.7e-238], N[(y0 * N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2.6e-257], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -4.4e-286], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 6.2e-114], N[(k * N[(N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.45e-84], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if c < -1.0200000000000001e83 or 2.4499999999999999e-84 < c

   1. Initial program 30.5%

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

   2. Taylor expanded in c around inf 60.4%

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

      1. +-commutative 60.4%

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

      2. mul-1-neg 60.4%

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

      3. unsub-neg 60.4%

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

      4. *-commutative 60.4%

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

      5. *-commutative 60.4%

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

      6. *-commutative 60.4%

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

      7. *-commutative 60.4%

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

   4. Simplified 60.4%

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

   if -1.0200000000000001e83 < c < -1.07999999999999998e39

   1. Initial program 12.5%

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

   2. Taylor expanded in b around inf 25.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in j around inf 75.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 75.7%

         \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)} \]

      2. *-commutative 75.7%

         \[\leadsto \left(b \cdot j\right) \cdot \left(t \cdot y4 - \color{blue}{y0 \cdot x}\right) \]

   5. Simplified 75.7%

      \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - y0 \cdot x\right)} \]

   if -1.07999999999999998e39 < c < -9.99999999999999908e-22

   1. Initial program 17.2%

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

   2. Taylor expanded in t around inf 34.0%

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

   3. Taylor expanded in z around 0 50.7%

      \[\leadsto \color{blue}{t \cdot \left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 50.7%

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

   5. Simplified 50.7%

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

   if -9.99999999999999908e-22 < c < -1.24999999999999989e-146

   1. Initial program 48.9%

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

   2. Taylor expanded in a around -inf 52.2%

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

      1. mul-1-neg 52.2%

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

      2. *-commutative 52.2%

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

      3. distribute-rgt-neg-in 52.2%

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

   4. Simplified 52.2%

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

   5. Taylor expanded in y3 around -inf 49.9%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if -1.24999999999999989e-146 < c < -5.70000000000000022e-238

   1. Initial program 23.8%

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

   2. Taylor expanded in y0 around inf 54.0%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 54.0%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 54.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 54.0%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 54.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 54.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 54.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 54.0%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 54.0%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in b around inf 53.6%

      \[\leadsto y0 \cdot \color{blue}{\left(b \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 53.6%

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

      2. *-commutative 53.6%

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

   7. Simplified 53.6%

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

   if -5.70000000000000022e-238 < c < -2.6000000000000001e-257

   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. Taylor expanded in b around inf 42.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 71.9%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 71.9%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 71.9%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 71.9%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -2.6000000000000001e-257 < c < -4.3999999999999998e-286

   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. Taylor expanded in j around inf 34.7%

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

      1. +-commutative 34.7%

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

      2. mul-1-neg 34.7%

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

      3. unsub-neg 34.7%

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

      4. *-commutative 34.7%

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

   4. Simplified 34.7%

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

   5. Taylor expanded in y0 around -inf 80.1%

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

      1. +-commutative 80.1%

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

      2. mul-1-neg 80.1%

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

      3. *-commutative 80.1%

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

      4. unsub-neg 80.1%

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

   7. Simplified 80.1%

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

   if -4.3999999999999998e-286 < c < 6.2e-114

   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. Taylor expanded in k around inf 57.7%

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

      1. sub-neg 57.7%

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

      2. +-commutative 57.7%

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

      3. mul-1-neg 57.7%

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

      4. unsub-neg 57.7%

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

      5. *-commutative 57.7%

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

      6. mul-1-neg 57.7%

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

      7. remove-double-neg 57.7%

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

   4. Simplified 57.7%

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

   if 6.2e-114 < c < 2.4499999999999999e-84

   1. Initial program 10.8%

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

   2. Taylor expanded in a around -inf 70.1%

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

      1. mul-1-neg 70.1%

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

      2. *-commutative 70.1%

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

      3. distribute-rgt-neg-in 70.1%

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

   4. Simplified 70.1%

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

   5. Taylor expanded in y around inf 70.4%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 70.4%

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

      2. mul-1-neg 70.4%

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

      3. unsub-neg 70.4%

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

      4. *-commutative 70.4%

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

   7. Simplified 70.4%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 59.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1.02 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq -1.08 \cdot 10^{+39}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;c \leq -1 \cdot 10^{-21}:\\ \;\;\;\;t \cdot \left(j \cdot \left(b \cdot y4 - i \cdot y5\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -1.25 \cdot 10^{-146}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq -5.7 \cdot 10^{-238}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;c \leq -2.6 \cdot 10^{-257}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq -4.4 \cdot 10^{-286}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;c \leq 6.2 \cdot 10^{-114}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 2.45 \cdot 10^{-84}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \]

Alternative 5: 43.5% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y2 - z \cdot y3\\ t_2 := t \cdot y2 - y \cdot y3\\ t_3 := c \cdot \left(\left(y0 \cdot t_1 + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot t_2\right)\\ t_4 := k \cdot y2 - j \cdot y3\\ \mathbf{if}\;c \leq -1.15 \cdot 10^{+87}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq -3.5 \cdot 10^{+38}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;c \leq -7.6 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq -8 \cdot 10^{-175}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot t_4 - a \cdot t_1\right)\right)\\ \mathbf{elif}\;c \leq 5 \cdot 10^{-159}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 3 \cdot 10^{+14}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_2 + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;c \leq 7.2 \cdot 10^{+74}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot t_4\right) - c \cdot t_2\right)\\ \mathbf{elif}\;c \leq 7.6 \cdot 10^{+74}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y2) (* z y3)))
        (t_2 (- (* t y2) (* y y3)))
        (t_3 (* c (- (+ (* y0 t_1) (* i (- (* z t) (* x y)))) (* y4 t_2))))
        (t_4 (- (* k y2) (* j y3))))
   (if (<= c -1.15e+87)
     t_3
     (if (<= c -3.5e+38)
       (* (* b j) (- (* t y4) (* x y0)))
       (if (<= c -7.6e+29)
         (* c (* y4 (- (* y y3) (* t y2))))
         (if (<= c -8e-175)
           (* y1 (+ (* i (- (* x j) (* z k))) (- (* y4 t_4) (* a t_1))))
           (if (<= c 5e-159)
             (*
              k
              (+
               (+ (* y2 (- (* y1 y4) (* y0 y5))) (* y (- (* i y5) (* b y4))))
               (* z (- (* b y0) (* i y1)))))
             (if (<= c 3e+14)
               (*
                a
                (+
                 (* y5 t_2)
                 (+ (* b (- (* x y) (* z t))) (* y1 (- (* z y3) (* x y2))))))
               (if (<= c 7.2e+74)
                 (* y4 (- (+ (* b (- (* t j) (* y k))) (* y1 t_4)) (* c t_2)))
                 (if (<= c 7.6e+74) (* a (* y5 (* y3 (- y)))) 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 = (x * y2) - (z * y3);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	double t_4 = (k * y2) - (j * y3);
	double tmp;
	if (c <= -1.15e+87) {
		tmp = t_3;
	} else if (c <= -3.5e+38) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (c <= -7.6e+29) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= -8e-175) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)));
	} else if (c <= 5e-159) {
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	} else if (c <= 3e+14) {
		tmp = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))));
	} else if (c <= 7.2e+74) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2));
	} else if (c <= 7.6e+74) {
		tmp = a * (y5 * (y3 * -y));
	} 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) :: tmp
    t_1 = (x * y2) - (z * y3)
    t_2 = (t * y2) - (y * y3)
    t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2))
    t_4 = (k * y2) - (j * y3)
    if (c <= (-1.15d+87)) then
        tmp = t_3
    else if (c <= (-3.5d+38)) then
        tmp = (b * j) * ((t * y4) - (x * y0))
    else if (c <= (-7.6d+29)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= (-8d-175)) then
        tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)))
    else if (c <= 5d-159) then
        tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
    else if (c <= 3d+14) then
        tmp = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))))
    else if (c <= 7.2d+74) then
        tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2))
    else if (c <= 7.6d+74) then
        tmp = a * (y5 * (y3 * -y))
    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 = (x * y2) - (z * y3);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	double t_4 = (k * y2) - (j * y3);
	double tmp;
	if (c <= -1.15e+87) {
		tmp = t_3;
	} else if (c <= -3.5e+38) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (c <= -7.6e+29) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= -8e-175) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)));
	} else if (c <= 5e-159) {
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	} else if (c <= 3e+14) {
		tmp = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))));
	} else if (c <= 7.2e+74) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2));
	} else if (c <= 7.6e+74) {
		tmp = a * (y5 * (y3 * -y));
	} 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 = (x * y2) - (z * y3)
	t_2 = (t * y2) - (y * y3)
	t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2))
	t_4 = (k * y2) - (j * y3)
	tmp = 0
	if c <= -1.15e+87:
		tmp = t_3
	elif c <= -3.5e+38:
		tmp = (b * j) * ((t * y4) - (x * y0))
	elif c <= -7.6e+29:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= -8e-175:
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)))
	elif c <= 5e-159:
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
	elif c <= 3e+14:
		tmp = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))))
	elif c <= 7.2e+74:
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2))
	elif c <= 7.6e+74:
		tmp = a * (y5 * (y3 * -y))
	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(x * y2) - Float64(z * y3))
	t_2 = Float64(Float64(t * y2) - Float64(y * y3))
	t_3 = Float64(c * Float64(Float64(Float64(y0 * t_1) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * t_2)))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	tmp = 0.0
	if (c <= -1.15e+87)
		tmp = t_3;
	elseif (c <= -3.5e+38)
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	elseif (c <= -7.6e+29)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= -8e-175)
		tmp = Float64(y1 * Float64(Float64(i * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(y4 * t_4) - Float64(a * t_1))));
	elseif (c <= 5e-159)
		tmp = Float64(k * Float64(Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))));
	elseif (c <= 3e+14)
		tmp = Float64(a * Float64(Float64(y5 * t_2) + Float64(Float64(b * Float64(Float64(x * y) - Float64(z * t))) + Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))));
	elseif (c <= 7.2e+74)
		tmp = Float64(y4 * Float64(Float64(Float64(b * Float64(Float64(t * j) - Float64(y * k))) + Float64(y1 * t_4)) - Float64(c * t_2)));
	elseif (c <= 7.6e+74)
		tmp = Float64(a * Float64(y5 * Float64(y3 * Float64(-y))));
	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 = (x * y2) - (z * y3);
	t_2 = (t * y2) - (y * y3);
	t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	t_4 = (k * y2) - (j * y3);
	tmp = 0.0;
	if (c <= -1.15e+87)
		tmp = t_3;
	elseif (c <= -3.5e+38)
		tmp = (b * j) * ((t * y4) - (x * y0));
	elseif (c <= -7.6e+29)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= -8e-175)
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)));
	elseif (c <= 5e-159)
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	elseif (c <= 3e+14)
		tmp = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))));
	elseif (c <= 7.2e+74)
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2));
	elseif (c <= 7.6e+74)
		tmp = a * (y5 * (y3 * -y));
	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[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(N[(N[(y0 * t$95$1), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.15e+87], t$95$3, If[LessEqual[c, -3.5e+38], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -7.6e+29], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -8e-175], N[(y1 * N[(N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y4 * t$95$4), $MachinePrecision] - N[(a * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5e-159], N[(k * N[(N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3e+14], N[(a * N[(N[(y5 * t$95$2), $MachinePrecision] + N[(N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 7.2e+74], 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[c, 7.6e+74], N[(a * N[(y5 * N[(y3 * (-y)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if c < -1.1500000000000001e87 or 7.5999999999999997e74 < c

   1. Initial program 25.3%

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

   2. Taylor expanded in c around inf 68.2%

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

      1. +-commutative 68.2%

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

      2. mul-1-neg 68.2%

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

      3. unsub-neg 68.2%

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

      4. *-commutative 68.2%

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

      5. *-commutative 68.2%

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

      6. *-commutative 68.2%

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

      7. *-commutative 68.2%

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

   4. Simplified 68.2%

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

   if -1.1500000000000001e87 < c < -3.50000000000000002e38

   1. Initial program 12.5%

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

   2. Taylor expanded in b around inf 25.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in j around inf 75.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 75.7%

         \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)} \]

      2. *-commutative 75.7%

         \[\leadsto \left(b \cdot j\right) \cdot \left(t \cdot y4 - \color{blue}{y0 \cdot x}\right) \]

   5. Simplified 75.7%

      \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - y0 \cdot x\right)} \]

   if -3.50000000000000002e38 < c < -7.59999999999999942e29

   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. Taylor expanded in c around inf 68.7%

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

      1. +-commutative 68.7%

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

      2. mul-1-neg 68.7%

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

      3. unsub-neg 68.7%

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

      4. *-commutative 68.7%

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

      5. *-commutative 68.7%

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

      6. *-commutative 68.7%

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

      7. *-commutative 68.7%

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

   4. Simplified 68.7%

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

   5. Taylor expanded in y4 around inf 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

   7. Simplified 100.0%

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

   if -7.59999999999999942e29 < c < -8e-175

   1. Initial program 39.6%

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

   2. Taylor expanded in y1 around -inf 50.7%

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

      1. mul-1-neg 50.7%

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

      2. distribute-rgt-neg-in 50.7%

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

      3. +-commutative 50.7%

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

      4. mul-1-neg 50.7%

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

      5. unsub-neg 50.7%

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

      6. *-commutative 50.7%

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

      7. *-commutative 50.7%

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

      8. *-commutative 50.7%

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

   4. Simplified 50.7%

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

   if -8e-175 < c < 5.00000000000000032e-159

   1. Initial program 32.7%

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

   2. Taylor expanded in k around inf 55.0%

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

      1. sub-neg 55.0%

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

      2. +-commutative 55.0%

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

      3. mul-1-neg 55.0%

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

      4. unsub-neg 55.0%

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

      5. *-commutative 55.0%

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

      6. mul-1-neg 55.0%

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

      7. remove-double-neg 55.0%

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

   4. Simplified 55.0%

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

   if 5.00000000000000032e-159 < c < 3e14

   1. Initial program 35.2%

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

   2. Taylor expanded in a around -inf 61.3%

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

      1. mul-1-neg 61.3%

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

      2. *-commutative 61.3%

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

      3. distribute-rgt-neg-in 61.3%

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

   4. Simplified 61.3%

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

   if 3e14 < c < 7.19999999999999975e74

   1. Initial program 55.4%

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

   2. Taylor expanded in y4 around inf 88.7%

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

   if 7.19999999999999975e74 < c < 7.5999999999999997e74

   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. Taylor expanded in a around -inf 100.0%

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

      1. mul-1-neg 100.0%

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

      2. *-commutative 100.0%

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

      3. distribute-rgt-neg-in 100.0%

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

   4. Simplified 100.0%

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

   5. Taylor expanded in y around inf 6.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 6.6%

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

      2. mul-1-neg 6.6%

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

      3. unsub-neg 6.6%

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

      4. *-commutative 6.6%

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

   7. Simplified 6.6%

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

   8. Taylor expanded in x around 0 6.6%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 6.6%

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

      2. associate-*r* 100.0%

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

   10. Simplified 100.0%

       \[\leadsto a \cdot \color{blue}{\left(-\left(y \cdot y3\right) \cdot y5\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 62.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1.15 \cdot 10^{+87}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq -3.5 \cdot 10^{+38}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;c \leq -7.6 \cdot 10^{+29}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq -8 \cdot 10^{-175}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;c \leq 5 \cdot 10^{-159}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 3 \cdot 10^{+14}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;c \leq 7.2 \cdot 10^{+74}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 7.6 \cdot 10^{+74}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \]

Alternative 6: 40.2% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot t - x \cdot y\\ t_2 := k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_3 := x \cdot y2 - z \cdot y3\\ t_4 := t \cdot y2 - y \cdot y3\\ t_5 := c \cdot \left(\left(y0 \cdot t_3 + i \cdot t_1\right) - y4 \cdot t_4\right)\\ t_6 := z \cdot k - x \cdot j\\ \mathbf{if}\;y0 \leq -2.9 \cdot 10^{+176}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;y0 \leq -7.2 \cdot 10^{-63}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq -2.1 \cdot 10^{-95}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_4\right)\\ \mathbf{elif}\;y0 \leq -1.85 \cdot 10^{-224}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq 2.6 \cdot 10^{-247}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot t_6\right)\\ \mathbf{elif}\;y0 \leq 8 \cdot 10^{-104}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot t_1 + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 2.2 \cdot 10^{-6}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;y0 \leq 1.05 \cdot 10^{+28}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(c \cdot t_3 + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right) + b \cdot t_6\right)\\ \end{array} \end{array} \]

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
         (*
          k
          (+
           (+ (* y2 (- (* y1 y4) (* y0 y5))) (* y (- (* i y5) (* b y4))))
           (* z (- (* b y0) (* i y1))))))
        (t_3 (- (* x y2) (* z y3)))
        (t_4 (- (* t y2) (* y y3)))
        (t_5 (* c (- (+ (* y0 t_3) (* i t_1)) (* y4 t_4))))
        (t_6 (- (* z k) (* x j))))
   (if (<= y0 -2.9e+176)
     t_5
     (if (<= y0 -7.2e-63)
       t_2
       (if (<= y0 -2.1e-95)
         (* a (* y5 t_4))
         (if (<= y0 -1.85e-224)
           t_2
           (if (<= y0 2.6e-247)
             (*
              b
              (+
               (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
               (* y0 t_6)))
             (if (<= y0 8e-104)
               (*
                i
                (+
                 (* y1 (- (* x j) (* z k)))
                 (+ (* c t_1) (* y5 (- (* y k) (* t j))))))
               (if (<= y0 2.2e-6)
                 t_5
                 (if (<= y0 1.05e+28)
                   (*
                    x
                    (+
                     (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1))))
                     (* j (- (* i y1) (* b y0)))))
                   (*
                    y0
                    (+
                     (+ (* c t_3) (* y5 (- (* j y3) (* k y2))))
                     (* b 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 = (z * t) - (x * y);
	double t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	double t_3 = (x * y2) - (z * y3);
	double t_4 = (t * y2) - (y * y3);
	double t_5 = c * (((y0 * t_3) + (i * t_1)) - (y4 * t_4));
	double t_6 = (z * k) - (x * j);
	double tmp;
	if (y0 <= -2.9e+176) {
		tmp = t_5;
	} else if (y0 <= -7.2e-63) {
		tmp = t_2;
	} else if (y0 <= -2.1e-95) {
		tmp = a * (y5 * t_4);
	} else if (y0 <= -1.85e-224) {
		tmp = t_2;
	} else if (y0 <= 2.6e-247) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_6));
	} else if (y0 <= 8e-104) {
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * ((y * k) - (t * j)))));
	} else if (y0 <= 2.2e-6) {
		tmp = t_5;
	} else if (y0 <= 1.05e+28) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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) :: tmp
    t_1 = (z * t) - (x * y)
    t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
    t_3 = (x * y2) - (z * y3)
    t_4 = (t * y2) - (y * y3)
    t_5 = c * (((y0 * t_3) + (i * t_1)) - (y4 * t_4))
    t_6 = (z * k) - (x * j)
    if (y0 <= (-2.9d+176)) then
        tmp = t_5
    else if (y0 <= (-7.2d-63)) then
        tmp = t_2
    else if (y0 <= (-2.1d-95)) then
        tmp = a * (y5 * t_4)
    else if (y0 <= (-1.85d-224)) then
        tmp = t_2
    else if (y0 <= 2.6d-247) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_6))
    else if (y0 <= 8d-104) then
        tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * ((y * k) - (t * j)))))
    else if (y0 <= 2.2d-6) then
        tmp = t_5
    else if (y0 <= 1.05d+28) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
    else
        tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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 = (z * t) - (x * y);
	double t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	double t_3 = (x * y2) - (z * y3);
	double t_4 = (t * y2) - (y * y3);
	double t_5 = c * (((y0 * t_3) + (i * t_1)) - (y4 * t_4));
	double t_6 = (z * k) - (x * j);
	double tmp;
	if (y0 <= -2.9e+176) {
		tmp = t_5;
	} else if (y0 <= -7.2e-63) {
		tmp = t_2;
	} else if (y0 <= -2.1e-95) {
		tmp = a * (y5 * t_4);
	} else if (y0 <= -1.85e-224) {
		tmp = t_2;
	} else if (y0 <= 2.6e-247) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_6));
	} else if (y0 <= 8e-104) {
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * ((y * k) - (t * j)))));
	} else if (y0 <= 2.2e-6) {
		tmp = t_5;
	} else if (y0 <= 1.05e+28) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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 = (z * t) - (x * y)
	t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
	t_3 = (x * y2) - (z * y3)
	t_4 = (t * y2) - (y * y3)
	t_5 = c * (((y0 * t_3) + (i * t_1)) - (y4 * t_4))
	t_6 = (z * k) - (x * j)
	tmp = 0
	if y0 <= -2.9e+176:
		tmp = t_5
	elif y0 <= -7.2e-63:
		tmp = t_2
	elif y0 <= -2.1e-95:
		tmp = a * (y5 * t_4)
	elif y0 <= -1.85e-224:
		tmp = t_2
	elif y0 <= 2.6e-247:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_6))
	elif y0 <= 8e-104:
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * ((y * k) - (t * j)))))
	elif y0 <= 2.2e-6:
		tmp = t_5
	elif y0 <= 1.05e+28:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
	else:
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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(z * t) - Float64(x * y))
	t_2 = Float64(k * Float64(Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_3 = Float64(Float64(x * y2) - Float64(z * y3))
	t_4 = Float64(Float64(t * y2) - Float64(y * y3))
	t_5 = Float64(c * Float64(Float64(Float64(y0 * t_3) + Float64(i * t_1)) - Float64(y4 * t_4)))
	t_6 = Float64(Float64(z * k) - Float64(x * j))
	tmp = 0.0
	if (y0 <= -2.9e+176)
		tmp = t_5;
	elseif (y0 <= -7.2e-63)
		tmp = t_2;
	elseif (y0 <= -2.1e-95)
		tmp = Float64(a * Float64(y5 * t_4));
	elseif (y0 <= -1.85e-224)
		tmp = t_2;
	elseif (y0 <= 2.6e-247)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * t_6)));
	elseif (y0 <= 8e-104)
		tmp = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(c * t_1) + Float64(y5 * Float64(Float64(y * k) - Float64(t * j))))));
	elseif (y0 <= 2.2e-6)
		tmp = t_5;
	elseif (y0 <= 1.05e+28)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	else
		tmp = Float64(y0 * Float64(Float64(Float64(c * t_3) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))) + Float64(b * 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 = (z * t) - (x * y);
	t_2 = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	t_3 = (x * y2) - (z * y3);
	t_4 = (t * y2) - (y * y3);
	t_5 = c * (((y0 * t_3) + (i * t_1)) - (y4 * t_4));
	t_6 = (z * k) - (x * j);
	tmp = 0.0;
	if (y0 <= -2.9e+176)
		tmp = t_5;
	elseif (y0 <= -7.2e-63)
		tmp = t_2;
	elseif (y0 <= -2.1e-95)
		tmp = a * (y5 * t_4);
	elseif (y0 <= -1.85e-224)
		tmp = t_2;
	elseif (y0 <= 2.6e-247)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_6));
	elseif (y0 <= 8e-104)
		tmp = i * ((y1 * ((x * j) - (z * k))) + ((c * t_1) + (y5 * ((y * k) - (t * j)))));
	elseif (y0 <= 2.2e-6)
		tmp = t_5;
	elseif (y0 <= 1.05e+28)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	else
		tmp = y0 * (((c * t_3) + (y5 * ((j * y3) - (k * y2)))) + (b * 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[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(c * N[(N[(N[(y0 * t$95$3), $MachinePrecision] + N[(i * t$95$1), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -2.9e+176], t$95$5, If[LessEqual[y0, -7.2e-63], t$95$2, If[LessEqual[y0, -2.1e-95], N[(a * N[(y5 * t$95$4), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -1.85e-224], t$95$2, If[LessEqual[y0, 2.6e-247], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 8e-104], N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(c * t$95$1), $MachinePrecision] + N[(y5 * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.2e-6], t$95$5, If[LessEqual[y0, 1.05e+28], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(N[(N[(c * t$95$3), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y0 < -2.9000000000000001e176 or 7.99999999999999941e-104 < y0 < 2.2000000000000001e-6

   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. Taylor expanded in c around inf 59.6%

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

      1. +-commutative 59.6%

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

      2. mul-1-neg 59.6%

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

      3. unsub-neg 59.6%

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

      4. *-commutative 59.6%

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

      5. *-commutative 59.6%

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

      6. *-commutative 59.6%

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

      7. *-commutative 59.6%

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

   4. Simplified 59.6%

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

   if -2.9000000000000001e176 < y0 < -7.20000000000000016e-63 or -2.1e-95 < y0 < -1.8500000000000001e-224

   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. Taylor expanded in k around inf 60.0%

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

      1. sub-neg 60.0%

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

      2. +-commutative 60.0%

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

      3. mul-1-neg 60.0%

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

      4. unsub-neg 60.0%

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

      5. *-commutative 60.0%

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

      6. mul-1-neg 60.0%

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

      7. remove-double-neg 60.0%

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

   4. Simplified 60.0%

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

   if -7.20000000000000016e-63 < y0 < -2.1e-95

   1. Initial program 27.3%

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

   2. Taylor expanded in a around -inf 63.7%

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

      1. mul-1-neg 63.7%

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

      2. *-commutative 63.7%

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

      3. distribute-rgt-neg-in 63.7%

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

   4. Simplified 63.7%

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

   5. Taylor expanded in y5 around -inf 72.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 72.8%

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

      2. *-commutative 72.8%

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

   7. Simplified 72.8%

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

   if -1.8500000000000001e-224 < y0 < 2.6e-247

   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. Taylor expanded in b around inf 50.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 2.6e-247 < y0 < 7.99999999999999941e-104

   1. Initial program 34.6%

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

   2. Taylor expanded in i around -inf 65.6%

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

   if 2.2000000000000001e-6 < y0 < 1.04999999999999995e28

   1. Initial program 27.3%

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

   2. Taylor expanded in x around inf 73.3%

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

   if 1.04999999999999995e28 < y0

   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. Taylor expanded in y0 around inf 61.6%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 61.6%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 61.6%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 61.6%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 61.6%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 61.6%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 61.6%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 61.6%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 61.6%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 60.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -2.9 \cdot 10^{+176}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -7.2 \cdot 10^{-63}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq -2.1 \cdot 10^{-95}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -1.85 \cdot 10^{-224}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 2.6 \cdot 10^{-247}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 8 \cdot 10^{-104}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 2.2 \cdot 10^{-6}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq 1.05 \cdot 10^{+28}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - z \cdot y3\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]

Alternative 7: 43.0% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y2 - z \cdot y3\\ t_2 := t \cdot y2 - y \cdot y3\\ t_3 := c \cdot \left(\left(y0 \cdot t_1 + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot t_2\right)\\ t_4 := k \cdot y2 - j \cdot y3\\ \mathbf{if}\;c \leq -1.05 \cdot 10^{+85}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq -3.8 \cdot 10^{+39}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;c \leq -2.6 \cdot 10^{+31}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq -7.2 \cdot 10^{-178}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot t_4 - a \cdot t_1\right)\right)\\ \mathbf{elif}\;c \leq 4.7 \cdot 10^{-116}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 3.9 \cdot 10^{-23}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq 7 \cdot 10^{+71}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot t_4\right) - c \cdot t_2\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y2) (* z y3)))
        (t_2 (- (* t y2) (* y y3)))
        (t_3 (* c (- (+ (* y0 t_1) (* i (- (* z t) (* x y)))) (* y4 t_2))))
        (t_4 (- (* k y2) (* j y3))))
   (if (<= c -1.05e+85)
     t_3
     (if (<= c -3.8e+39)
       (* (* b j) (- (* t y4) (* x y0)))
       (if (<= c -2.6e+31)
         (* c (* y4 (- (* y y3) (* t y2))))
         (if (<= c -7.2e-178)
           (* y1 (+ (* i (- (* x j) (* z k))) (- (* y4 t_4) (* a t_1))))
           (if (<= c 4.7e-116)
             (*
              k
              (+
               (+ (* y2 (- (* y1 y4) (* y0 y5))) (* y (- (* i y5) (* b y4))))
               (* z (- (* b y0) (* i y1)))))
             (if (<= c 3.9e-23)
               (* a (* y3 (- (* z y1) (* y y5))))
               (if (<= c 7e+71)
                 (* y4 (- (+ (* b (- (* t j) (* y k))) (* y1 t_4)) (* c t_2)))
                 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 = (x * y2) - (z * y3);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	double t_4 = (k * y2) - (j * y3);
	double tmp;
	if (c <= -1.05e+85) {
		tmp = t_3;
	} else if (c <= -3.8e+39) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (c <= -2.6e+31) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= -7.2e-178) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)));
	} else if (c <= 4.7e-116) {
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	} else if (c <= 3.9e-23) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (c <= 7e+71) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2));
	} 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) :: tmp
    t_1 = (x * y2) - (z * y3)
    t_2 = (t * y2) - (y * y3)
    t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2))
    t_4 = (k * y2) - (j * y3)
    if (c <= (-1.05d+85)) then
        tmp = t_3
    else if (c <= (-3.8d+39)) then
        tmp = (b * j) * ((t * y4) - (x * y0))
    else if (c <= (-2.6d+31)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= (-7.2d-178)) then
        tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)))
    else if (c <= 4.7d-116) then
        tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
    else if (c <= 3.9d-23) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (c <= 7d+71) then
        tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2))
    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 = (x * y2) - (z * y3);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	double t_4 = (k * y2) - (j * y3);
	double tmp;
	if (c <= -1.05e+85) {
		tmp = t_3;
	} else if (c <= -3.8e+39) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (c <= -2.6e+31) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= -7.2e-178) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)));
	} else if (c <= 4.7e-116) {
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	} else if (c <= 3.9e-23) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (c <= 7e+71) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2));
	} 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 = (x * y2) - (z * y3)
	t_2 = (t * y2) - (y * y3)
	t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2))
	t_4 = (k * y2) - (j * y3)
	tmp = 0
	if c <= -1.05e+85:
		tmp = t_3
	elif c <= -3.8e+39:
		tmp = (b * j) * ((t * y4) - (x * y0))
	elif c <= -2.6e+31:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= -7.2e-178:
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)))
	elif c <= 4.7e-116:
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))))
	elif c <= 3.9e-23:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif c <= 7e+71:
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2))
	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(x * y2) - Float64(z * y3))
	t_2 = Float64(Float64(t * y2) - Float64(y * y3))
	t_3 = Float64(c * Float64(Float64(Float64(y0 * t_1) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * t_2)))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	tmp = 0.0
	if (c <= -1.05e+85)
		tmp = t_3;
	elseif (c <= -3.8e+39)
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	elseif (c <= -2.6e+31)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= -7.2e-178)
		tmp = Float64(y1 * Float64(Float64(i * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(y4 * t_4) - Float64(a * t_1))));
	elseif (c <= 4.7e-116)
		tmp = Float64(k * Float64(Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))) + Float64(z * Float64(Float64(b * y0) - Float64(i * y1)))));
	elseif (c <= 3.9e-23)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (c <= 7e+71)
		tmp = Float64(y4 * Float64(Float64(Float64(b * Float64(Float64(t * j) - Float64(y * k))) + Float64(y1 * t_4)) - Float64(c * t_2)));
	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 = (x * y2) - (z * y3);
	t_2 = (t * y2) - (y * y3);
	t_3 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	t_4 = (k * y2) - (j * y3);
	tmp = 0.0;
	if (c <= -1.05e+85)
		tmp = t_3;
	elseif (c <= -3.8e+39)
		tmp = (b * j) * ((t * y4) - (x * y0));
	elseif (c <= -2.6e+31)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= -7.2e-178)
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * t_4) - (a * t_1)));
	elseif (c <= 4.7e-116)
		tmp = k * (((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4)))) + (z * ((b * y0) - (i * y1))));
	elseif (c <= 3.9e-23)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (c <= 7e+71)
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * t_4)) - (c * t_2));
	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[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(N[(N[(y0 * t$95$1), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.05e+85], t$95$3, If[LessEqual[c, -3.8e+39], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2.6e+31], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -7.2e-178], N[(y1 * N[(N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y4 * t$95$4), $MachinePrecision] - N[(a * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 4.7e-116], N[(k * N[(N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.9e-23], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 7e+71], 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], t$95$3]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if c < -1.05000000000000005e85 or 6.9999999999999998e71 < c

   1. Initial program 25.1%

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

   2. Taylor expanded in c around inf 67.5%

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

      1. +-commutative 67.5%

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

      2. mul-1-neg 67.5%

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

      3. unsub-neg 67.5%

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

      4. *-commutative 67.5%

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

      5. *-commutative 67.5%

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

      6. *-commutative 67.5%

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

      7. *-commutative 67.5%

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

   4. Simplified 67.5%

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

   if -1.05000000000000005e85 < c < -3.7999999999999998e39

   1. Initial program 12.5%

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

   2. Taylor expanded in b around inf 25.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in j around inf 75.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 75.7%

         \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)} \]

      2. *-commutative 75.7%

         \[\leadsto \left(b \cdot j\right) \cdot \left(t \cdot y4 - \color{blue}{y0 \cdot x}\right) \]

   5. Simplified 75.7%

      \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - y0 \cdot x\right)} \]

   if -3.7999999999999998e39 < c < -2.6e31

   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. Taylor expanded in c around inf 68.7%

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

      1. +-commutative 68.7%

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

      2. mul-1-neg 68.7%

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

      3. unsub-neg 68.7%

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

      4. *-commutative 68.7%

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

      5. *-commutative 68.7%

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

      6. *-commutative 68.7%

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

      7. *-commutative 68.7%

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

   4. Simplified 68.7%

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

   5. Taylor expanded in y4 around inf 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

   7. Simplified 100.0%

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

   if -2.6e31 < c < -7.19999999999999987e-178

   1. Initial program 39.6%

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

   2. Taylor expanded in y1 around -inf 50.7%

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

      1. mul-1-neg 50.7%

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

      2. distribute-rgt-neg-in 50.7%

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

      3. +-commutative 50.7%

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

      4. mul-1-neg 50.7%

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

      5. unsub-neg 50.7%

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

      6. *-commutative 50.7%

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

      7. *-commutative 50.7%

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

      8. *-commutative 50.7%

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

   4. Simplified 50.7%

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

   if -7.19999999999999987e-178 < c < 4.69999999999999994e-116

   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. Taylor expanded in k around inf 54.4%

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

      1. sub-neg 54.4%

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

      2. +-commutative 54.4%

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

      3. mul-1-neg 54.4%

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

      4. unsub-neg 54.4%

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

      5. *-commutative 54.4%

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

      6. mul-1-neg 54.4%

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

      7. remove-double-neg 54.4%

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

   4. Simplified 54.4%

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

   if 4.69999999999999994e-116 < c < 3.9e-23

   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. Taylor expanded in a around -inf 58.2%

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

      1. mul-1-neg 58.2%

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

      2. *-commutative 58.2%

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

      3. distribute-rgt-neg-in 58.2%

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

   4. Simplified 58.2%

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

   5. Taylor expanded in y3 around -inf 57.9%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 3.9e-23 < c < 6.9999999999999998e71

   1. Initial program 43.6%

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

   2. Taylor expanded in y4 around inf 62.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 60.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1.05 \cdot 10^{+85}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq -3.8 \cdot 10^{+39}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;c \leq -2.6 \cdot 10^{+31}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq -7.2 \cdot 10^{-178}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;c \leq 4.7 \cdot 10^{-116}:\\ \;\;\;\;k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 3.9 \cdot 10^{-23}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;c \leq 7 \cdot 10^{+71}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \]

Alternative 8: 42.4% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y2 - z \cdot y3\\ t_2 := t \cdot y2 - y \cdot y3\\ t_3 := a \cdot \left(y5 \cdot t_2 + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ t_4 := c \cdot \left(\left(y0 \cdot t_1 + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot t_2\right)\\ \mathbf{if}\;a \leq -1.4 \cdot 10^{+102}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{-293}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 7.2 \cdot 10^{-258}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot t_1\right)\right)\\ \mathbf{elif}\;a \leq 4.4 \cdot 10^{-30}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 3.4 \cdot 10^{+105}:\\ \;\;\;\;y \cdot \left(\left(k \cdot \left(i \cdot y5 - b \cdot y4\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) + y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y2) (* z y3)))
        (t_2 (- (* t y2) (* y y3)))
        (t_3
         (*
          a
          (+
           (* y5 t_2)
           (+ (* b (- (* x y) (* z t))) (* y1 (- (* z y3) (* x y2)))))))
        (t_4 (* c (- (+ (* y0 t_1) (* i (- (* z t) (* x y)))) (* y4 t_2)))))
   (if (<= a -1.4e+102)
     t_3
     (if (<= a -2.1e-293)
       t_4
       (if (<= a 7.2e-258)
         (*
          y1
          (+
           (* i (- (* x j) (* z k)))
           (- (* y4 (- (* k y2) (* j y3))) (* a t_1))))
         (if (<= a 4.4e-30)
           t_4
           (if (<= a 3.4e+105)
             (*
              y
              (+
               (+ (* k (- (* i y5) (* b y4))) (* x (- (* a b) (* c i))))
               (* y3 (- (* c y4) (* a y5)))))
             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 = (x * y2) - (z * y3);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))));
	double t_4 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	double tmp;
	if (a <= -1.4e+102) {
		tmp = t_3;
	} else if (a <= -2.1e-293) {
		tmp = t_4;
	} else if (a <= 7.2e-258) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * t_1)));
	} else if (a <= 4.4e-30) {
		tmp = t_4;
	} else if (a <= 3.4e+105) {
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))));
	} 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) :: tmp
    t_1 = (x * y2) - (z * y3)
    t_2 = (t * y2) - (y * y3)
    t_3 = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))))
    t_4 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2))
    if (a <= (-1.4d+102)) then
        tmp = t_3
    else if (a <= (-2.1d-293)) then
        tmp = t_4
    else if (a <= 7.2d-258) then
        tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * t_1)))
    else if (a <= 4.4d-30) then
        tmp = t_4
    else if (a <= 3.4d+105) then
        tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))))
    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 = (x * y2) - (z * y3);
	double t_2 = (t * y2) - (y * y3);
	double t_3 = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))));
	double t_4 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	double tmp;
	if (a <= -1.4e+102) {
		tmp = t_3;
	} else if (a <= -2.1e-293) {
		tmp = t_4;
	} else if (a <= 7.2e-258) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * t_1)));
	} else if (a <= 4.4e-30) {
		tmp = t_4;
	} else if (a <= 3.4e+105) {
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))));
	} 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 = (x * y2) - (z * y3)
	t_2 = (t * y2) - (y * y3)
	t_3 = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))))
	t_4 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2))
	tmp = 0
	if a <= -1.4e+102:
		tmp = t_3
	elif a <= -2.1e-293:
		tmp = t_4
	elif a <= 7.2e-258:
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * t_1)))
	elif a <= 4.4e-30:
		tmp = t_4
	elif a <= 3.4e+105:
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))))
	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(x * y2) - Float64(z * y3))
	t_2 = Float64(Float64(t * y2) - Float64(y * y3))
	t_3 = Float64(a * Float64(Float64(y5 * t_2) + Float64(Float64(b * Float64(Float64(x * y) - Float64(z * t))) + Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))))
	t_4 = Float64(c * Float64(Float64(Float64(y0 * t_1) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * t_2)))
	tmp = 0.0
	if (a <= -1.4e+102)
		tmp = t_3;
	elseif (a <= -2.1e-293)
		tmp = t_4;
	elseif (a <= 7.2e-258)
		tmp = Float64(y1 * Float64(Float64(i * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(a * t_1))));
	elseif (a <= 4.4e-30)
		tmp = t_4;
	elseif (a <= 3.4e+105)
		tmp = Float64(y * Float64(Float64(Float64(k * Float64(Float64(i * y5) - Float64(b * y4))) + Float64(x * Float64(Float64(a * b) - Float64(c * i)))) + Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5)))));
	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 = (x * y2) - (z * y3);
	t_2 = (t * y2) - (y * y3);
	t_3 = a * ((y5 * t_2) + ((b * ((x * y) - (z * t))) + (y1 * ((z * y3) - (x * y2)))));
	t_4 = c * (((y0 * t_1) + (i * ((z * t) - (x * y)))) - (y4 * t_2));
	tmp = 0.0;
	if (a <= -1.4e+102)
		tmp = t_3;
	elseif (a <= -2.1e-293)
		tmp = t_4;
	elseif (a <= 7.2e-258)
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * t_1)));
	elseif (a <= 4.4e-30)
		tmp = t_4;
	elseif (a <= 3.4e+105)
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))));
	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[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(a * N[(N[(y5 * t$95$2), $MachinePrecision] + N[(N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(c * N[(N[(N[(y0 * t$95$1), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.4e+102], t$95$3, If[LessEqual[a, -2.1e-293], t$95$4, If[LessEqual[a, 7.2e-258], N[(y1 * N[(N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.4e-30], t$95$4, If[LessEqual[a, 3.4e+105], N[(y * N[(N[(N[(k * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if a < -1.40000000000000009e102 or 3.3999999999999999e105 < a

   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. Taylor expanded in a around -inf 60.1%

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

      1. mul-1-neg 60.1%

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

      2. *-commutative 60.1%

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

      3. distribute-rgt-neg-in 60.1%

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

   4. Simplified 60.1%

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

   if -1.40000000000000009e102 < a < -2.10000000000000005e-293 or 7.19999999999999958e-258 < a < 4.39999999999999967e-30

   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. Taylor expanded in c around inf 53.4%

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

      1. +-commutative 53.4%

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

      2. mul-1-neg 53.4%

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

      3. unsub-neg 53.4%

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

      4. *-commutative 53.4%

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

      5. *-commutative 53.4%

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

      6. *-commutative 53.4%

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

      7. *-commutative 53.4%

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

   4. Simplified 53.4%

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

   if -2.10000000000000005e-293 < a < 7.19999999999999958e-258

   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. Taylor expanded in y1 around -inf 64.4%

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

      1. mul-1-neg 64.4%

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

      2. distribute-rgt-neg-in 64.4%

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

      3. +-commutative 64.4%

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

      4. mul-1-neg 64.4%

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

      5. unsub-neg 64.4%

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

      6. *-commutative 64.4%

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

      7. *-commutative 64.4%

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

      8. *-commutative 64.4%

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

   4. Simplified 64.4%

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

   if 4.39999999999999967e-30 < a < 3.3999999999999999e105

   1. Initial program 32.1%

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

   2. Taylor expanded in y around inf 68.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 57.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -1.4 \cdot 10^{+102}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{-293}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 7.2 \cdot 10^{-258}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;a \leq 4.4 \cdot 10^{-30}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 3.4 \cdot 10^{+105}:\\ \;\;\;\;y \cdot \left(\left(k \cdot \left(i \cdot y5 - b \cdot y4\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) + y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \end{array} \]

Alternative 9: 37.6% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;a \leq -7.5 \cdot 10^{+137}:\\ \;\;\;\;a \cdot \left(y5 \cdot t_1\right)\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{+149}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot t_1\right)\\ \mathbf{elif}\;a \leq 1.75 \cdot 10^{+196}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t y2) (* y y3))))
   (if (<= a -7.5e+137)
     (* a (* y5 t_1))
     (if (<= a 1.1e+149)
       (*
        c
        (-
         (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
         (* y4 t_1)))
       (if (<= a 1.75e+196)
         (* j (* x (- (* i y1) (* b y0))))
         (*
          b
          (+
           (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
           (* y0 (- (* z k) (* x j))))))))))

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 = (t * y2) - (y * y3);
	double tmp;
	if (a <= -7.5e+137) {
		tmp = a * (y5 * t_1);
	} else if (a <= 1.1e+149) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * t_1));
	} else if (a <= 1.75e+196) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	}
	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 = (t * y2) - (y * y3)
    if (a <= (-7.5d+137)) then
        tmp = a * (y5 * t_1)
    else if (a <= 1.1d+149) then
        tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * t_1))
    else if (a <= 1.75d+196) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    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 = (t * y2) - (y * y3);
	double tmp;
	if (a <= -7.5e+137) {
		tmp = a * (y5 * t_1);
	} else if (a <= 1.1e+149) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * t_1));
	} else if (a <= 1.75e+196) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (t * y2) - (y * y3)
	tmp = 0
	if a <= -7.5e+137:
		tmp = a * (y5 * t_1)
	elif a <= 1.1e+149:
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * t_1))
	elif a <= 1.75e+196:
		tmp = j * (x * ((i * y1) - (b * y0)))
	else:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	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(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (a <= -7.5e+137)
		tmp = Float64(a * Float64(y5 * t_1));
	elseif (a <= 1.1e+149)
		tmp = Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) - Float64(y4 * t_1)));
	elseif (a <= 1.75e+196)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	else
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	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 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (a <= -7.5e+137)
		tmp = a * (y5 * t_1);
	elseif (a <= 1.1e+149)
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) - (y4 * t_1));
	elseif (a <= 1.75e+196)
		tmp = j * (x * ((i * y1) - (b * y0)));
	else
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	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[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -7.5e+137], N[(a * N[(y5 * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.1e+149], N[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.75e+196], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 4 regimes

2. if a < -7.50000000000000025e137

   1. Initial program 14.4%

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

   2. Taylor expanded in a around -inf 63.1%

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

      1. mul-1-neg 63.1%

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

      2. *-commutative 63.1%

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

      3. distribute-rgt-neg-in 63.1%

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

   4. Simplified 63.1%

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

   5. Taylor expanded in y5 around -inf 57.5%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 57.5%

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

      2. *-commutative 57.5%

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

   7. Simplified 57.5%

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

   if -7.50000000000000025e137 < a < 1.1e149

   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. Taylor expanded in c around inf 50.3%

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

      1. +-commutative 50.3%

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

      2. mul-1-neg 50.3%

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

      3. unsub-neg 50.3%

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

      4. *-commutative 50.3%

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

      5. *-commutative 50.3%

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

      6. *-commutative 50.3%

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

      7. *-commutative 50.3%

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

   4. Simplified 50.3%

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

   if 1.1e149 < a < 1.7499999999999999e196

   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. Taylor expanded in x around inf 9.3%

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

   3. Taylor expanded in j around inf 82.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 82.1%

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

      2. *-commutative 82.1%

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

   5. Simplified 82.1%

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

   if 1.7499999999999999e196 < a

   1. Initial program 28.0%

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

   2. Taylor expanded in b around inf 60.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 53.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -7.5 \cdot 10^{+137}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{+149}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 1.75 \cdot 10^{+196}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]

Alternative 10: 36.1% accurate, 2.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ t_2 := t \cdot \left(b \cdot y4 - i \cdot y5\right)\\ t_3 := j \cdot \left(t_2 + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{if}\;y2 \leq -4.1 \cdot 10^{+159}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -8 \cdot 10^{-212}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y2 \leq -7.5 \cdot 10^{-267}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y2 \leq -1.02 \cdot 10^{-269}:\\ \;\;\;\;j \cdot t_2\\ \mathbf{elif}\;y2 \leq 4.5 \cdot 10^{-307}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{-88}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y2 \leq 4.8 \cdot 10^{+44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{+97}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 4.1 \cdot 10^{+129}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 5.6 \cdot 10^{+231}:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y2 (- (* y1 y4) (* y0 y5)))))
        (t_2 (* t (- (* b y4) (* i y5))))
        (t_3 (* j (+ t_2 (* x (- (* i y1) (* b y0)))))))
   (if (<= y2 -4.1e+159)
     t_1
     (if (<= y2 -8e-212)
       (*
        b
        (+
         (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
         (* y0 (- (* z k) (* x j)))))
       (if (<= y2 -7.5e-267)
         t_3
         (if (<= y2 -1.02e-269)
           (* j t_2)
           (if (<= y2 4.5e-307)
             (* y0 (* y3 (- (* j y5) (* z c))))
             (if (<= y2 4e-88)
               t_3
               (if (<= y2 4.8e+44)
                 t_1
                 (if (<= y2 4e+97)
                   (* b (* y (- (* x a) (* k y4))))
                   (if (<= y2 4.1e+129)
                     (* a (* y3 (- (* z y1) (* y y5))))
                     (if (<= y2 5.6e+231)
                       (* a (* y2 (- (* t y5) (* x y1))))
                       (* y0 (* y2 (- (* x c) (* k 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double t_2 = t * ((b * y4) - (i * y5));
	double t_3 = j * (t_2 + (x * ((i * y1) - (b * y0))));
	double tmp;
	if (y2 <= -4.1e+159) {
		tmp = t_1;
	} else if (y2 <= -8e-212) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (y2 <= -7.5e-267) {
		tmp = t_3;
	} else if (y2 <= -1.02e-269) {
		tmp = j * t_2;
	} else if (y2 <= 4.5e-307) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y2 <= 4e-88) {
		tmp = t_3;
	} else if (y2 <= 4.8e+44) {
		tmp = t_1;
	} else if (y2 <= 4e+97) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 4.1e+129) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 5.6e+231) {
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    t_2 = t * ((b * y4) - (i * y5))
    t_3 = j * (t_2 + (x * ((i * y1) - (b * y0))))
    if (y2 <= (-4.1d+159)) then
        tmp = t_1
    else if (y2 <= (-8d-212)) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else if (y2 <= (-7.5d-267)) then
        tmp = t_3
    else if (y2 <= (-1.02d-269)) then
        tmp = j * t_2
    else if (y2 <= 4.5d-307) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (y2 <= 4d-88) then
        tmp = t_3
    else if (y2 <= 4.8d+44) then
        tmp = t_1
    else if (y2 <= 4d+97) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (y2 <= 4.1d+129) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y2 <= 5.6d+231) then
        tmp = a * (y2 * ((t * y5) - (x * y1)))
    else
        tmp = y0 * (y2 * ((x * c) - (k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double t_2 = t * ((b * y4) - (i * y5));
	double t_3 = j * (t_2 + (x * ((i * y1) - (b * y0))));
	double tmp;
	if (y2 <= -4.1e+159) {
		tmp = t_1;
	} else if (y2 <= -8e-212) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (y2 <= -7.5e-267) {
		tmp = t_3;
	} else if (y2 <= -1.02e-269) {
		tmp = j * t_2;
	} else if (y2 <= 4.5e-307) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y2 <= 4e-88) {
		tmp = t_3;
	} else if (y2 <= 4.8e+44) {
		tmp = t_1;
	} else if (y2 <= 4e+97) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 4.1e+129) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 5.6e+231) {
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	t_2 = t * ((b * y4) - (i * y5))
	t_3 = j * (t_2 + (x * ((i * y1) - (b * y0))))
	tmp = 0
	if y2 <= -4.1e+159:
		tmp = t_1
	elif y2 <= -8e-212:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	elif y2 <= -7.5e-267:
		tmp = t_3
	elif y2 <= -1.02e-269:
		tmp = j * t_2
	elif y2 <= 4.5e-307:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif y2 <= 4e-88:
		tmp = t_3
	elif y2 <= 4.8e+44:
		tmp = t_1
	elif y2 <= 4e+97:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif y2 <= 4.1e+129:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y2 <= 5.6e+231:
		tmp = a * (y2 * ((t * y5) - (x * y1)))
	else:
		tmp = y0 * (y2 * ((x * c) - (k * 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(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	t_2 = Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))
	t_3 = Float64(j * Float64(t_2 + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))))
	tmp = 0.0
	if (y2 <= -4.1e+159)
		tmp = t_1;
	elseif (y2 <= -8e-212)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (y2 <= -7.5e-267)
		tmp = t_3;
	elseif (y2 <= -1.02e-269)
		tmp = Float64(j * t_2);
	elseif (y2 <= 4.5e-307)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (y2 <= 4e-88)
		tmp = t_3;
	elseif (y2 <= 4.8e+44)
		tmp = t_1;
	elseif (y2 <= 4e+97)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (y2 <= 4.1e+129)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y2 <= 5.6e+231)
		tmp = Float64(a * Float64(y2 * Float64(Float64(t * y5) - Float64(x * y1))));
	else
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	t_2 = t * ((b * y4) - (i * y5));
	t_3 = j * (t_2 + (x * ((i * y1) - (b * y0))));
	tmp = 0.0;
	if (y2 <= -4.1e+159)
		tmp = t_1;
	elseif (y2 <= -8e-212)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	elseif (y2 <= -7.5e-267)
		tmp = t_3;
	elseif (y2 <= -1.02e-269)
		tmp = j * t_2;
	elseif (y2 <= 4.5e-307)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (y2 <= 4e-88)
		tmp = t_3;
	elseif (y2 <= 4.8e+44)
		tmp = t_1;
	elseif (y2 <= 4e+97)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (y2 <= 4.1e+129)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y2 <= 5.6e+231)
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	else
		tmp = y0 * (y2 * ((x * c) - (k * 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[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(t$95$2 + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -4.1e+159], t$95$1, If[LessEqual[y2, -8e-212], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -7.5e-267], t$95$3, If[LessEqual[y2, -1.02e-269], N[(j * t$95$2), $MachinePrecision], If[LessEqual[y2, 4.5e-307], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4e-88], t$95$3, If[LessEqual[y2, 4.8e+44], t$95$1, If[LessEqual[y2, 4e+97], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.1e+129], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5.6e+231], N[(a * N[(y2 * N[(N[(t * y5), $MachinePrecision] - N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y2 < -4.10000000000000014e159 or 3.99999999999999974e-88 < y2 < 4.80000000000000026e44

   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. Taylor expanded in k around inf 41.7%

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

      1. sub-neg 41.7%

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

      2. +-commutative 41.7%

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

      3. mul-1-neg 41.7%

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

      4. unsub-neg 41.7%

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

      5. *-commutative 41.7%

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

      6. mul-1-neg 41.7%

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

      7. remove-double-neg 41.7%

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

   4. Simplified 41.7%

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

   5. Taylor expanded in y2 around inf 52.2%

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

   if -4.10000000000000014e159 < y2 < -7.99999999999999963e-212

   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. Taylor expanded in b around inf 48.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -7.99999999999999963e-212 < y2 < -7.4999999999999999e-267 or 4.49999999999999989e-307 < y2 < 3.99999999999999974e-88

   1. Initial program 33.0%

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

   2. Taylor expanded in j around inf 40.7%

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

      1. +-commutative 40.7%

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

      2. mul-1-neg 40.7%

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

      3. unsub-neg 40.7%

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

      4. *-commutative 40.7%

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

   4. Simplified 40.7%

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

   5. Taylor expanded in y3 around 0 49.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 49.4%

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

      2. *-commutative 49.4%

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

   7. Simplified 49.4%

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

   if -7.4999999999999999e-267 < y2 < -1.02000000000000002e-269

   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. Taylor expanded in t around inf 50.0%

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

   3. Taylor expanded in j around inf 100.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.02000000000000002e-269 < y2 < 4.49999999999999989e-307

   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. Taylor expanded in y0 around inf 51.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 51.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 51.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 51.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 51.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 51.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 51.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 51.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 51.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y3 around inf 80.1%

      \[\leadsto y0 \cdot \color{blue}{\left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) - -1 \cdot \left(j \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. sub-neg 80.1%

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

      2. mul-1-neg 80.1%

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

      3. remove-double-neg 80.1%

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

      4. +-commutative 80.1%

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

      5. mul-1-neg 80.1%

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

      6. unsub-neg 80.1%

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

   7. Simplified 80.1%

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

   if 4.80000000000000026e44 < y2 < 4.0000000000000003e97

   1. Initial program 15.3%

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

   2. Taylor expanded in b around inf 16.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 61.8%

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

      1. +-commutative 61.8%

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

      2. mul-1-neg 61.8%

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

      3. unsub-neg 61.8%

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

      4. *-commutative 61.8%

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

      5. *-commutative 61.8%

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

   5. Simplified 61.8%

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

   if 4.0000000000000003e97 < y2 < 4.1000000000000003e129

   1. Initial program 11.1%

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

   2. Taylor expanded in a around -inf 46.1%

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

      1. mul-1-neg 46.1%

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

      2. *-commutative 46.1%

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

      3. distribute-rgt-neg-in 46.1%

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

   4. Simplified 46.1%

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

   5. Taylor expanded in y3 around -inf 56.3%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 4.1000000000000003e129 < y2 < 5.6e231

   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. Taylor expanded in a around -inf 45.2%

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

      1. mul-1-neg 45.2%

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

      2. *-commutative 45.2%

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

      3. distribute-rgt-neg-in 45.2%

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

   4. Simplified 45.2%

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

   5. Taylor expanded in y2 around inf 60.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y2 \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 60.7%

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

      2. neg-mul-1 60.7%

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

   7. Simplified 60.7%

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

   if 5.6e231 < y2

   1. Initial program 30.8%

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

   2. Taylor expanded in y0 around inf 69.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 69.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 69.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 69.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y2 around inf 92.3%

      \[\leadsto \color{blue}{y0 \cdot \left(y2 \cdot \left(c \cdot x - k \cdot y5\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 55.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -4.1 \cdot 10^{+159}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -8 \cdot 10^{-212}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y2 \leq -7.5 \cdot 10^{-267}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -1.02 \cdot 10^{-269}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 4.5 \cdot 10^{-307}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{-88}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 4.8 \cdot 10^{+44}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{+97}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 4.1 \cdot 10^{+129}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 5.6 \cdot 10^{+231}:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \]

Alternative 11: 29.1% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ t_2 := j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{if}\;y2 \leq -3.7 \cdot 10^{+180}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -1.36 \cdot 10^{+135}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq -3.6 \cdot 10^{+99}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -7.5 \cdot 10^{+40}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y2 \leq -3.8 \cdot 10^{-217}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -4.8 \cdot 10^{-289}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 3.2 \cdot 10^{-121}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 8.8 \cdot 10^{+160}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 7.5 \cdot 10^{+202}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 1.75 \cdot 10^{+224}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* x (- (* y0 y2) (* y i)))))
        (t_2 (* j (* x (- (* i y1) (* b y0))))))
   (if (<= y2 -3.7e+180)
     t_1
     (if (<= y2 -1.36e+135)
       (* k (* y (- (* i y5) (* b y4))))
       (if (<= y2 -3.6e+99)
         (* a (* y (- (* x b) (* y3 y5))))
         (if (<= y2 -7.5e+40)
           (* a (* y5 (- (* t y2) (* y y3))))
           (if (<= y2 -3.8e-217)
             (* b (* x (- (* y a) (* j y0))))
             (if (<= y2 -4.8e-289)
               (* j (* t (- (* b y4) (* i y5))))
               (if (<= y2 3.2e-121)
                 t_2
                 (if (<= y2 8.8e+160)
                   (* a (* y3 (- (* z y1) (* y y5))))
                   (if (<= y2 7.5e+202)
                     t_2
                     (if (<= y2 1.75e+224)
                       (* c (* y4 (- (* y y3) (* t y2))))
                       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 * (x * ((y0 * y2) - (y * i)));
	double t_2 = j * (x * ((i * y1) - (b * y0)));
	double tmp;
	if (y2 <= -3.7e+180) {
		tmp = t_1;
	} else if (y2 <= -1.36e+135) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (y2 <= -3.6e+99) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y2 <= -7.5e+40) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y2 <= -3.8e-217) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -4.8e-289) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 3.2e-121) {
		tmp = t_2;
	} else if (y2 <= 8.8e+160) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 7.5e+202) {
		tmp = t_2;
	} else if (y2 <= 1.75e+224) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} 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) :: t_2
    real(8) :: tmp
    t_1 = c * (x * ((y0 * y2) - (y * i)))
    t_2 = j * (x * ((i * y1) - (b * y0)))
    if (y2 <= (-3.7d+180)) then
        tmp = t_1
    else if (y2 <= (-1.36d+135)) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (y2 <= (-3.6d+99)) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (y2 <= (-7.5d+40)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (y2 <= (-3.8d-217)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y2 <= (-4.8d-289)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y2 <= 3.2d-121) then
        tmp = t_2
    else if (y2 <= 8.8d+160) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y2 <= 7.5d+202) then
        tmp = t_2
    else if (y2 <= 1.75d+224) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    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 * (x * ((y0 * y2) - (y * i)));
	double t_2 = j * (x * ((i * y1) - (b * y0)));
	double tmp;
	if (y2 <= -3.7e+180) {
		tmp = t_1;
	} else if (y2 <= -1.36e+135) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (y2 <= -3.6e+99) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y2 <= -7.5e+40) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (y2 <= -3.8e-217) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -4.8e-289) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 3.2e-121) {
		tmp = t_2;
	} else if (y2 <= 8.8e+160) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 7.5e+202) {
		tmp = t_2;
	} else if (y2 <= 1.75e+224) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} 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 * (x * ((y0 * y2) - (y * i)))
	t_2 = j * (x * ((i * y1) - (b * y0)))
	tmp = 0
	if y2 <= -3.7e+180:
		tmp = t_1
	elif y2 <= -1.36e+135:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif y2 <= -3.6e+99:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif y2 <= -7.5e+40:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif y2 <= -3.8e-217:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y2 <= -4.8e-289:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y2 <= 3.2e-121:
		tmp = t_2
	elif y2 <= 8.8e+160:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y2 <= 7.5e+202:
		tmp = t_2
	elif y2 <= 1.75e+224:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	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(x * Float64(Float64(y0 * y2) - Float64(y * i))))
	t_2 = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))))
	tmp = 0.0
	if (y2 <= -3.7e+180)
		tmp = t_1;
	elseif (y2 <= -1.36e+135)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (y2 <= -3.6e+99)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (y2 <= -7.5e+40)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (y2 <= -3.8e-217)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y2 <= -4.8e-289)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y2 <= 3.2e-121)
		tmp = t_2;
	elseif (y2 <= 8.8e+160)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y2 <= 7.5e+202)
		tmp = t_2;
	elseif (y2 <= 1.75e+224)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	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 * (x * ((y0 * y2) - (y * i)));
	t_2 = j * (x * ((i * y1) - (b * y0)));
	tmp = 0.0;
	if (y2 <= -3.7e+180)
		tmp = t_1;
	elseif (y2 <= -1.36e+135)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (y2 <= -3.6e+99)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (y2 <= -7.5e+40)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (y2 <= -3.8e-217)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y2 <= -4.8e-289)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y2 <= 3.2e-121)
		tmp = t_2;
	elseif (y2 <= 8.8e+160)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y2 <= 7.5e+202)
		tmp = t_2;
	elseif (y2 <= 1.75e+224)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	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[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -3.7e+180], t$95$1, If[LessEqual[y2, -1.36e+135], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -3.6e+99], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -7.5e+40], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -3.8e-217], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -4.8e-289], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 3.2e-121], t$95$2, If[LessEqual[y2, 8.8e+160], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 7.5e+202], t$95$2, If[LessEqual[y2, 1.75e+224], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y2 < -3.7000000000000002e180 or 1.75e224 < y2

   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. Taylor expanded in c around inf 60.5%

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

      1. +-commutative 60.5%

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

      2. mul-1-neg 60.5%

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

      3. unsub-neg 60.5%

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

      4. *-commutative 60.5%

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

      5. *-commutative 60.5%

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

      6. *-commutative 60.5%

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

      7. *-commutative 60.5%

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

   4. Simplified 60.5%

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

   5. Taylor expanded in x around inf 58.0%

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

   if -3.7000000000000002e180 < y2 < -1.36000000000000007e135

   1. Initial program 37.0%

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

   2. Taylor expanded in k around inf 73.7%

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

      1. sub-neg 73.7%

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

      2. +-commutative 73.7%

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

      3. mul-1-neg 73.7%

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

      4. unsub-neg 73.7%

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

      5. *-commutative 73.7%

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

      6. mul-1-neg 73.7%

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

      7. remove-double-neg 73.7%

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

   4. Simplified 73.7%

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

   5. Taylor expanded in y around inf 64.5%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 64.5%

         \[\leadsto k \cdot \left(y \cdot \left(\color{blue}{y5 \cdot i} - b \cdot y4\right)\right) \]

      2. *-commutative 64.5%

         \[\leadsto k \cdot \left(y \cdot \left(y5 \cdot i - \color{blue}{y4 \cdot b}\right)\right) \]

   7. Simplified 64.5%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(y5 \cdot i - y4 \cdot b\right)\right)} \]

   if -1.36000000000000007e135 < y2 < -3.6000000000000002e99

   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. Taylor expanded in a around -inf 57.1%

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

      1. mul-1-neg 57.1%

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

      2. *-commutative 57.1%

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

      3. distribute-rgt-neg-in 57.1%

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

   4. Simplified 57.1%

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

   5. Taylor expanded in y around inf 57.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 57.7%

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

      2. mul-1-neg 57.7%

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

      3. unsub-neg 57.7%

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

      4. *-commutative 57.7%

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

   7. Simplified 57.7%

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

   if -3.6000000000000002e99 < y2 < -7.4999999999999996e40

   1. Initial program 61.0%

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

   2. Taylor expanded in a around -inf 67.3%

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

      1. mul-1-neg 67.3%

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

      2. *-commutative 67.3%

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

      3. distribute-rgt-neg-in 67.3%

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

   4. Simplified 67.3%

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

   5. Taylor expanded in y5 around -inf 56.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 56.0%

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

      2. *-commutative 56.0%

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

   7. Simplified 56.0%

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

   if -7.4999999999999996e40 < y2 < -3.79999999999999987e-217

   1. Initial program 28.9%

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

   2. Taylor expanded in b around inf 44.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 41.4%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.4%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 41.4%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 41.4%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -3.79999999999999987e-217 < y2 < -4.79999999999999988e-289

   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. Taylor expanded in t around inf 50.7%

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

   3. Taylor expanded in j around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -4.79999999999999988e-289 < y2 < 3.20000000000000019e-121 or 8.79999999999999968e160 < y2 < 7.4999999999999999e202

   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. Taylor expanded in x around inf 48.8%

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

   3. Taylor expanded in j around inf 49.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 49.5%

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

      2. *-commutative 49.5%

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

   5. Simplified 49.5%

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

   if 3.20000000000000019e-121 < y2 < 8.79999999999999968e160

   1. Initial program 26.3%

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

   2. Taylor expanded in a around -inf 43.6%

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

      1. mul-1-neg 43.6%

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

      2. *-commutative 43.6%

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

      3. distribute-rgt-neg-in 43.6%

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

   4. Simplified 43.6%

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

   5. Taylor expanded in y3 around -inf 38.4%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 7.4999999999999999e202 < y2 < 1.75e224

   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. Taylor expanded in c around inf 60.0%

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

      1. +-commutative 60.0%

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

      2. mul-1-neg 60.0%

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

      3. unsub-neg 60.0%

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

      4. *-commutative 60.0%

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

      5. *-commutative 60.0%

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

      6. *-commutative 60.0%

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

      7. *-commutative 60.0%

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

   4. Simplified 60.0%

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

   5. Taylor expanded in y4 around inf 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

   7. Simplified 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 50.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -3.7 \cdot 10^{+180}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;y2 \leq -1.36 \cdot 10^{+135}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq -3.6 \cdot 10^{+99}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -7.5 \cdot 10^{+40}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y2 \leq -3.8 \cdot 10^{-217}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -4.8 \cdot 10^{-289}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 3.2 \cdot 10^{-121}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 8.8 \cdot 10^{+160}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 7.5 \cdot 10^{+202}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 1.75 \cdot 10^{+224}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 12: 29.9% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;y2 \leq -7.5 \cdot 10^{+78}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq -3.15 \cdot 10^{-218}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -4.6 \cdot 10^{-289}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 5.5 \cdot 10^{-307}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 4.8 \cdot 10^{-104}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 2.4 \cdot 10^{+36}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{+97}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 3 \cdot 10^{+161}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 7.8 \cdot 10^{+202}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 1.8 \cdot 10^{+222}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* x (- (* i y1) (* b y0)))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= y2 -7.5e+78)
     t_2
     (if (<= y2 -3.15e-218)
       (* b (* x (- (* y a) (* j y0))))
       (if (<= y2 -4.6e-289)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= y2 5.5e-307)
           (* a (* y (- (* x b) (* y3 y5))))
           (if (<= y2 4.8e-104)
             t_1
             (if (<= y2 2.4e+36)
               t_2
               (if (<= y2 4e+97)
                 (* b (* y (- (* x a) (* k y4))))
                 (if (<= y2 3e+161)
                   (* a (* y3 (- (* z y1) (* y y5))))
                   (if (<= y2 7.8e+202)
                     t_1
                     (if (<= y2 1.8e+222)
                       (* c (* y4 (- (* y y3) (* t y2))))
                       (* c (* x (- (* y0 y2) (* y 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 = j * (x * ((i * y1) - (b * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -7.5e+78) {
		tmp = t_2;
	} else if (y2 <= -3.15e-218) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -4.6e-289) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 5.5e-307) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y2 <= 4.8e-104) {
		tmp = t_1;
	} else if (y2 <= 2.4e+36) {
		tmp = t_2;
	} else if (y2 <= 4e+97) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 3e+161) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 7.8e+202) {
		tmp = t_1;
	} else if (y2 <= 1.8e+222) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else {
		tmp = c * (x * ((y0 * y2) - (y * 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 = j * (x * ((i * y1) - (b * y0)))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (y2 <= (-7.5d+78)) then
        tmp = t_2
    else if (y2 <= (-3.15d-218)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y2 <= (-4.6d-289)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y2 <= 5.5d-307) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (y2 <= 4.8d-104) then
        tmp = t_1
    else if (y2 <= 2.4d+36) then
        tmp = t_2
    else if (y2 <= 4d+97) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (y2 <= 3d+161) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y2 <= 7.8d+202) then
        tmp = t_1
    else if (y2 <= 1.8d+222) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else
        tmp = c * (x * ((y0 * y2) - (y * 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 = j * (x * ((i * y1) - (b * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -7.5e+78) {
		tmp = t_2;
	} else if (y2 <= -3.15e-218) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -4.6e-289) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 5.5e-307) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y2 <= 4.8e-104) {
		tmp = t_1;
	} else if (y2 <= 2.4e+36) {
		tmp = t_2;
	} else if (y2 <= 4e+97) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 3e+161) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 7.8e+202) {
		tmp = t_1;
	} else if (y2 <= 1.8e+222) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (x * ((i * y1) - (b * y0)))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if y2 <= -7.5e+78:
		tmp = t_2
	elif y2 <= -3.15e-218:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y2 <= -4.6e-289:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y2 <= 5.5e-307:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif y2 <= 4.8e-104:
		tmp = t_1
	elif y2 <= 2.4e+36:
		tmp = t_2
	elif y2 <= 4e+97:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif y2 <= 3e+161:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y2 <= 7.8e+202:
		tmp = t_1
	elif y2 <= 1.8e+222:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	else:
		tmp = c * (x * ((y0 * y2) - (y * 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(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (y2 <= -7.5e+78)
		tmp = t_2;
	elseif (y2 <= -3.15e-218)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y2 <= -4.6e-289)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y2 <= 5.5e-307)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (y2 <= 4.8e-104)
		tmp = t_1;
	elseif (y2 <= 2.4e+36)
		tmp = t_2;
	elseif (y2 <= 4e+97)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (y2 <= 3e+161)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y2 <= 7.8e+202)
		tmp = t_1;
	elseif (y2 <= 1.8e+222)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	else
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * 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 = j * (x * ((i * y1) - (b * y0)));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (y2 <= -7.5e+78)
		tmp = t_2;
	elseif (y2 <= -3.15e-218)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y2 <= -4.6e-289)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y2 <= 5.5e-307)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (y2 <= 4.8e-104)
		tmp = t_1;
	elseif (y2 <= 2.4e+36)
		tmp = t_2;
	elseif (y2 <= 4e+97)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (y2 <= 3e+161)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y2 <= 7.8e+202)
		tmp = t_1;
	elseif (y2 <= 1.8e+222)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	else
		tmp = c * (x * ((y0 * y2) - (y * 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[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -7.5e+78], t$95$2, If[LessEqual[y2, -3.15e-218], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -4.6e-289], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5.5e-307], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.8e-104], t$95$1, If[LessEqual[y2, 2.4e+36], t$95$2, If[LessEqual[y2, 4e+97], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 3e+161], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 7.8e+202], t$95$1, If[LessEqual[y2, 1.8e+222], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y2 < -7.49999999999999934e78 or 4.8000000000000001e-104 < y2 < 2.39999999999999992e36

   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. Taylor expanded in k around inf 44.4%

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

      1. sub-neg 44.4%

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

      2. +-commutative 44.4%

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

      3. mul-1-neg 44.4%

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

      4. unsub-neg 44.4%

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

      5. *-commutative 44.4%

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

      6. mul-1-neg 44.4%

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

      7. remove-double-neg 44.4%

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

   4. Simplified 44.4%

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

   5. Taylor expanded in y2 around inf 46.3%

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

   if -7.49999999999999934e78 < y2 < -3.1499999999999998e-218

   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. Taylor expanded in b around inf 46.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 42.0%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.0%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 42.0%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 42.0%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -3.1499999999999998e-218 < y2 < -4.6000000000000004e-289

   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. Taylor expanded in t around inf 50.7%

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

   3. Taylor expanded in j around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -4.6000000000000004e-289 < y2 < 5.50000000000000039e-307

   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. Taylor expanded in a around -inf 57.9%

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

      1. mul-1-neg 57.9%

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

      2. *-commutative 57.9%

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

      3. distribute-rgt-neg-in 57.9%

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

   4. Simplified 57.9%

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

   5. Taylor expanded in y around inf 58.0%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 58.0%

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

      2. mul-1-neg 58.0%

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

      3. unsub-neg 58.0%

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

      4. *-commutative 58.0%

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

   7. Simplified 58.0%

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

   if 5.50000000000000039e-307 < y2 < 4.8000000000000001e-104 or 3.00000000000000011e161 < y2 < 7.79999999999999967e202

   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. Taylor expanded in x around inf 47.7%

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

   3. Taylor expanded in j around inf 48.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 48.5%

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

      2. *-commutative 48.5%

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

   5. Simplified 48.5%

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

   if 2.39999999999999992e36 < y2 < 4.0000000000000003e97

   1. Initial program 15.3%

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

   2. Taylor expanded in b around inf 16.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 61.8%

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

      1. +-commutative 61.8%

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

      2. mul-1-neg 61.8%

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

      3. unsub-neg 61.8%

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

      4. *-commutative 61.8%

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

      5. *-commutative 61.8%

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

   5. Simplified 61.8%

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

   if 4.0000000000000003e97 < y2 < 3.00000000000000011e161

   1. Initial program 13.2%

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

   2. Taylor expanded in a around -inf 54.5%

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

      1. mul-1-neg 54.5%

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

      2. *-commutative 54.5%

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

      3. distribute-rgt-neg-in 54.5%

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

   4. Simplified 54.5%

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

   5. Taylor expanded in y3 around -inf 47.8%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 7.79999999999999967e202 < y2 < 1.8000000000000001e222

   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. Taylor expanded in c around inf 60.0%

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

      1. +-commutative 60.0%

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

      2. mul-1-neg 60.0%

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

      3. unsub-neg 60.0%

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

      4. *-commutative 60.0%

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

      5. *-commutative 60.0%

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

      6. *-commutative 60.0%

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

      7. *-commutative 60.0%

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

   4. Simplified 60.0%

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

   5. Taylor expanded in y4 around inf 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

   7. Simplified 100.0%

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

   if 1.8000000000000001e222 < y2

   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. Taylor expanded in c around inf 67.4%

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

      1. +-commutative 67.4%

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

      2. mul-1-neg 67.4%

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

      3. unsub-neg 67.4%

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

      4. *-commutative 67.4%

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

      5. *-commutative 67.4%

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

      6. *-commutative 67.4%

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

      7. *-commutative 67.4%

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

   4. Simplified 67.4%

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

   5. Taylor expanded in x around inf 73.8%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 50.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -7.5 \cdot 10^{+78}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -3.15 \cdot 10^{-218}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -4.6 \cdot 10^{-289}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 5.5 \cdot 10^{-307}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 4.8 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 2.4 \cdot 10^{+36}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{+97}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 3 \cdot 10^{+161}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 7.8 \cdot 10^{+202}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 1.8 \cdot 10^{+222}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 13: 32.9% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;z \leq -3.4 \cdot 10^{+149}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -7.6 \cdot 10^{+63}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -7.5 \cdot 10^{+39}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -1.14 \cdot 10^{-98}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -8.8 \cdot 10^{-217}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{-290}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 1.9 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 7.2 \cdot 10^{-129}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 4.7 \cdot 10^{+27}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* z (- (* b y0) (* i y1))))))
   (if (<= z -3.4e+149)
     t_1
     (if (<= z -7.6e+63)
       (* b (* y (- (* x a) (* k y4))))
       (if (<= z -7.5e+39)
         (* b (* x (- (* y a) (* j y0))))
         (if (<= z -1.14e-98)
           (* k (* y2 (- (* y1 y4) (* y0 y5))))
           (if (<= z -8.8e-217)
             (* k (* y (- (* i y5) (* b y4))))
             (if (<= z 1.55e-290)
               (* a (* y5 (- (* t y2) (* y y3))))
               (if (<= z 1.9e-226)
                 (* j (* x (- (* i y1) (* b y0))))
                 (if (<= z 7.2e-129)
                   (* c (* y4 (- (* y y3) (* t y2))))
                   (if (<= z 4.7e+27)
                     (* c (* x (- (* y0 y2) (* y i))))
                     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 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -3.4e+149) {
		tmp = t_1;
	} else if (z <= -7.6e+63) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (z <= -7.5e+39) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (z <= -1.14e-98) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -8.8e-217) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= 1.55e-290) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (z <= 1.9e-226) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= 7.2e-129) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (z <= 4.7e+27) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} 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 = k * (z * ((b * y0) - (i * y1)))
    if (z <= (-3.4d+149)) then
        tmp = t_1
    else if (z <= (-7.6d+63)) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (z <= (-7.5d+39)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (z <= (-1.14d-98)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (z <= (-8.8d-217)) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (z <= 1.55d-290) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (z <= 1.9d-226) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (z <= 7.2d-129) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (z <= 4.7d+27) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    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 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -3.4e+149) {
		tmp = t_1;
	} else if (z <= -7.6e+63) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (z <= -7.5e+39) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (z <= -1.14e-98) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -8.8e-217) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= 1.55e-290) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (z <= 1.9e-226) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= 7.2e-129) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (z <= 4.7e+27) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} 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 = k * (z * ((b * y0) - (i * y1)))
	tmp = 0
	if z <= -3.4e+149:
		tmp = t_1
	elif z <= -7.6e+63:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif z <= -7.5e+39:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif z <= -1.14e-98:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif z <= -8.8e-217:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif z <= 1.55e-290:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif z <= 1.9e-226:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif z <= 7.2e-129:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif z <= 4.7e+27:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	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(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))))
	tmp = 0.0
	if (z <= -3.4e+149)
		tmp = t_1;
	elseif (z <= -7.6e+63)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (z <= -7.5e+39)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (z <= -1.14e-98)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (z <= -8.8e-217)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (z <= 1.55e-290)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (z <= 1.9e-226)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (z <= 7.2e-129)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (z <= 4.7e+27)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	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 = k * (z * ((b * y0) - (i * y1)));
	tmp = 0.0;
	if (z <= -3.4e+149)
		tmp = t_1;
	elseif (z <= -7.6e+63)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (z <= -7.5e+39)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (z <= -1.14e-98)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (z <= -8.8e-217)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (z <= 1.55e-290)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (z <= 1.9e-226)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (z <= 7.2e-129)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (z <= 4.7e+27)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	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[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3.4e+149], t$95$1, If[LessEqual[z, -7.6e+63], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.5e+39], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.14e-98], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -8.8e-217], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.55e-290], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.9e-226], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7.2e-129], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.7e+27], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if z < -3.3999999999999998e149 or 4.69999999999999976e27 < z

   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. Taylor expanded in k around inf 38.9%

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

      1. sub-neg 38.9%

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

      2. +-commutative 38.9%

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

      3. mul-1-neg 38.9%

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

      4. unsub-neg 38.9%

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

      5. *-commutative 38.9%

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

      6. mul-1-neg 38.9%

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

      7. remove-double-neg 38.9%

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

   4. Simplified 38.9%

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

   5. Taylor expanded in z around inf 54.8%

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

      1. *-commutative 54.8%

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

      2. *-commutative 54.8%

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

      3. *-commutative 54.8%

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

      4. *-commutative 54.8%

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

   7. Simplified 54.8%

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

   if -3.3999999999999998e149 < z < -7.6000000000000002e63

   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. Taylor expanded in b around inf 71.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 58.2%

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

      1. +-commutative 58.2%

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

      2. mul-1-neg 58.2%

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

      3. unsub-neg 58.2%

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

      4. *-commutative 58.2%

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

      5. *-commutative 58.2%

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

   5. Simplified 58.2%

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

   if -7.6000000000000002e63 < z < -7.5000000000000005e39

   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. Taylor expanded in b around inf 38.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 51.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.5%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 51.5%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 51.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -7.5000000000000005e39 < z < -1.14000000000000006e-98

   1. Initial program 46.4%

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

   2. Taylor expanded in k around inf 39.8%

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

      1. sub-neg 39.8%

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

      2. +-commutative 39.8%

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

      3. mul-1-neg 39.8%

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

      4. unsub-neg 39.8%

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

      5. *-commutative 39.8%

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

      6. mul-1-neg 39.8%

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

      7. remove-double-neg 39.8%

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

   4. Simplified 39.8%

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

   5. Taylor expanded in y2 around inf 47.6%

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

   if -1.14000000000000006e-98 < z < -8.79999999999999927e-217

   1. Initial program 28.4%

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

   2. Taylor expanded in k around inf 53.1%

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

      1. sub-neg 53.1%

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

      2. +-commutative 53.1%

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

      3. mul-1-neg 53.1%

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

      4. unsub-neg 53.1%

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

      5. *-commutative 53.1%

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

      6. mul-1-neg 53.1%

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

      7. remove-double-neg 53.1%

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

   4. Simplified 53.1%

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

   5. Taylor expanded in y around inf 57.9%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 57.9%

         \[\leadsto k \cdot \left(y \cdot \left(\color{blue}{y5 \cdot i} - b \cdot y4\right)\right) \]

      2. *-commutative 57.9%

         \[\leadsto k \cdot \left(y \cdot \left(y5 \cdot i - \color{blue}{y4 \cdot b}\right)\right) \]

   7. Simplified 57.9%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(y5 \cdot i - y4 \cdot b\right)\right)} \]

   if -8.79999999999999927e-217 < z < 1.54999999999999995e-290

   1. Initial program 42.9%

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

   2. Taylor expanded in a around -inf 66.9%

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

      1. mul-1-neg 66.9%

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

      2. *-commutative 66.9%

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

      3. distribute-rgt-neg-in 66.9%

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

   4. Simplified 66.9%

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

   5. Taylor expanded in y5 around -inf 48.3%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.3%

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

      2. *-commutative 48.3%

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

   7. Simplified 48.3%

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

   if 1.54999999999999995e-290 < z < 1.89999999999999991e-226

   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. Taylor expanded in x around inf 46.4%

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

   3. Taylor expanded in j around inf 51.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.0%

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

      2. *-commutative 51.0%

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

   5. Simplified 51.0%

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

   if 1.89999999999999991e-226 < z < 7.2e-129

   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. Taylor expanded in c around inf 48.2%

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

      1. +-commutative 48.2%

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

      2. mul-1-neg 48.2%

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

      3. unsub-neg 48.2%

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

      4. *-commutative 48.2%

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

      5. *-commutative 48.2%

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

      6. *-commutative 48.2%

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

      7. *-commutative 48.2%

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

   4. Simplified 48.2%

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

   5. Taylor expanded in y4 around inf 48.4%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.4%

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

      2. *-commutative 48.4%

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

   7. Simplified 48.4%

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

   if 7.2e-129 < z < 4.69999999999999976e27

   1. Initial program 30.5%

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

   2. Taylor expanded in c around inf 43.8%

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

      1. +-commutative 43.8%

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

      2. mul-1-neg 43.8%

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

      3. unsub-neg 43.8%

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

      4. *-commutative 43.8%

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

      5. *-commutative 43.8%

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

      6. *-commutative 43.8%

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

      7. *-commutative 43.8%

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

   4. Simplified 43.8%

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

   5. Taylor expanded in x around inf 47.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 52.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.4 \cdot 10^{+149}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -7.6 \cdot 10^{+63}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -7.5 \cdot 10^{+39}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -1.14 \cdot 10^{-98}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -8.8 \cdot 10^{-217}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{-290}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 1.9 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 7.2 \cdot 10^{-129}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 4.7 \cdot 10^{+27}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]

Alternative 14: 31.4% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;y2 \leq -2.3 \cdot 10^{+79}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -1.35 \cdot 10^{-226}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -1.1 \cdot 10^{-269}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 2.8 \cdot 10^{-307}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y2 \leq 3 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 5 \cdot 10^{+35}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 10^{+98}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 1.1 \cdot 10^{+132}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 9 \cdot 10^{+230}:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= y2 -2.3e+79)
     t_1
     (if (<= y2 -1.35e-226)
       (* b (* x (- (* y a) (* j y0))))
       (if (<= y2 -1.1e-269)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= y2 2.8e-307)
           (* y0 (* y3 (- (* j y5) (* z c))))
           (if (<= y2 3e-104)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= y2 5e+35)
               t_1
               (if (<= y2 1e+98)
                 (* b (* y (- (* x a) (* k y4))))
                 (if (<= y2 1.1e+132)
                   (* a (* y3 (- (* z y1) (* y y5))))
                   (if (<= y2 9e+230)
                     (* a (* y2 (- (* t y5) (* x y1))))
                     (* y0 (* y2 (- (* x c) (* k 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -2.3e+79) {
		tmp = t_1;
	} else if (y2 <= -1.35e-226) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -1.1e-269) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 2.8e-307) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y2 <= 3e-104) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y2 <= 5e+35) {
		tmp = t_1;
	} else if (y2 <= 1e+98) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 1.1e+132) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 9e+230) {
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * 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) :: tmp
    t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (y2 <= (-2.3d+79)) then
        tmp = t_1
    else if (y2 <= (-1.35d-226)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y2 <= (-1.1d-269)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y2 <= 2.8d-307) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (y2 <= 3d-104) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y2 <= 5d+35) then
        tmp = t_1
    else if (y2 <= 1d+98) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (y2 <= 1.1d+132) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y2 <= 9d+230) then
        tmp = a * (y2 * ((t * y5) - (x * y1)))
    else
        tmp = y0 * (y2 * ((x * c) - (k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -2.3e+79) {
		tmp = t_1;
	} else if (y2 <= -1.35e-226) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -1.1e-269) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 2.8e-307) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y2 <= 3e-104) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y2 <= 5e+35) {
		tmp = t_1;
	} else if (y2 <= 1e+98) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 1.1e+132) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 9e+230) {
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if y2 <= -2.3e+79:
		tmp = t_1
	elif y2 <= -1.35e-226:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y2 <= -1.1e-269:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y2 <= 2.8e-307:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif y2 <= 3e-104:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y2 <= 5e+35:
		tmp = t_1
	elif y2 <= 1e+98:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif y2 <= 1.1e+132:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y2 <= 9e+230:
		tmp = a * (y2 * ((t * y5) - (x * y1)))
	else:
		tmp = y0 * (y2 * ((x * c) - (k * 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(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (y2 <= -2.3e+79)
		tmp = t_1;
	elseif (y2 <= -1.35e-226)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y2 <= -1.1e-269)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y2 <= 2.8e-307)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (y2 <= 3e-104)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y2 <= 5e+35)
		tmp = t_1;
	elseif (y2 <= 1e+98)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (y2 <= 1.1e+132)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y2 <= 9e+230)
		tmp = Float64(a * Float64(y2 * Float64(Float64(t * y5) - Float64(x * y1))));
	else
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (y2 <= -2.3e+79)
		tmp = t_1;
	elseif (y2 <= -1.35e-226)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y2 <= -1.1e-269)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y2 <= 2.8e-307)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (y2 <= 3e-104)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y2 <= 5e+35)
		tmp = t_1;
	elseif (y2 <= 1e+98)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (y2 <= 1.1e+132)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y2 <= 9e+230)
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	else
		tmp = y0 * (y2 * ((x * c) - (k * 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[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -2.3e+79], t$95$1, If[LessEqual[y2, -1.35e-226], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -1.1e-269], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 2.8e-307], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 3e-104], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5e+35], t$95$1, If[LessEqual[y2, 1e+98], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 1.1e+132], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 9e+230], N[(a * N[(y2 * N[(N[(t * y5), $MachinePrecision] - N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y2 < -2.3e79 or 3.0000000000000002e-104 < y2 < 5.00000000000000021e35

   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. Taylor expanded in k around inf 44.4%

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

      1. sub-neg 44.4%

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

      2. +-commutative 44.4%

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

      3. mul-1-neg 44.4%

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

      4. unsub-neg 44.4%

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

      5. *-commutative 44.4%

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

      6. mul-1-neg 44.4%

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

      7. remove-double-neg 44.4%

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

   4. Simplified 44.4%

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

   5. Taylor expanded in y2 around inf 46.3%

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

   if -2.3e79 < y2 < -1.35000000000000007e-226

   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. Taylor expanded in b around inf 46.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 42.0%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.0%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 42.0%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 42.0%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -1.35000000000000007e-226 < y2 < -1.09999999999999992e-269

   1. Initial program 27.3%

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

   2. Taylor expanded in t around inf 46.3%

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

   3. Taylor expanded in j around inf 64.6%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.09999999999999992e-269 < y2 < 2.8e-307

   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. Taylor expanded in y0 around inf 56.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 56.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 56.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 56.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y3 around inf 89.0%

      \[\leadsto y0 \cdot \color{blue}{\left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) - -1 \cdot \left(j \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. sub-neg 89.0%

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

      2. mul-1-neg 89.0%

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

      3. remove-double-neg 89.0%

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

      4. +-commutative 89.0%

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

      5. mul-1-neg 89.0%

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

      6. unsub-neg 89.0%

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

   7. Simplified 89.0%

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

   if 2.8e-307 < y2 < 3.0000000000000002e-104

   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. Taylor expanded in x around inf 47.4%

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

   3. Taylor expanded in j around inf 45.8%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 45.8%

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

      2. *-commutative 45.8%

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

   5. Simplified 45.8%

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

   if 5.00000000000000021e35 < y2 < 9.99999999999999998e97

   1. Initial program 15.3%

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

   2. Taylor expanded in b around inf 16.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 61.8%

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

      1. +-commutative 61.8%

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

      2. mul-1-neg 61.8%

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

      3. unsub-neg 61.8%

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

      4. *-commutative 61.8%

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

      5. *-commutative 61.8%

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

   5. Simplified 61.8%

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

   if 9.99999999999999998e97 < y2 < 1.09999999999999994e132

   1. Initial program 11.1%

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

   2. Taylor expanded in a around -inf 46.1%

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

      1. mul-1-neg 46.1%

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

      2. *-commutative 46.1%

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

      3. distribute-rgt-neg-in 46.1%

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

   4. Simplified 46.1%

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

   5. Taylor expanded in y3 around -inf 56.3%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 1.09999999999999994e132 < y2 < 8.9999999999999998e230

   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. Taylor expanded in a around -inf 45.2%

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

      1. mul-1-neg 45.2%

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

      2. *-commutative 45.2%

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

      3. distribute-rgt-neg-in 45.2%

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

   4. Simplified 45.2%

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

   5. Taylor expanded in y2 around inf 60.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y2 \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 60.7%

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

      2. neg-mul-1 60.7%

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

   7. Simplified 60.7%

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

   if 8.9999999999999998e230 < y2

   1. Initial program 30.8%

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

   2. Taylor expanded in y0 around inf 69.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 69.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 69.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 69.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y2 around inf 92.3%

      \[\leadsto \color{blue}{y0 \cdot \left(y2 \cdot \left(c \cdot x - k \cdot y5\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 52.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -2.3 \cdot 10^{+79}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -1.35 \cdot 10^{-226}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -1.1 \cdot 10^{-269}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 2.8 \cdot 10^{-307}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y2 \leq 3 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 5 \cdot 10^{+35}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 10^{+98}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 1.1 \cdot 10^{+132}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 9 \cdot 10^{+230}:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \]

Alternative 15: 29.0% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_2 := c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{if}\;y2 \leq -4 \cdot 10^{+149}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq -2.3 \cdot 10^{-31}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq -1.85 \cdot 10^{-217}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -1.35 \cdot 10^{-289}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 1.5 \cdot 10^{-121}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 6.2 \cdot 10^{+155}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 5 \cdot 10^{+203}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 2.25 \cdot 10^{+223}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* x (- (* i y1) (* b y0)))))
        (t_2 (* c (* x (- (* y0 y2) (* y i))))))
   (if (<= y2 -4e+149)
     t_2
     (if (<= y2 -2.3e-31)
       (* b (* y (- (* x a) (* k y4))))
       (if (<= y2 -1.85e-217)
         (* b (* x (- (* y a) (* j y0))))
         (if (<= y2 -1.35e-289)
           (* j (* t (- (* b y4) (* i y5))))
           (if (<= y2 1.5e-121)
             t_1
             (if (<= y2 6.2e+155)
               (* a (* y3 (- (* z y1) (* y y5))))
               (if (<= y2 5e+203)
                 t_1
                 (if (<= y2 2.25e+223)
                   (* c (* y4 (- (* y y3) (* t 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 = j * (x * ((i * y1) - (b * y0)));
	double t_2 = c * (x * ((y0 * y2) - (y * i)));
	double tmp;
	if (y2 <= -4e+149) {
		tmp = t_2;
	} else if (y2 <= -2.3e-31) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= -1.85e-217) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -1.35e-289) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 1.5e-121) {
		tmp = t_1;
	} else if (y2 <= 6.2e+155) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 5e+203) {
		tmp = t_1;
	} else if (y2 <= 2.25e+223) {
		tmp = c * (y4 * ((y * y3) - (t * 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 = j * (x * ((i * y1) - (b * y0)))
    t_2 = c * (x * ((y0 * y2) - (y * i)))
    if (y2 <= (-4d+149)) then
        tmp = t_2
    else if (y2 <= (-2.3d-31)) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (y2 <= (-1.85d-217)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y2 <= (-1.35d-289)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y2 <= 1.5d-121) then
        tmp = t_1
    else if (y2 <= 6.2d+155) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y2 <= 5d+203) then
        tmp = t_1
    else if (y2 <= 2.25d+223) then
        tmp = c * (y4 * ((y * y3) - (t * 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 = j * (x * ((i * y1) - (b * y0)));
	double t_2 = c * (x * ((y0 * y2) - (y * i)));
	double tmp;
	if (y2 <= -4e+149) {
		tmp = t_2;
	} else if (y2 <= -2.3e-31) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= -1.85e-217) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -1.35e-289) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 1.5e-121) {
		tmp = t_1;
	} else if (y2 <= 6.2e+155) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 5e+203) {
		tmp = t_1;
	} else if (y2 <= 2.25e+223) {
		tmp = c * (y4 * ((y * y3) - (t * 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 = j * (x * ((i * y1) - (b * y0)))
	t_2 = c * (x * ((y0 * y2) - (y * i)))
	tmp = 0
	if y2 <= -4e+149:
		tmp = t_2
	elif y2 <= -2.3e-31:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif y2 <= -1.85e-217:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y2 <= -1.35e-289:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y2 <= 1.5e-121:
		tmp = t_1
	elif y2 <= 6.2e+155:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y2 <= 5e+203:
		tmp = t_1
	elif y2 <= 2.25e+223:
		tmp = c * (y4 * ((y * y3) - (t * 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(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))))
	t_2 = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))))
	tmp = 0.0
	if (y2 <= -4e+149)
		tmp = t_2;
	elseif (y2 <= -2.3e-31)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (y2 <= -1.85e-217)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y2 <= -1.35e-289)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y2 <= 1.5e-121)
		tmp = t_1;
	elseif (y2 <= 6.2e+155)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y2 <= 5e+203)
		tmp = t_1;
	elseif (y2 <= 2.25e+223)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = j * (x * ((i * y1) - (b * y0)));
	t_2 = c * (x * ((y0 * y2) - (y * i)));
	tmp = 0.0;
	if (y2 <= -4e+149)
		tmp = t_2;
	elseif (y2 <= -2.3e-31)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (y2 <= -1.85e-217)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y2 <= -1.35e-289)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y2 <= 1.5e-121)
		tmp = t_1;
	elseif (y2 <= 6.2e+155)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y2 <= 5e+203)
		tmp = t_1;
	elseif (y2 <= 2.25e+223)
		tmp = c * (y4 * ((y * y3) - (t * 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[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -4e+149], t$95$2, If[LessEqual[y2, -2.3e-31], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -1.85e-217], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -1.35e-289], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 1.5e-121], t$95$1, If[LessEqual[y2, 6.2e+155], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5e+203], t$95$1, If[LessEqual[y2, 2.25e+223], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y2 < -4.0000000000000002e149 or 2.25e223 < y2

   1. Initial program 30.8%

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

   2. Taylor expanded in c around inf 57.2%

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

      1. +-commutative 57.2%

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

      2. mul-1-neg 57.2%

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

      3. unsub-neg 57.2%

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

      4. *-commutative 57.2%

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

      5. *-commutative 57.2%

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

      6. *-commutative 57.2%

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

      7. *-commutative 57.2%

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

   4. Simplified 57.2%

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

   5. Taylor expanded in x around inf 55.0%

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

   if -4.0000000000000002e149 < y2 < -2.2999999999999998e-31

   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. Taylor expanded in b around inf 45.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 45.9%

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

      1. +-commutative 45.9%

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

      2. mul-1-neg 45.9%

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

      3. unsub-neg 45.9%

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

      4. *-commutative 45.9%

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

      5. *-commutative 45.9%

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

   5. Simplified 45.9%

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

   if -2.2999999999999998e-31 < y2 < -1.8499999999999998e-217

   1. Initial program 28.7%

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

   2. Taylor expanded in b around inf 45.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 41.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.5%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 41.5%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 41.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -1.8499999999999998e-217 < y2 < -1.35e-289

   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. Taylor expanded in t around inf 50.7%

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

   3. Taylor expanded in j around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.35e-289 < y2 < 1.5e-121 or 6.19999999999999978e155 < y2 < 4.99999999999999994e203

   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. Taylor expanded in x around inf 48.8%

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

   3. Taylor expanded in j around inf 49.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 49.5%

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

      2. *-commutative 49.5%

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

   5. Simplified 49.5%

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

   if 1.5e-121 < y2 < 6.19999999999999978e155

   1. Initial program 26.3%

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

   2. Taylor expanded in a around -inf 43.6%

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

      1. mul-1-neg 43.6%

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

      2. *-commutative 43.6%

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

      3. distribute-rgt-neg-in 43.6%

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

   4. Simplified 43.6%

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

   5. Taylor expanded in y3 around -inf 38.4%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 4.99999999999999994e203 < y2 < 2.25e223

   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. Taylor expanded in c around inf 60.0%

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

      1. +-commutative 60.0%

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

      2. mul-1-neg 60.0%

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

      3. unsub-neg 60.0%

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

      4. *-commutative 60.0%

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

      5. *-commutative 60.0%

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

      6. *-commutative 60.0%

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

      7. *-commutative 60.0%

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

   4. Simplified 60.0%

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

   5. Taylor expanded in y4 around inf 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

   7. Simplified 100.0%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -4 \cdot 10^{+149}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;y2 \leq -2.3 \cdot 10^{-31}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq -1.85 \cdot 10^{-217}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -1.35 \cdot 10^{-289}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 1.5 \cdot 10^{-121}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 6.2 \cdot 10^{+155}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 5 \cdot 10^{+203}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 2.25 \cdot 10^{+223}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 16: 33.2% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;z \leq -4.4 \cdot 10^{+173}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1.55 \cdot 10^{+53}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq -2.4 \cdot 10^{-98}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -4.1 \cdot 10^{-216}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-291}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 1.5 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-128}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{+28}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* z (- (* b y0) (* i y1))))))
   (if (<= z -4.4e+173)
     t_1
     (if (<= z -1.55e+53)
       (* y0 (* b (- (* z k) (* x j))))
       (if (<= z -2.4e-98)
         (* k (* y2 (- (* y1 y4) (* y0 y5))))
         (if (<= z -4.1e-216)
           (* k (* y (- (* i y5) (* b y4))))
           (if (<= z 7e-291)
             (* a (* y5 (- (* t y2) (* y y3))))
             (if (<= z 1.5e-226)
               (* j (* x (- (* i y1) (* b y0))))
               (if (<= z 1.35e-128)
                 (* c (* y4 (- (* y y3) (* t y2))))
                 (if (<= z 1.55e+28)
                   (* c (* x (- (* y0 y2) (* y i))))
                   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 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -4.4e+173) {
		tmp = t_1;
	} else if (z <= -1.55e+53) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else if (z <= -2.4e-98) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -4.1e-216) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= 7e-291) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (z <= 1.5e-226) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= 1.35e-128) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (z <= 1.55e+28) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} 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 = k * (z * ((b * y0) - (i * y1)))
    if (z <= (-4.4d+173)) then
        tmp = t_1
    else if (z <= (-1.55d+53)) then
        tmp = y0 * (b * ((z * k) - (x * j)))
    else if (z <= (-2.4d-98)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (z <= (-4.1d-216)) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (z <= 7d-291) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (z <= 1.5d-226) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (z <= 1.35d-128) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (z <= 1.55d+28) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    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 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -4.4e+173) {
		tmp = t_1;
	} else if (z <= -1.55e+53) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else if (z <= -2.4e-98) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -4.1e-216) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= 7e-291) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (z <= 1.5e-226) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= 1.35e-128) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (z <= 1.55e+28) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} 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 = k * (z * ((b * y0) - (i * y1)))
	tmp = 0
	if z <= -4.4e+173:
		tmp = t_1
	elif z <= -1.55e+53:
		tmp = y0 * (b * ((z * k) - (x * j)))
	elif z <= -2.4e-98:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif z <= -4.1e-216:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif z <= 7e-291:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif z <= 1.5e-226:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif z <= 1.35e-128:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif z <= 1.55e+28:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	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(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))))
	tmp = 0.0
	if (z <= -4.4e+173)
		tmp = t_1;
	elseif (z <= -1.55e+53)
		tmp = Float64(y0 * Float64(b * Float64(Float64(z * k) - Float64(x * j))));
	elseif (z <= -2.4e-98)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (z <= -4.1e-216)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (z <= 7e-291)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (z <= 1.5e-226)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (z <= 1.35e-128)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (z <= 1.55e+28)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	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 = k * (z * ((b * y0) - (i * y1)));
	tmp = 0.0;
	if (z <= -4.4e+173)
		tmp = t_1;
	elseif (z <= -1.55e+53)
		tmp = y0 * (b * ((z * k) - (x * j)));
	elseif (z <= -2.4e-98)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (z <= -4.1e-216)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (z <= 7e-291)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (z <= 1.5e-226)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (z <= 1.35e-128)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (z <= 1.55e+28)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	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[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -4.4e+173], t$95$1, If[LessEqual[z, -1.55e+53], N[(y0 * N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.4e-98], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -4.1e-216], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7e-291], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.5e-226], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.35e-128], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.55e+28], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if z < -4.4e173 or 1.55e28 < z

   1. Initial program 25.5%

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

   2. Taylor expanded in k around inf 39.3%

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

      1. sub-neg 39.3%

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

      2. +-commutative 39.3%

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

      3. mul-1-neg 39.3%

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

      4. unsub-neg 39.3%

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

      5. *-commutative 39.3%

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

      6. mul-1-neg 39.3%

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

      7. remove-double-neg 39.3%

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

   4. Simplified 39.3%

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

   5. Taylor expanded in z around inf 55.1%

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

      1. *-commutative 55.1%

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

      2. *-commutative 55.1%

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

      3. *-commutative 55.1%

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

      4. *-commutative 55.1%

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

   7. Simplified 55.1%

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

   if -4.4e173 < z < -1.5500000000000001e53

   1. Initial program 30.8%

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

   2. Taylor expanded in y0 around inf 60.7%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 60.7%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 60.7%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 60.7%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 60.7%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 60.7%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 60.7%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 60.7%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 60.7%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in b around inf 65.2%

      \[\leadsto y0 \cdot \color{blue}{\left(b \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 65.2%

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

      2. *-commutative 65.2%

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

   7. Simplified 65.2%

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

   if -1.5500000000000001e53 < z < -2.40000000000000005e-98

   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. Taylor expanded in k around inf 37.0%

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

      1. sub-neg 37.0%

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

      2. +-commutative 37.0%

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

      3. mul-1-neg 37.0%

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

      4. unsub-neg 37.0%

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

      5. *-commutative 37.0%

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

      6. mul-1-neg 37.0%

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

      7. remove-double-neg 37.0%

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

   4. Simplified 37.0%

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

   5. Taylor expanded in y2 around inf 43.5%

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

   if -2.40000000000000005e-98 < z < -4.10000000000000024e-216

   1. Initial program 28.4%

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

   2. Taylor expanded in k around inf 53.1%

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

      1. sub-neg 53.1%

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

      2. +-commutative 53.1%

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

      3. mul-1-neg 53.1%

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

      4. unsub-neg 53.1%

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

      5. *-commutative 53.1%

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

      6. mul-1-neg 53.1%

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

      7. remove-double-neg 53.1%

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

   4. Simplified 53.1%

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

   5. Taylor expanded in y around inf 57.9%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 57.9%

         \[\leadsto k \cdot \left(y \cdot \left(\color{blue}{y5 \cdot i} - b \cdot y4\right)\right) \]

      2. *-commutative 57.9%

         \[\leadsto k \cdot \left(y \cdot \left(y5 \cdot i - \color{blue}{y4 \cdot b}\right)\right) \]

   7. Simplified 57.9%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(y5 \cdot i - y4 \cdot b\right)\right)} \]

   if -4.10000000000000024e-216 < z < 6.99999999999999991e-291

   1. Initial program 42.9%

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

   2. Taylor expanded in a around -inf 66.9%

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

      1. mul-1-neg 66.9%

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

      2. *-commutative 66.9%

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

      3. distribute-rgt-neg-in 66.9%

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

   4. Simplified 66.9%

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

   5. Taylor expanded in y5 around -inf 48.3%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.3%

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

      2. *-commutative 48.3%

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

   7. Simplified 48.3%

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

   if 6.99999999999999991e-291 < z < 1.49999999999999998e-226

   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. Taylor expanded in x around inf 46.4%

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

   3. Taylor expanded in j around inf 51.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.0%

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

      2. *-commutative 51.0%

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

   5. Simplified 51.0%

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

   if 1.49999999999999998e-226 < z < 1.35000000000000003e-128

   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. Taylor expanded in c around inf 48.2%

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

      1. +-commutative 48.2%

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

      2. mul-1-neg 48.2%

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

      3. unsub-neg 48.2%

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

      4. *-commutative 48.2%

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

      5. *-commutative 48.2%

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

      6. *-commutative 48.2%

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

      7. *-commutative 48.2%

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

   4. Simplified 48.2%

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

   5. Taylor expanded in y4 around inf 48.4%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.4%

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

      2. *-commutative 48.4%

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

   7. Simplified 48.4%

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

   if 1.35000000000000003e-128 < z < 1.55e28

   1. Initial program 30.5%

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

   2. Taylor expanded in c around inf 43.8%

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

      1. +-commutative 43.8%

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

      2. mul-1-neg 43.8%

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

      3. unsub-neg 43.8%

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

      4. *-commutative 43.8%

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

      5. *-commutative 43.8%

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

      6. *-commutative 43.8%

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

      7. *-commutative 43.8%

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

   4. Simplified 43.8%

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

   5. Taylor expanded in x around inf 47.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 52.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -4.4 \cdot 10^{+173}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.55 \cdot 10^{+53}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq -2.4 \cdot 10^{-98}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -4.1 \cdot 10^{-216}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-291}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 1.5 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-128}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{+28}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]

Alternative 17: 33.2% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;z \leq -7.6 \cdot 10^{+171}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -8.8 \cdot 10^{+48}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq -5.4 \cdot 10^{-97}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -2.15 \cdot 10^{-217}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{-282}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 1.95 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 3.2 \cdot 10^{-126}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 9.8 \cdot 10^{+27}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* z (- (* b y0) (* i y1))))))
   (if (<= z -7.6e+171)
     t_1
     (if (<= z -8.8e+48)
       (* y0 (* b (- (* z k) (* x j))))
       (if (<= z -5.4e-97)
         (* y0 (* y2 (- (* x c) (* k y5))))
         (if (<= z -2.15e-217)
           (* k (* y (- (* i y5) (* b y4))))
           (if (<= z 1.05e-282)
             (* a (* y5 (- (* t y2) (* y y3))))
             (if (<= z 1.95e-226)
               (* j (* x (- (* i y1) (* b y0))))
               (if (<= z 3.2e-126)
                 (* c (* y4 (- (* y y3) (* t y2))))
                 (if (<= z 9.8e+27)
                   (* c (* x (- (* y0 y2) (* y i))))
                   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 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -7.6e+171) {
		tmp = t_1;
	} else if (z <= -8.8e+48) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else if (z <= -5.4e-97) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (z <= -2.15e-217) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= 1.05e-282) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (z <= 1.95e-226) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= 3.2e-126) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (z <= 9.8e+27) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} 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 = k * (z * ((b * y0) - (i * y1)))
    if (z <= (-7.6d+171)) then
        tmp = t_1
    else if (z <= (-8.8d+48)) then
        tmp = y0 * (b * ((z * k) - (x * j)))
    else if (z <= (-5.4d-97)) then
        tmp = y0 * (y2 * ((x * c) - (k * y5)))
    else if (z <= (-2.15d-217)) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (z <= 1.05d-282) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (z <= 1.95d-226) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (z <= 3.2d-126) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (z <= 9.8d+27) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    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 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -7.6e+171) {
		tmp = t_1;
	} else if (z <= -8.8e+48) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else if (z <= -5.4e-97) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (z <= -2.15e-217) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= 1.05e-282) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (z <= 1.95e-226) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= 3.2e-126) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (z <= 9.8e+27) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} 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 = k * (z * ((b * y0) - (i * y1)))
	tmp = 0
	if z <= -7.6e+171:
		tmp = t_1
	elif z <= -8.8e+48:
		tmp = y0 * (b * ((z * k) - (x * j)))
	elif z <= -5.4e-97:
		tmp = y0 * (y2 * ((x * c) - (k * y5)))
	elif z <= -2.15e-217:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif z <= 1.05e-282:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif z <= 1.95e-226:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif z <= 3.2e-126:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif z <= 9.8e+27:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	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(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))))
	tmp = 0.0
	if (z <= -7.6e+171)
		tmp = t_1;
	elseif (z <= -8.8e+48)
		tmp = Float64(y0 * Float64(b * Float64(Float64(z * k) - Float64(x * j))));
	elseif (z <= -5.4e-97)
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (z <= -2.15e-217)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (z <= 1.05e-282)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (z <= 1.95e-226)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (z <= 3.2e-126)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (z <= 9.8e+27)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	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 = k * (z * ((b * y0) - (i * y1)));
	tmp = 0.0;
	if (z <= -7.6e+171)
		tmp = t_1;
	elseif (z <= -8.8e+48)
		tmp = y0 * (b * ((z * k) - (x * j)));
	elseif (z <= -5.4e-97)
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	elseif (z <= -2.15e-217)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (z <= 1.05e-282)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (z <= 1.95e-226)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (z <= 3.2e-126)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (z <= 9.8e+27)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	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[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -7.6e+171], t$95$1, If[LessEqual[z, -8.8e+48], N[(y0 * N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -5.4e-97], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.15e-217], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.05e-282], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.95e-226], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.2e-126], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.8e+27], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if z < -7.6000000000000004e171 or 9.8000000000000003e27 < z

   1. Initial program 25.5%

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

   2. Taylor expanded in k around inf 39.3%

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

      1. sub-neg 39.3%

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

      2. +-commutative 39.3%

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

      3. mul-1-neg 39.3%

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

      4. unsub-neg 39.3%

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

      5. *-commutative 39.3%

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

      6. mul-1-neg 39.3%

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

      7. remove-double-neg 39.3%

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

   4. Simplified 39.3%

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

   5. Taylor expanded in z around inf 55.1%

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

      1. *-commutative 55.1%

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

      2. *-commutative 55.1%

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

      3. *-commutative 55.1%

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

      4. *-commutative 55.1%

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

   7. Simplified 55.1%

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

   if -7.6000000000000004e171 < z < -8.7999999999999997e48

   1. Initial program 28.3%

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

   2. Taylor expanded in y0 around inf 55.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 55.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 55.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 55.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 55.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 55.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 55.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 55.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 55.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in b around inf 63.9%

      \[\leadsto y0 \cdot \color{blue}{\left(b \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 63.9%

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

      2. *-commutative 63.9%

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

   7. Simplified 63.9%

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

   if -8.7999999999999997e48 < z < -5.3999999999999997e-97

   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. Taylor expanded in y0 around inf 48.9%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 48.9%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 48.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 48.9%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 48.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 48.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 48.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 48.9%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 48.9%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y2 around inf 46.0%

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

   if -5.3999999999999997e-97 < z < -2.15000000000000011e-217

   1. Initial program 28.4%

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

   2. Taylor expanded in k around inf 53.1%

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

      1. sub-neg 53.1%

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

      2. +-commutative 53.1%

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

      3. mul-1-neg 53.1%

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

      4. unsub-neg 53.1%

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

      5. *-commutative 53.1%

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

      6. mul-1-neg 53.1%

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

      7. remove-double-neg 53.1%

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

   4. Simplified 53.1%

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

   5. Taylor expanded in y around inf 57.9%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 57.9%

         \[\leadsto k \cdot \left(y \cdot \left(\color{blue}{y5 \cdot i} - b \cdot y4\right)\right) \]

      2. *-commutative 57.9%

         \[\leadsto k \cdot \left(y \cdot \left(y5 \cdot i - \color{blue}{y4 \cdot b}\right)\right) \]

   7. Simplified 57.9%

      \[\leadsto \color{blue}{k \cdot \left(y \cdot \left(y5 \cdot i - y4 \cdot b\right)\right)} \]

   if -2.15000000000000011e-217 < z < 1.05000000000000006e-282

   1. Initial program 43.5%

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

   2. Taylor expanded in a around -inf 61.2%

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

      1. mul-1-neg 61.2%

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

      2. *-commutative 61.2%

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

      3. distribute-rgt-neg-in 61.2%

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

   4. Simplified 61.2%

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

   5. Taylor expanded in y5 around -inf 44.2%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 44.2%

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

      2. *-commutative 44.2%

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

   7. Simplified 44.2%

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

   if 1.05000000000000006e-282 < z < 1.9499999999999999e-226

   1. Initial program 29.9%

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

   2. Taylor expanded in x around inf 46.0%

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

   3. Taylor expanded in j around inf 56.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 56.1%

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

      2. *-commutative 56.1%

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

   5. Simplified 56.1%

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

   if 1.9499999999999999e-226 < z < 3.2000000000000001e-126

   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. Taylor expanded in c around inf 48.2%

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

      1. +-commutative 48.2%

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

      2. mul-1-neg 48.2%

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

      3. unsub-neg 48.2%

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

      4. *-commutative 48.2%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      5. *-commutative 48.2%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      6. *-commutative 48.2%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(\color{blue}{y \cdot x} - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      7. *-commutative 48.2%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) \]

   4. Simplified 48.2%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]

   5. Taylor expanded in y4 around inf 48.4%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.4%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 48.4%

         \[\leadsto c \cdot \left(y4 \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   7. Simplified 48.4%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   if 3.2000000000000001e-126 < z < 9.8000000000000003e27

   1. Initial program 30.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 43.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 43.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      2. mul-1-neg 43.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)}\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      3. unsub-neg 43.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      4. *-commutative 43.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      5. *-commutative 43.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      6. *-commutative 43.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(\color{blue}{y \cdot x} - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      7. *-commutative 43.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) \]

   4. Simplified 43.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]

   5. Taylor expanded in x around inf 47.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 52.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7.6 \cdot 10^{+171}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -8.8 \cdot 10^{+48}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq -5.4 \cdot 10^{-97}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -2.15 \cdot 10^{-217}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{-282}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 1.95 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 3.2 \cdot 10^{-126}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 9.8 \cdot 10^{+27}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]

Alternative 18: 30.7% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;y2 \leq -2.9 \cdot 10^{+78}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -1.35 \cdot 10^{-223}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -9.4 \cdot 10^{-271}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 3.8 \cdot 10^{-307}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y2 \leq 4.4 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 1.8 \cdot 10^{+40}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 1.1 \cdot 10^{+98}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 3.8 \cdot 10^{+202}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= y2 -2.9e+78)
     t_1
     (if (<= y2 -1.35e-223)
       (* b (* x (- (* y a) (* j y0))))
       (if (<= y2 -9.4e-271)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= y2 3.8e-307)
           (* y0 (* y3 (- (* j y5) (* z c))))
           (if (<= y2 4.4e-104)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= y2 1.8e+40)
               t_1
               (if (<= y2 1.1e+98)
                 (* b (* y (- (* x a) (* k y4))))
                 (if (<= y2 3.8e+202)
                   (* y0 (* b (- (* z k) (* x j))))
                   (* y0 (* y2 (- (* x c) (* k 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -2.9e+78) {
		tmp = t_1;
	} else if (y2 <= -1.35e-223) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -9.4e-271) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 3.8e-307) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y2 <= 4.4e-104) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y2 <= 1.8e+40) {
		tmp = t_1;
	} else if (y2 <= 1.1e+98) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 3.8e+202) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * 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) :: tmp
    t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (y2 <= (-2.9d+78)) then
        tmp = t_1
    else if (y2 <= (-1.35d-223)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y2 <= (-9.4d-271)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y2 <= 3.8d-307) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (y2 <= 4.4d-104) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y2 <= 1.8d+40) then
        tmp = t_1
    else if (y2 <= 1.1d+98) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (y2 <= 3.8d+202) then
        tmp = y0 * (b * ((z * k) - (x * j)))
    else
        tmp = y0 * (y2 * ((x * c) - (k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -2.9e+78) {
		tmp = t_1;
	} else if (y2 <= -1.35e-223) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= -9.4e-271) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y2 <= 3.8e-307) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y2 <= 4.4e-104) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y2 <= 1.8e+40) {
		tmp = t_1;
	} else if (y2 <= 1.1e+98) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 3.8e+202) {
		tmp = y0 * (b * ((z * k) - (x * j)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if y2 <= -2.9e+78:
		tmp = t_1
	elif y2 <= -1.35e-223:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y2 <= -9.4e-271:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y2 <= 3.8e-307:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif y2 <= 4.4e-104:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y2 <= 1.8e+40:
		tmp = t_1
	elif y2 <= 1.1e+98:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif y2 <= 3.8e+202:
		tmp = y0 * (b * ((z * k) - (x * j)))
	else:
		tmp = y0 * (y2 * ((x * c) - (k * 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(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (y2 <= -2.9e+78)
		tmp = t_1;
	elseif (y2 <= -1.35e-223)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y2 <= -9.4e-271)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y2 <= 3.8e-307)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (y2 <= 4.4e-104)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y2 <= 1.8e+40)
		tmp = t_1;
	elseif (y2 <= 1.1e+98)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (y2 <= 3.8e+202)
		tmp = Float64(y0 * Float64(b * Float64(Float64(z * k) - Float64(x * j))));
	else
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (y2 <= -2.9e+78)
		tmp = t_1;
	elseif (y2 <= -1.35e-223)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y2 <= -9.4e-271)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y2 <= 3.8e-307)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (y2 <= 4.4e-104)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y2 <= 1.8e+40)
		tmp = t_1;
	elseif (y2 <= 1.1e+98)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (y2 <= 3.8e+202)
		tmp = y0 * (b * ((z * k) - (x * j)));
	else
		tmp = y0 * (y2 * ((x * c) - (k * 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[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -2.9e+78], t$95$1, If[LessEqual[y2, -1.35e-223], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -9.4e-271], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 3.8e-307], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.4e-104], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 1.8e+40], t$95$1, If[LessEqual[y2, 1.1e+98], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 3.8e+202], N[(y0 * N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y2 < -2.90000000000000017e78 or 4.40000000000000023e-104 < y2 < 1.79999999999999998e40

   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. Taylor expanded in k around inf 44.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. sub-neg 44.4%

         \[\leadsto k \cdot \color{blue}{\left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right)} \]

      2. +-commutative 44.4%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + -1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\right)} + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      3. mul-1-neg 44.4%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + \color{blue}{\left(-y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)}\right) + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      4. unsub-neg 44.4%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      5. *-commutative 44.4%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y}\right) + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      6. mul-1-neg 44.4%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \left(b \cdot y4 - i \cdot y5\right) \cdot y\right) + \left(-\color{blue}{\left(-z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)}\right)\right) \]

      7. remove-double-neg 44.4%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \left(b \cdot y4 - i \cdot y5\right) \cdot y\right) + \color{blue}{z \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Simplified 44.4%

      \[\leadsto \color{blue}{k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \left(b \cdot y4 - i \cdot y5\right) \cdot y\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf 46.3%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if -2.90000000000000017e78 < y2 < -1.34999999999999994e-223

   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. Taylor expanded in b around inf 46.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 42.0%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.0%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 42.0%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 42.0%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -1.34999999999999994e-223 < y2 < -9.4000000000000001e-271

   1. Initial program 27.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 46.3%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 64.6%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -9.4000000000000001e-271 < y2 < 3.79999999999999985e-307

   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. Taylor expanded in y0 around inf 56.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 56.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 56.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 56.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 56.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y3 around inf 89.0%

      \[\leadsto y0 \cdot \color{blue}{\left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) - -1 \cdot \left(j \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. sub-neg 89.0%

         \[\leadsto y0 \cdot \left(y3 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot z\right) + \left(--1 \cdot \left(j \cdot y5\right)\right)\right)}\right) \]

      2. mul-1-neg 89.0%

         \[\leadsto y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) + \left(-\color{blue}{\left(-j \cdot y5\right)}\right)\right)\right) \]

      3. remove-double-neg 89.0%

         \[\leadsto y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(c \cdot z\right) + \color{blue}{j \cdot y5}\right)\right) \]

      4. +-commutative 89.0%

         \[\leadsto y0 \cdot \left(y3 \cdot \color{blue}{\left(j \cdot y5 + -1 \cdot \left(c \cdot z\right)\right)}\right) \]

      5. mul-1-neg 89.0%

         \[\leadsto y0 \cdot \left(y3 \cdot \left(j \cdot y5 + \color{blue}{\left(-c \cdot z\right)}\right)\right) \]

      6. unsub-neg 89.0%

         \[\leadsto y0 \cdot \left(y3 \cdot \color{blue}{\left(j \cdot y5 - c \cdot z\right)}\right) \]

   7. Simplified 89.0%

      \[\leadsto y0 \cdot \color{blue}{\left(y3 \cdot \left(j \cdot y5 - c \cdot z\right)\right)} \]

   if 3.79999999999999985e-307 < y2 < 4.40000000000000023e-104

   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. Taylor expanded in x around inf 47.4%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around inf 45.8%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 45.8%

         \[\leadsto j \cdot \left(x \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right)\right) \]

      2. *-commutative 45.8%

         \[\leadsto j \cdot \left(x \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right)\right) \]

   5. Simplified 45.8%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(y1 \cdot i - y0 \cdot b\right)\right)} \]

   if 1.79999999999999998e40 < y2 < 1.10000000000000004e98

   1. Initial program 15.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 16.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 61.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 61.8%

         \[\leadsto b \cdot \left(y \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right)\right) \]

      3. unsub-neg 61.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)}\right) \]

      4. *-commutative 61.8%

         \[\leadsto b \cdot \left(y \cdot \left(\color{blue}{x \cdot a} - k \cdot y4\right)\right) \]

      5. *-commutative 61.8%

         \[\leadsto b \cdot \left(y \cdot \left(x \cdot a - \color{blue}{y4 \cdot k}\right)\right) \]

   5. Simplified 61.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(x \cdot a - y4 \cdot k\right)\right)} \]

   if 1.10000000000000004e98 < y2 < 3.8000000000000001e202

   1. Initial program 18.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y0 around inf 18.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 18.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 18.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 18.8%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 18.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 18.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 18.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 18.8%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 18.8%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in b around inf 46.1%

      \[\leadsto y0 \cdot \color{blue}{\left(b \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 46.1%

         \[\leadsto y0 \cdot \left(b \cdot \left(\color{blue}{z \cdot k} - j \cdot x\right)\right) \]

      2. *-commutative 46.1%

         \[\leadsto y0 \cdot \left(b \cdot \left(z \cdot k - \color{blue}{x \cdot j}\right)\right) \]

   7. Simplified 46.1%

      \[\leadsto y0 \cdot \color{blue}{\left(b \cdot \left(z \cdot k - x \cdot j\right)\right)} \]

   if 3.8000000000000001e202 < y2

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y0 around inf 55.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 55.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 55.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 55.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 55.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 55.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 55.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 55.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 55.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y2 around inf 75.2%

      \[\leadsto \color{blue}{y0 \cdot \left(y2 \cdot \left(c \cdot x - k \cdot y5\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 50.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -2.9 \cdot 10^{+78}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -1.35 \cdot 10^{-223}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq -9.4 \cdot 10^{-271}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 3.8 \cdot 10^{-307}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y2 \leq 4.4 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 1.8 \cdot 10^{+40}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 1.1 \cdot 10^{+98}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 3.8 \cdot 10^{+202}:\\ \;\;\;\;y0 \cdot \left(b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \]

Alternative 19: 34.1% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;y2 \leq -8.8 \cdot 10^{+80}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq -1.9 \cdot 10^{-228}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{-88}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 3.2 \cdot 10^{+44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 2.4 \cdot 10^{+96}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 8.2 \cdot 10^{+132}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 1.4 \cdot 10^{+233}:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= y2 -8.8e+80)
     t_1
     (if (<= y2 -1.9e-228)
       (* b (* x (- (* y a) (* j y0))))
       (if (<= y2 4e-88)
         (* j (+ (* t (- (* b y4) (* i y5))) (* x (- (* i y1) (* b y0)))))
         (if (<= y2 3.2e+44)
           t_1
           (if (<= y2 2.4e+96)
             (* b (* y (- (* x a) (* k y4))))
             (if (<= y2 8.2e+132)
               (* a (* y3 (- (* z y1) (* y y5))))
               (if (<= y2 1.4e+233)
                 (* a (* y2 (- (* t y5) (* x y1))))
                 (* y0 (* y2 (- (* x c) (* k 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -8.8e+80) {
		tmp = t_1;
	} else if (y2 <= -1.9e-228) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= 4e-88) {
		tmp = j * ((t * ((b * y4) - (i * y5))) + (x * ((i * y1) - (b * y0))));
	} else if (y2 <= 3.2e+44) {
		tmp = t_1;
	} else if (y2 <= 2.4e+96) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 8.2e+132) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 1.4e+233) {
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * 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) :: tmp
    t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (y2 <= (-8.8d+80)) then
        tmp = t_1
    else if (y2 <= (-1.9d-228)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y2 <= 4d-88) then
        tmp = j * ((t * ((b * y4) - (i * y5))) + (x * ((i * y1) - (b * y0))))
    else if (y2 <= 3.2d+44) then
        tmp = t_1
    else if (y2 <= 2.4d+96) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (y2 <= 8.2d+132) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y2 <= 1.4d+233) then
        tmp = a * (y2 * ((t * y5) - (x * y1)))
    else
        tmp = y0 * (y2 * ((x * c) - (k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y2 <= -8.8e+80) {
		tmp = t_1;
	} else if (y2 <= -1.9e-228) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y2 <= 4e-88) {
		tmp = j * ((t * ((b * y4) - (i * y5))) + (x * ((i * y1) - (b * y0))));
	} else if (y2 <= 3.2e+44) {
		tmp = t_1;
	} else if (y2 <= 2.4e+96) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (y2 <= 8.2e+132) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y2 <= 1.4e+233) {
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	} else {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if y2 <= -8.8e+80:
		tmp = t_1
	elif y2 <= -1.9e-228:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y2 <= 4e-88:
		tmp = j * ((t * ((b * y4) - (i * y5))) + (x * ((i * y1) - (b * y0))))
	elif y2 <= 3.2e+44:
		tmp = t_1
	elif y2 <= 2.4e+96:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif y2 <= 8.2e+132:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y2 <= 1.4e+233:
		tmp = a * (y2 * ((t * y5) - (x * y1)))
	else:
		tmp = y0 * (y2 * ((x * c) - (k * 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(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (y2 <= -8.8e+80)
		tmp = t_1;
	elseif (y2 <= -1.9e-228)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y2 <= 4e-88)
		tmp = Float64(j * Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (y2 <= 3.2e+44)
		tmp = t_1;
	elseif (y2 <= 2.4e+96)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (y2 <= 8.2e+132)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y2 <= 1.4e+233)
		tmp = Float64(a * Float64(y2 * Float64(Float64(t * y5) - Float64(x * y1))));
	else
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * 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 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (y2 <= -8.8e+80)
		tmp = t_1;
	elseif (y2 <= -1.9e-228)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y2 <= 4e-88)
		tmp = j * ((t * ((b * y4) - (i * y5))) + (x * ((i * y1) - (b * y0))));
	elseif (y2 <= 3.2e+44)
		tmp = t_1;
	elseif (y2 <= 2.4e+96)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (y2 <= 8.2e+132)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y2 <= 1.4e+233)
		tmp = a * (y2 * ((t * y5) - (x * y1)));
	else
		tmp = y0 * (y2 * ((x * c) - (k * 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[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -8.8e+80], t$95$1, If[LessEqual[y2, -1.9e-228], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4e-88], N[(j * N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 3.2e+44], t$95$1, If[LessEqual[y2, 2.4e+96], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 8.2e+132], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 1.4e+233], N[(a * N[(y2 * N[(N[(t * y5), $MachinePrecision] - N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y2 < -8.80000000000000011e80 or 3.99999999999999974e-88 < y2 < 3.20000000000000004e44

   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. Taylor expanded in k around inf 45.5%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. sub-neg 45.5%

         \[\leadsto k \cdot \color{blue}{\left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right)} \]

      2. +-commutative 45.5%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + -1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\right)} + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      3. mul-1-neg 45.5%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + \color{blue}{\left(-y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)}\right) + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      4. unsub-neg 45.5%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      5. *-commutative 45.5%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y}\right) + \left(--1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)\right) \]

      6. mul-1-neg 45.5%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \left(b \cdot y4 - i \cdot y5\right) \cdot y\right) + \left(-\color{blue}{\left(-z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)}\right)\right) \]

      7. remove-double-neg 45.5%

         \[\leadsto k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \left(b \cdot y4 - i \cdot y5\right) \cdot y\right) + \color{blue}{z \cdot \left(b \cdot y0 - i \cdot y1\right)}\right) \]

   4. Simplified 45.5%

      \[\leadsto \color{blue}{k \cdot \left(\left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - \left(b \cdot y4 - i \cdot y5\right) \cdot y\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   5. Taylor expanded in y2 around inf 49.0%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if -8.80000000000000011e80 < y2 < -1.8999999999999999e-228

   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. Taylor expanded in b around inf 45.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 41.3%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.3%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 41.3%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 41.3%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -1.8999999999999999e-228 < y2 < 3.99999999999999974e-88

   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. Taylor expanded in j around inf 39.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around 0 48.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.9%

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 48.9%

         \[\leadsto j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   7. Simplified 48.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   if 3.20000000000000004e44 < y2 < 2.39999999999999993e96

   1. Initial program 15.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 16.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 61.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 61.8%

         \[\leadsto b \cdot \left(y \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right)\right) \]

      3. unsub-neg 61.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)}\right) \]

      4. *-commutative 61.8%

         \[\leadsto b \cdot \left(y \cdot \left(\color{blue}{x \cdot a} - k \cdot y4\right)\right) \]

      5. *-commutative 61.8%

         \[\leadsto b \cdot \left(y \cdot \left(x \cdot a - \color{blue}{y4 \cdot k}\right)\right) \]

   5. Simplified 61.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(x \cdot a - y4 \cdot k\right)\right)} \]

   if 2.39999999999999993e96 < y2 < 8.19999999999999983e132

   1. Initial program 11.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 46.1%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 46.1%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 46.1%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 46.1%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 46.1%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y3 around -inf 56.3%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 8.19999999999999983e132 < y2 < 1.40000000000000005e233

   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. Taylor expanded in a around -inf 45.2%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 45.2%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 45.2%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 45.2%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 45.2%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y2 around inf 60.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y2 \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 60.7%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y2 \cdot \left(x \cdot y1 - t \cdot y5\right)\right)} \]

      2. neg-mul-1 60.7%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y2 \cdot \left(x \cdot y1 - t \cdot y5\right)\right) \]

   7. Simplified 60.7%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y2 \cdot \left(x \cdot y1 - t \cdot y5\right)\right)} \]

   if 1.40000000000000005e233 < y2

   1. Initial program 30.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y0 around inf 69.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 69.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. mul-1-neg 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)}\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. unsub-neg 69.2%

         \[\leadsto y0 \cdot \left(\color{blue}{\left(c \cdot \left(x \cdot y2 - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      4. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      5. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      6. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - \color{blue}{y3 \cdot j}\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      7. *-commutative 69.2%

         \[\leadsto y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   4. Simplified 69.2%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(c \cdot \left(y2 \cdot x - z \cdot y3\right) - y5 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - b \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   5. Taylor expanded in y2 around inf 92.3%

      \[\leadsto \color{blue}{y0 \cdot \left(y2 \cdot \left(c \cdot x - k \cdot y5\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 51.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -8.8 \cdot 10^{+80}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -1.9 \cdot 10^{-228}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{-88}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 3.2 \cdot 10^{+44}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 2.4 \cdot 10^{+96}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 8.2 \cdot 10^{+132}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq 1.4 \cdot 10^{+233}:\\ \;\;\;\;a \cdot \left(y2 \cdot \left(t \cdot y5 - x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \end{array} \]

Alternative 20: 30.0% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ t_2 := a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{if}\;y3 \leq -4.4 \cdot 10^{+247}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y3 \leq -1.95 \cdot 10^{+147}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y3 \leq -1.35 \cdot 10^{+139}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y3 \leq -1.02 \cdot 10^{+124}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.7 \cdot 10^{+97}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y3 \leq -3.2 \cdot 10^{+51}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y3 \leq 5 \cdot 10^{-23}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0)))))
        (t_2 (* a (* y3 (- (* z y1) (* y y5))))))
   (if (<= y3 -4.4e+247)
     t_2
     (if (<= y3 -1.95e+147)
       t_1
       (if (<= y3 -1.35e+139)
         t_2
         (if (<= y3 -1.02e+124)
           (* y0 (* j (* y3 y5)))
           (if (<= y3 -1.7e+97)
             t_1
             (if (<= y3 -3.2e+51)
               t_2
               (if (<= y3 5e-23)
                 t_1
                 (* a (* y5 (- (* t y2) (* y y3)))))))))))))

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 * (x * ((y * a) - (j * y0)));
	double t_2 = a * (y3 * ((z * y1) - (y * y5)));
	double tmp;
	if (y3 <= -4.4e+247) {
		tmp = t_2;
	} else if (y3 <= -1.95e+147) {
		tmp = t_1;
	} else if (y3 <= -1.35e+139) {
		tmp = t_2;
	} else if (y3 <= -1.02e+124) {
		tmp = y0 * (j * (y3 * y5));
	} else if (y3 <= -1.7e+97) {
		tmp = t_1;
	} else if (y3 <= -3.2e+51) {
		tmp = t_2;
	} else if (y3 <= 5e-23) {
		tmp = t_1;
	} else {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	}
	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 = b * (x * ((y * a) - (j * y0)))
    t_2 = a * (y3 * ((z * y1) - (y * y5)))
    if (y3 <= (-4.4d+247)) then
        tmp = t_2
    else if (y3 <= (-1.95d+147)) then
        tmp = t_1
    else if (y3 <= (-1.35d+139)) then
        tmp = t_2
    else if (y3 <= (-1.02d+124)) then
        tmp = y0 * (j * (y3 * y5))
    else if (y3 <= (-1.7d+97)) then
        tmp = t_1
    else if (y3 <= (-3.2d+51)) then
        tmp = t_2
    else if (y3 <= 5d-23) then
        tmp = t_1
    else
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    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 * (x * ((y * a) - (j * y0)));
	double t_2 = a * (y3 * ((z * y1) - (y * y5)));
	double tmp;
	if (y3 <= -4.4e+247) {
		tmp = t_2;
	} else if (y3 <= -1.95e+147) {
		tmp = t_1;
	} else if (y3 <= -1.35e+139) {
		tmp = t_2;
	} else if (y3 <= -1.02e+124) {
		tmp = y0 * (j * (y3 * y5));
	} else if (y3 <= -1.7e+97) {
		tmp = t_1;
	} else if (y3 <= -3.2e+51) {
		tmp = t_2;
	} else if (y3 <= 5e-23) {
		tmp = t_1;
	} else {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (x * ((y * a) - (j * y0)))
	t_2 = a * (y3 * ((z * y1) - (y * y5)))
	tmp = 0
	if y3 <= -4.4e+247:
		tmp = t_2
	elif y3 <= -1.95e+147:
		tmp = t_1
	elif y3 <= -1.35e+139:
		tmp = t_2
	elif y3 <= -1.02e+124:
		tmp = y0 * (j * (y3 * y5))
	elif y3 <= -1.7e+97:
		tmp = t_1
	elif y3 <= -3.2e+51:
		tmp = t_2
	elif y3 <= 5e-23:
		tmp = t_1
	else:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	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(x * Float64(Float64(y * a) - Float64(j * y0))))
	t_2 = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))))
	tmp = 0.0
	if (y3 <= -4.4e+247)
		tmp = t_2;
	elseif (y3 <= -1.95e+147)
		tmp = t_1;
	elseif (y3 <= -1.35e+139)
		tmp = t_2;
	elseif (y3 <= -1.02e+124)
		tmp = Float64(y0 * Float64(j * Float64(y3 * y5)));
	elseif (y3 <= -1.7e+97)
		tmp = t_1;
	elseif (y3 <= -3.2e+51)
		tmp = t_2;
	elseif (y3 <= 5e-23)
		tmp = t_1;
	else
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	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 * (x * ((y * a) - (j * y0)));
	t_2 = a * (y3 * ((z * y1) - (y * y5)));
	tmp = 0.0;
	if (y3 <= -4.4e+247)
		tmp = t_2;
	elseif (y3 <= -1.95e+147)
		tmp = t_1;
	elseif (y3 <= -1.35e+139)
		tmp = t_2;
	elseif (y3 <= -1.02e+124)
		tmp = y0 * (j * (y3 * y5));
	elseif (y3 <= -1.7e+97)
		tmp = t_1;
	elseif (y3 <= -3.2e+51)
		tmp = t_2;
	elseif (y3 <= 5e-23)
		tmp = t_1;
	else
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	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[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y3, -4.4e+247], t$95$2, If[LessEqual[y3, -1.95e+147], t$95$1, If[LessEqual[y3, -1.35e+139], t$95$2, If[LessEqual[y3, -1.02e+124], N[(y0 * N[(j * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.7e+97], t$95$1, If[LessEqual[y3, -3.2e+51], t$95$2, If[LessEqual[y3, 5e-23], t$95$1, N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if y3 < -4.40000000000000022e247 or -1.95000000000000008e147 < y3 < -1.3499999999999999e139 or -1.70000000000000005e97 < y3 < -3.2000000000000002e51

   1. Initial program 12.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 44.1%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 44.1%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 44.1%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 44.1%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 44.1%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y3 around -inf 68.9%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if -4.40000000000000022e247 < y3 < -1.95000000000000008e147 or -1.01999999999999994e124 < y3 < -1.70000000000000005e97 or -3.2000000000000002e51 < y3 < 5.0000000000000002e-23

   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. Taylor expanded in b around inf 39.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 37.3%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 37.3%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 37.3%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 37.3%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -1.3499999999999999e139 < y3 < -1.01999999999999994e124

   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. Taylor expanded in j around inf 20.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 20.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 20.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 20.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 20.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 20.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 41.1%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 41.1%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 41.1%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 41.1%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 41.1%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 41.1%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around inf 43.1%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 43.1%

         \[\leadsto \color{blue}{\left(j \cdot y0\right) \cdot \left(y3 \cdot y5\right)} \]

      2. *-commutative 43.1%

         \[\leadsto \color{blue}{\left(y0 \cdot j\right)} \cdot \left(y3 \cdot y5\right) \]

      3. *-commutative 43.1%

         \[\leadsto \left(y0 \cdot j\right) \cdot \color{blue}{\left(y5 \cdot y3\right)} \]

      4. associate-*l* 62.0%

         \[\leadsto \color{blue}{y0 \cdot \left(j \cdot \left(y5 \cdot y3\right)\right)} \]

   10. Simplified 62.0%

       \[\leadsto \color{blue}{y0 \cdot \left(j \cdot \left(y5 \cdot y3\right)\right)} \]

   if 5.0000000000000002e-23 < y3

   1. Initial program 29.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 46.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 46.3%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 46.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 46.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 46.3%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y5 around -inf 43.5%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 43.5%

         \[\leadsto a \cdot \left(y5 \cdot \left(\color{blue}{y2 \cdot t} - y \cdot y3\right)\right) \]

      2. *-commutative 43.5%

         \[\leadsto a \cdot \left(y5 \cdot \left(y2 \cdot t - \color{blue}{y3 \cdot y}\right)\right) \]

   7. Simplified 43.5%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(y2 \cdot t - y3 \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 42.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -4.4 \cdot 10^{+247}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.95 \cdot 10^{+147}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y3 \leq -1.35 \cdot 10^{+139}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.02 \cdot 10^{+124}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -1.7 \cdot 10^{+97}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y3 \leq -3.2 \cdot 10^{+51}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq 5 \cdot 10^{-23}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \]

Alternative 21: 27.1% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ t_2 := x \cdot \left(-y0\right)\\ \mathbf{if}\;y3 \leq -7.4 \cdot 10^{+223}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y3 \leq -2.55 \cdot 10^{-201}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq 8 \cdot 10^{-295}:\\ \;\;\;\;j \cdot \left(b \cdot t_2\right)\\ \mathbf{elif}\;y3 \leq 4.5 \cdot 10^{-166}:\\ \;\;\;\;\left(x \cdot y1\right) \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;y3 \leq 10^{-27}:\\ \;\;\;\;\left(b \cdot j\right) \cdot t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y3 (- (* z y1) (* y y5))))) (t_2 (* x (- y0))))
   (if (<= y3 -7.4e+223)
     t_1
     (if (<= y3 -2.55e-201)
       (* a (* y (- (* x b) (* y3 y5))))
       (if (<= y3 8e-295)
         (* j (* b t_2))
         (if (<= y3 4.5e-166)
           (* (* x y1) (* i j))
           (if (<= y3 1e-27) (* (* b j) t_2) 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 = a * (y3 * ((z * y1) - (y * y5)));
	double t_2 = x * -y0;
	double tmp;
	if (y3 <= -7.4e+223) {
		tmp = t_1;
	} else if (y3 <= -2.55e-201) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y3 <= 8e-295) {
		tmp = j * (b * t_2);
	} else if (y3 <= 4.5e-166) {
		tmp = (x * y1) * (i * j);
	} else if (y3 <= 1e-27) {
		tmp = (b * j) * t_2;
	} 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) :: t_2
    real(8) :: tmp
    t_1 = a * (y3 * ((z * y1) - (y * y5)))
    t_2 = x * -y0
    if (y3 <= (-7.4d+223)) then
        tmp = t_1
    else if (y3 <= (-2.55d-201)) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (y3 <= 8d-295) then
        tmp = j * (b * t_2)
    else if (y3 <= 4.5d-166) then
        tmp = (x * y1) * (i * j)
    else if (y3 <= 1d-27) then
        tmp = (b * j) * t_2
    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 = a * (y3 * ((z * y1) - (y * y5)));
	double t_2 = x * -y0;
	double tmp;
	if (y3 <= -7.4e+223) {
		tmp = t_1;
	} else if (y3 <= -2.55e-201) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y3 <= 8e-295) {
		tmp = j * (b * t_2);
	} else if (y3 <= 4.5e-166) {
		tmp = (x * y1) * (i * j);
	} else if (y3 <= 1e-27) {
		tmp = (b * j) * t_2;
	} 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 = a * (y3 * ((z * y1) - (y * y5)))
	t_2 = x * -y0
	tmp = 0
	if y3 <= -7.4e+223:
		tmp = t_1
	elif y3 <= -2.55e-201:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif y3 <= 8e-295:
		tmp = j * (b * t_2)
	elif y3 <= 4.5e-166:
		tmp = (x * y1) * (i * j)
	elif y3 <= 1e-27:
		tmp = (b * j) * t_2
	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(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))))
	t_2 = Float64(x * Float64(-y0))
	tmp = 0.0
	if (y3 <= -7.4e+223)
		tmp = t_1;
	elseif (y3 <= -2.55e-201)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (y3 <= 8e-295)
		tmp = Float64(j * Float64(b * t_2));
	elseif (y3 <= 4.5e-166)
		tmp = Float64(Float64(x * y1) * Float64(i * j));
	elseif (y3 <= 1e-27)
		tmp = Float64(Float64(b * j) * t_2);
	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 = a * (y3 * ((z * y1) - (y * y5)));
	t_2 = x * -y0;
	tmp = 0.0;
	if (y3 <= -7.4e+223)
		tmp = t_1;
	elseif (y3 <= -2.55e-201)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (y3 <= 8e-295)
		tmp = j * (b * t_2);
	elseif (y3 <= 4.5e-166)
		tmp = (x * y1) * (i * j);
	elseif (y3 <= 1e-27)
		tmp = (b * j) * t_2;
	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[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * (-y0)), $MachinePrecision]}, If[LessEqual[y3, -7.4e+223], t$95$1, If[LessEqual[y3, -2.55e-201], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 8e-295], N[(j * N[(b * t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 4.5e-166], N[(N[(x * y1), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1e-27], N[(N[(b * j), $MachinePrecision] * t$95$2), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y3 < -7.4000000000000005e223 or 1e-27 < y3

   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. Taylor expanded in a around -inf 41.9%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 41.9%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 41.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 41.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 41.9%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y3 around -inf 46.9%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if -7.4000000000000005e223 < y3 < -2.5500000000000001e-201

   1. Initial program 29.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 37.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 37.0%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 37.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 37.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 37.0%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 34.4%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 34.4%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 34.4%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 34.4%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 34.4%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 34.4%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   if -2.5500000000000001e-201 < y3 < 8.00000000000000048e-295

   1. Initial program 42.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 27.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 27.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 27.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 27.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 27.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 27.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 21.0%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 21.0%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 21.0%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 21.0%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 21.0%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 21.0%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 32.0%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 32.0%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(x \cdot y0\right)\right)} \]

      2. neg-mul-1 32.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(-b\right)} \cdot \left(x \cdot y0\right)\right) \]

      3. *-commutative 32.0%

         \[\leadsto j \cdot \left(\left(-b\right) \cdot \color{blue}{\left(y0 \cdot x\right)}\right) \]

   10. Simplified 32.0%

       \[\leadsto j \cdot \color{blue}{\left(\left(-b\right) \cdot \left(y0 \cdot x\right)\right)} \]

   if 8.00000000000000048e-295 < y3 < 4.4999999999999998e-166

   1. Initial program 26.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 30.8%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around inf 31.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 27.3%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      2. *-commutative 27.3%

         \[\leadsto \left(j \cdot x\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      3. *-commutative 27.3%

         \[\leadsto \left(j \cdot x\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   5. Simplified 27.3%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   6. Taylor expanded in y1 around inf 24.0%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 30.5%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(x \cdot y1\right)} \]

      2. *-commutative 30.5%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(y1 \cdot x\right)} \]

   8. Simplified 30.5%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(y1 \cdot x\right)} \]

   if 4.4999999999999998e-166 < y3 < 1e-27

   1. Initial program 45.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 35.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 35.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 35.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 35.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 35.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 35.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 23.5%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 23.5%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 23.5%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 23.5%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 23.5%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 23.5%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 35.0%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 35.0%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. associate-*r* 35.2%

         \[\leadsto -\color{blue}{\left(b \cdot j\right) \cdot \left(x \cdot y0\right)} \]

      3. *-commutative 35.2%

         \[\leadsto -\left(b \cdot j\right) \cdot \color{blue}{\left(y0 \cdot x\right)} \]

   10. Simplified 35.2%

       \[\leadsto \color{blue}{-\left(b \cdot j\right) \cdot \left(y0 \cdot x\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 37.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -7.4 \cdot 10^{+223}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -2.55 \cdot 10^{-201}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq 8 \cdot 10^{-295}:\\ \;\;\;\;j \cdot \left(b \cdot \left(x \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 4.5 \cdot 10^{-166}:\\ \;\;\;\;\left(x \cdot y1\right) \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;y3 \leq 10^{-27}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \end{array} \]

Alternative 22: 26.8% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{if}\;y0 \leq -3.6 \cdot 10^{+85}:\\ \;\;\;\;j \cdot \left(b \cdot \left(x \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -7.8 \cdot 10^{-58}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq -2 \cdot 10^{-199}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq -2.8 \cdot 10^{-271}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4\right)\\ \mathbf{elif}\;y0 \leq 2.6 \cdot 10^{-41}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y5 (- (* t y2) (* y y3))))))
   (if (<= y0 -3.6e+85)
     (* j (* b (* x (- y0))))
     (if (<= y0 -7.8e-58)
       (* a (* y (- (* x b) (* y3 y5))))
       (if (<= y0 -2e-199)
         t_1
         (if (<= y0 -2.8e-271)
           (* (* b j) (* t y4))
           (if (<= y0 2.6e-41) t_1 (* a (* y3 (- (* z y1) (* y 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 = a * (y5 * ((t * y2) - (y * y3)));
	double tmp;
	if (y0 <= -3.6e+85) {
		tmp = j * (b * (x * -y0));
	} else if (y0 <= -7.8e-58) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y0 <= -2e-199) {
		tmp = t_1;
	} else if (y0 <= -2.8e-271) {
		tmp = (b * j) * (t * y4);
	} else if (y0 <= 2.6e-41) {
		tmp = t_1;
	} else {
		tmp = a * (y3 * ((z * y1) - (y * 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) :: tmp
    t_1 = a * (y5 * ((t * y2) - (y * y3)))
    if (y0 <= (-3.6d+85)) then
        tmp = j * (b * (x * -y0))
    else if (y0 <= (-7.8d-58)) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (y0 <= (-2d-199)) then
        tmp = t_1
    else if (y0 <= (-2.8d-271)) then
        tmp = (b * j) * (t * y4)
    else if (y0 <= 2.6d-41) then
        tmp = t_1
    else
        tmp = a * (y3 * ((z * y1) - (y * 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 = a * (y5 * ((t * y2) - (y * y3)));
	double tmp;
	if (y0 <= -3.6e+85) {
		tmp = j * (b * (x * -y0));
	} else if (y0 <= -7.8e-58) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y0 <= -2e-199) {
		tmp = t_1;
	} else if (y0 <= -2.8e-271) {
		tmp = (b * j) * (t * y4);
	} else if (y0 <= 2.6e-41) {
		tmp = t_1;
	} else {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	}
	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 y0 <= -3.6e+85:
		tmp = j * (b * (x * -y0))
	elif y0 <= -7.8e-58:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif y0 <= -2e-199:
		tmp = t_1
	elif y0 <= -2.8e-271:
		tmp = (b * j) * (t * y4)
	elif y0 <= 2.6e-41:
		tmp = t_1
	else:
		tmp = a * (y3 * ((z * y1) - (y * 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(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))))
	tmp = 0.0
	if (y0 <= -3.6e+85)
		tmp = Float64(j * Float64(b * Float64(x * Float64(-y0))));
	elseif (y0 <= -7.8e-58)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (y0 <= -2e-199)
		tmp = t_1;
	elseif (y0 <= -2.8e-271)
		tmp = Float64(Float64(b * j) * Float64(t * y4));
	elseif (y0 <= 2.6e-41)
		tmp = t_1;
	else
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * 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 = a * (y5 * ((t * y2) - (y * y3)));
	tmp = 0.0;
	if (y0 <= -3.6e+85)
		tmp = j * (b * (x * -y0));
	elseif (y0 <= -7.8e-58)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (y0 <= -2e-199)
		tmp = t_1;
	elseif (y0 <= -2.8e-271)
		tmp = (b * j) * (t * y4);
	elseif (y0 <= 2.6e-41)
		tmp = t_1;
	else
		tmp = a * (y3 * ((z * y1) - (y * 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[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -3.6e+85], N[(j * N[(b * N[(x * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -7.8e-58], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -2e-199], t$95$1, If[LessEqual[y0, -2.8e-271], N[(N[(b * j), $MachinePrecision] * N[(t * y4), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.6e-41], t$95$1, N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y0 < -3.5999999999999998e85

   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. Taylor expanded in j around inf 22.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 22.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 22.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 22.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 22.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 22.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 48.2%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 48.2%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 48.2%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 48.2%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 48.2%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 48.2%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 44.9%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 44.9%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(x \cdot y0\right)\right)} \]

      2. neg-mul-1 44.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(-b\right)} \cdot \left(x \cdot y0\right)\right) \]

      3. *-commutative 44.9%

         \[\leadsto j \cdot \left(\left(-b\right) \cdot \color{blue}{\left(y0 \cdot x\right)}\right) \]

   10. Simplified 44.9%

       \[\leadsto j \cdot \color{blue}{\left(\left(-b\right) \cdot \left(y0 \cdot x\right)\right)} \]

   if -3.5999999999999998e85 < y0 < -7.79999999999999985e-58

   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. Taylor expanded in a around -inf 41.1%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 41.1%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 41.1%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 41.1%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 41.1%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 45.9%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 45.9%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 45.9%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 45.9%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 45.9%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 45.9%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   if -7.79999999999999985e-58 < y0 < -1.99999999999999996e-199 or -2.7999999999999997e-271 < y0 < 2.5999999999999999e-41

   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. Taylor expanded in a around -inf 41.6%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 41.6%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 41.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 41.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 41.6%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y5 around -inf 39.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 39.0%

         \[\leadsto a \cdot \left(y5 \cdot \left(\color{blue}{y2 \cdot t} - y \cdot y3\right)\right) \]

      2. *-commutative 39.0%

         \[\leadsto a \cdot \left(y5 \cdot \left(y2 \cdot t - \color{blue}{y3 \cdot y}\right)\right) \]

   7. Simplified 39.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(y2 \cdot t - y3 \cdot y\right)\right)} \]

   if -1.99999999999999996e-199 < y0 < -2.7999999999999997e-271

   1. Initial program 42.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 36.6%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 29.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 30.2%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 37.0%

         \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4\right)} \]

      2. *-commutative 37.0%

         \[\leadsto \color{blue}{\left(j \cdot b\right)} \cdot \left(t \cdot y4\right) \]

   6. Simplified 37.0%

      \[\leadsto \color{blue}{\left(j \cdot b\right) \cdot \left(t \cdot y4\right)} \]

   if 2.5999999999999999e-41 < y0

   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. Taylor expanded in a around -inf 36.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 36.5%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 36.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 36.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 36.5%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y3 around -inf 31.0%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 38.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -3.6 \cdot 10^{+85}:\\ \;\;\;\;j \cdot \left(b \cdot \left(x \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -7.8 \cdot 10^{-58}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq -2 \cdot 10^{-199}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq -2.8 \cdot 10^{-271}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4\right)\\ \mathbf{elif}\;y0 \leq 2.6 \cdot 10^{-41}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \end{array} \]

Alternative 23: 30.7% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{if}\;b \leq -5.2 \cdot 10^{+73}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;b \leq -1.2 \cdot 10^{-205}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 1.95 \cdot 10^{-279}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;b \leq 8 \cdot 10^{-106}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 5.2 \cdot 10^{+84}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* y4 (- (* y y3) (* t y2))))))
   (if (<= b -5.2e+73)
     (* b (* x (- (* y a) (* j y0))))
     (if (<= b -1.2e-205)
       t_1
       (if (<= b 1.95e-279)
         (* c (* x (- (* y0 y2) (* y i))))
         (if (<= b 8e-106)
           t_1
           (if (<= b 5.2e+84)
             (* a (* y3 (- (* z y1) (* y y5))))
             (* b (* y (- (* x a) (* k 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 = c * (y4 * ((y * y3) - (t * y2)));
	double tmp;
	if (b <= -5.2e+73) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (b <= -1.2e-205) {
		tmp = t_1;
	} else if (b <= 1.95e-279) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (b <= 8e-106) {
		tmp = t_1;
	} else if (b <= 5.2e+84) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else {
		tmp = b * (y * ((x * a) - (k * 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 = c * (y4 * ((y * y3) - (t * y2)))
    if (b <= (-5.2d+73)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (b <= (-1.2d-205)) then
        tmp = t_1
    else if (b <= 1.95d-279) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else if (b <= 8d-106) then
        tmp = t_1
    else if (b <= 5.2d+84) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else
        tmp = b * (y * ((x * a) - (k * 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 = c * (y4 * ((y * y3) - (t * y2)));
	double tmp;
	if (b <= -5.2e+73) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (b <= -1.2e-205) {
		tmp = t_1;
	} else if (b <= 1.95e-279) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (b <= 8e-106) {
		tmp = t_1;
	} else if (b <= 5.2e+84) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else {
		tmp = b * (y * ((x * a) - (k * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (y4 * ((y * y3) - (t * y2)))
	tmp = 0
	if b <= -5.2e+73:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif b <= -1.2e-205:
		tmp = t_1
	elif b <= 1.95e-279:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	elif b <= 8e-106:
		tmp = t_1
	elif b <= 5.2e+84:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	else:
		tmp = b * (y * ((x * a) - (k * 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(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))))
	tmp = 0.0
	if (b <= -5.2e+73)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (b <= -1.2e-205)
		tmp = t_1;
	elseif (b <= 1.95e-279)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	elseif (b <= 8e-106)
		tmp = t_1;
	elseif (b <= 5.2e+84)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	else
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * 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 = c * (y4 * ((y * y3) - (t * y2)));
	tmp = 0.0;
	if (b <= -5.2e+73)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (b <= -1.2e-205)
		tmp = t_1;
	elseif (b <= 1.95e-279)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	elseif (b <= 8e-106)
		tmp = t_1;
	elseif (b <= 5.2e+84)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	else
		tmp = b * (y * ((x * a) - (k * 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[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -5.2e+73], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -1.2e-205], t$95$1, If[LessEqual[b, 1.95e-279], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 8e-106], t$95$1, If[LessEqual[b, 5.2e+84], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if b < -5.2000000000000001e73

   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. Taylor expanded in b around inf 46.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 46.2%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 46.2%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 46.2%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 46.2%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -5.2000000000000001e73 < b < -1.2000000000000001e-205 or 1.95000000000000014e-279 < b < 7.99999999999999953e-106

   1. Initial program 38.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 47.7%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 47.7%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      2. mul-1-neg 47.7%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)}\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      3. unsub-neg 47.7%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      4. *-commutative 47.7%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      5. *-commutative 47.7%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      6. *-commutative 47.7%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(\color{blue}{y \cdot x} - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      7. *-commutative 47.7%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) \]

   4. Simplified 47.7%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]

   5. Taylor expanded in y4 around inf 46.5%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 46.5%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 46.5%

         \[\leadsto c \cdot \left(y4 \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   7. Simplified 46.5%

      \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   if -1.2000000000000001e-205 < b < 1.95000000000000014e-279

   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. Taylor expanded in c around inf 59.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 59.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      2. mul-1-neg 59.6%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)}\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      3. unsub-neg 59.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      4. *-commutative 59.6%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      5. *-commutative 59.6%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      6. *-commutative 59.6%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(\color{blue}{y \cdot x} - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      7. *-commutative 59.6%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) \]

   4. Simplified 59.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]

   5. Taylor expanded in x around inf 46.7%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]

   if 7.99999999999999953e-106 < b < 5.2000000000000002e84

   1. Initial program 29.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 42.2%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.2%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 42.2%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 42.2%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 42.2%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y3 around -inf 35.1%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 5.2000000000000002e84 < b

   1. Initial program 17.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 51.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 45.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right)\right) \]

      3. unsub-neg 45.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)}\right) \]

      4. *-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(\color{blue}{x \cdot a} - k \cdot y4\right)\right) \]

      5. *-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(x \cdot a - \color{blue}{y4 \cdot k}\right)\right) \]

   5. Simplified 45.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(x \cdot a - y4 \cdot k\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 44.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \leq -5.2 \cdot 10^{+73}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;b \leq -1.2 \cdot 10^{-205}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;b \leq 1.95 \cdot 10^{-279}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;b \leq 8 \cdot 10^{-106}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;b \leq 5.2 \cdot 10^{+84}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \end{array} \]

Alternative 24: 29.4% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -1.15 \cdot 10^{+114}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;b \leq -3.8 \cdot 10^{-103}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;b \leq -6.4 \cdot 10^{-198}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;b \leq 3.3 \cdot 10^{+83}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b -1.15e+114)
   (* b (* x (- (* y a) (* j y0))))
   (if (<= b -3.8e-103)
     (* a (* y5 (- (* t y2) (* y y3))))
     (if (<= b -6.4e-198)
       (* j (* t (* i (- y5))))
       (if (<= b 3.3e+83)
         (* a (* y3 (- (* z y1) (* y y5))))
         (* b (* y (- (* x a) (* k 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 tmp;
	if (b <= -1.15e+114) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (b <= -3.8e-103) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (b <= -6.4e-198) {
		tmp = j * (t * (i * -y5));
	} else if (b <= 3.3e+83) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else {
		tmp = b * (y * ((x * a) - (k * 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) :: tmp
    if (b <= (-1.15d+114)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (b <= (-3.8d-103)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (b <= (-6.4d-198)) then
        tmp = j * (t * (i * -y5))
    else if (b <= 3.3d+83) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else
        tmp = b * (y * ((x * a) - (k * 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 tmp;
	if (b <= -1.15e+114) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (b <= -3.8e-103) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (b <= -6.4e-198) {
		tmp = j * (t * (i * -y5));
	} else if (b <= 3.3e+83) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else {
		tmp = b * (y * ((x * a) - (k * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if b <= -1.15e+114:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif b <= -3.8e-103:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif b <= -6.4e-198:
		tmp = j * (t * (i * -y5))
	elif b <= 3.3e+83:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	else:
		tmp = b * (y * ((x * a) - (k * y4)))
	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 (b <= -1.15e+114)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (b <= -3.8e-103)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (b <= -6.4e-198)
		tmp = Float64(j * Float64(t * Float64(i * Float64(-y5))));
	elseif (b <= 3.3e+83)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	else
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * 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)
	tmp = 0.0;
	if (b <= -1.15e+114)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (b <= -3.8e-103)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (b <= -6.4e-198)
		tmp = j * (t * (i * -y5));
	elseif (b <= 3.3e+83)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	else
		tmp = b * (y * ((x * a) - (k * y4)));
	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[b, -1.15e+114], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -3.8e-103], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -6.4e-198], N[(j * N[(t * N[(i * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 3.3e+83], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if b < -1.15e114

   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. Taylor expanded in b around inf 50.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 50.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 50.5%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 50.5%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 50.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -1.15e114 < b < -3.8000000000000001e-103

   1. Initial program 48.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 42.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.3%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 42.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 42.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 42.3%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y5 around -inf 33.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 33.0%

         \[\leadsto a \cdot \left(y5 \cdot \left(\color{blue}{y2 \cdot t} - y \cdot y3\right)\right) \]

      2. *-commutative 33.0%

         \[\leadsto a \cdot \left(y5 \cdot \left(y2 \cdot t - \color{blue}{y3 \cdot y}\right)\right) \]

   7. Simplified 33.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(y2 \cdot t - y3 \cdot y\right)\right)} \]

   if -3.8000000000000001e-103 < b < -6.39999999999999989e-198

   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. Taylor expanded in t around inf 53.3%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 34.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around 0 33.7%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y5\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 33.7%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-i \cdot y5\right)}\right) \]

      2. distribute-lft-neg-in 33.7%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(\left(-i\right) \cdot y5\right)}\right) \]

      3. *-commutative 33.7%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   6. Simplified 33.7%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   if -6.39999999999999989e-198 < b < 3.29999999999999985e83

   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. Taylor expanded in a around -inf 34.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 34.3%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 34.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 34.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 34.3%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y3 around -inf 33.0%

      \[\leadsto \color{blue}{a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)} \]

   if 3.29999999999999985e83 < b

   1. Initial program 17.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 51.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 45.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right)\right) \]

      3. unsub-neg 45.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)}\right) \]

      4. *-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(\color{blue}{x \cdot a} - k \cdot y4\right)\right) \]

      5. *-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(x \cdot a - \color{blue}{y4 \cdot k}\right)\right) \]

   5. Simplified 45.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(x \cdot a - y4 \cdot k\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 38.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \leq -1.15 \cdot 10^{+114}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;b \leq -3.8 \cdot 10^{-103}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;b \leq -6.4 \cdot 10^{-198}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;b \leq 3.3 \cdot 10^{+83}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \end{array} \]

Alternative 25: 30.3% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{if}\;a \leq -7.4 \cdot 10^{+52}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 5 \cdot 10^{-202}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.3 \cdot 10^{-57}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 4 \cdot 10^{+106}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* i (- (* z t) (* x y))))))
   (if (<= a -7.4e+52)
     (* a (* y5 (- (* t y2) (* y y3))))
     (if (<= a 5e-202)
       t_1
       (if (<= a 3.3e-57)
         (* b (* y (- (* x a) (* k y4))))
         (if (<= a 4e+106) t_1 (* b (* x (- (* y a) (* j 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 * (i * ((z * t) - (x * y)));
	double tmp;
	if (a <= -7.4e+52) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (a <= 5e-202) {
		tmp = t_1;
	} else if (a <= 3.3e-57) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (a <= 4e+106) {
		tmp = t_1;
	} else {
		tmp = b * (x * ((y * a) - (j * 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 = c * (i * ((z * t) - (x * y)))
    if (a <= (-7.4d+52)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (a <= 5d-202) then
        tmp = t_1
    else if (a <= 3.3d-57) then
        tmp = b * (y * ((x * a) - (k * y4)))
    else if (a <= 4d+106) then
        tmp = t_1
    else
        tmp = b * (x * ((y * a) - (j * 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 = c * (i * ((z * t) - (x * y)));
	double tmp;
	if (a <= -7.4e+52) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (a <= 5e-202) {
		tmp = t_1;
	} else if (a <= 3.3e-57) {
		tmp = b * (y * ((x * a) - (k * y4)));
	} else if (a <= 4e+106) {
		tmp = t_1;
	} else {
		tmp = b * (x * ((y * a) - (j * y0)));
	}
	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)))
	tmp = 0
	if a <= -7.4e+52:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif a <= 5e-202:
		tmp = t_1
	elif a <= 3.3e-57:
		tmp = b * (y * ((x * a) - (k * y4)))
	elif a <= 4e+106:
		tmp = t_1
	else:
		tmp = b * (x * ((y * a) - (j * 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(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))))
	tmp = 0.0
	if (a <= -7.4e+52)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (a <= 5e-202)
		tmp = t_1;
	elseif (a <= 3.3e-57)
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * y4))));
	elseif (a <= 4e+106)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * 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 = c * (i * ((z * t) - (x * y)));
	tmp = 0.0;
	if (a <= -7.4e+52)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (a <= 5e-202)
		tmp = t_1;
	elseif (a <= 3.3e-57)
		tmp = b * (y * ((x * a) - (k * y4)));
	elseif (a <= 4e+106)
		tmp = t_1;
	else
		tmp = b * (x * ((y * a) - (j * 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[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -7.4e+52], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5e-202], t$95$1, If[LessEqual[a, 3.3e-57], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4e+106], t$95$1, N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 4 regimes

2. if a < -7.3999999999999999e52

   1. Initial program 22.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 52.6%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 52.6%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 52.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 52.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 52.6%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y5 around -inf 48.7%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.7%

         \[\leadsto a \cdot \left(y5 \cdot \left(\color{blue}{y2 \cdot t} - y \cdot y3\right)\right) \]

      2. *-commutative 48.7%

         \[\leadsto a \cdot \left(y5 \cdot \left(y2 \cdot t - \color{blue}{y3 \cdot y}\right)\right) \]

   7. Simplified 48.7%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(y2 \cdot t - y3 \cdot y\right)\right)} \]

   if -7.3999999999999999e52 < a < 4.99999999999999973e-202 or 3.2999999999999998e-57 < a < 4.00000000000000036e106

   1. Initial program 38.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 51.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 51.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      2. mul-1-neg 51.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)}\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      3. unsub-neg 51.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      4. *-commutative 51.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      5. *-commutative 51.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      6. *-commutative 51.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(\color{blue}{y \cdot x} - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      7. *-commutative 51.8%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) \]

   4. Simplified 51.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]

   5. Taylor expanded in i around inf 38.9%

      \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(t \cdot z - x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 38.9%

         \[\leadsto c \cdot \left(i \cdot \left(\color{blue}{z \cdot t} - x \cdot y\right)\right) \]

   7. Simplified 38.9%

      \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(z \cdot t - x \cdot y\right)\right)} \]

   if 4.99999999999999973e-202 < a < 3.2999999999999998e-57

   1. Initial program 31.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 46.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 28.4%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 28.4%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 28.4%

         \[\leadsto b \cdot \left(y \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right)\right) \]

      3. unsub-neg 28.4%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)}\right) \]

      4. *-commutative 28.4%

         \[\leadsto b \cdot \left(y \cdot \left(\color{blue}{x \cdot a} - k \cdot y4\right)\right) \]

      5. *-commutative 28.4%

         \[\leadsto b \cdot \left(y \cdot \left(x \cdot a - \color{blue}{y4 \cdot k}\right)\right) \]

   5. Simplified 28.4%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(x \cdot a - y4 \cdot k\right)\right)} \]

   if 4.00000000000000036e106 < a

   1. Initial program 22.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 45.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 45.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 45.5%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 45.5%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 45.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 41.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -7.4 \cdot 10^{+52}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 5 \cdot 10^{-202}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;a \leq 3.3 \cdot 10^{-57}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 4 \cdot 10^{+106}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]

Alternative 26: 30.0% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -9.2 \cdot 10^{+116}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;b \leq -2.8 \cdot 10^{-9}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;b \leq -1.15 \cdot 10^{-120}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;b \leq 4.4 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b -9.2e+116)
   (* b (* x (- (* y a) (* j y0))))
   (if (<= b -2.8e-9)
     (* a (* y5 (- (* t y2) (* y y3))))
     (if (<= b -1.15e-120)
       (* a (* y (- (* x b) (* y3 y5))))
       (if (<= b 4.4e+83)
         (* c (* x (- (* y0 y2) (* y i))))
         (* b (* y (- (* x a) (* k 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 tmp;
	if (b <= -9.2e+116) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (b <= -2.8e-9) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (b <= -1.15e-120) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (b <= 4.4e+83) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else {
		tmp = b * (y * ((x * a) - (k * 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) :: tmp
    if (b <= (-9.2d+116)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (b <= (-2.8d-9)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (b <= (-1.15d-120)) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (b <= 4.4d+83) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else
        tmp = b * (y * ((x * a) - (k * 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 tmp;
	if (b <= -9.2e+116) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (b <= -2.8e-9) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (b <= -1.15e-120) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (b <= 4.4e+83) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else {
		tmp = b * (y * ((x * a) - (k * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if b <= -9.2e+116:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif b <= -2.8e-9:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif b <= -1.15e-120:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif b <= 4.4e+83:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	else:
		tmp = b * (y * ((x * a) - (k * y4)))
	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 (b <= -9.2e+116)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (b <= -2.8e-9)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (b <= -1.15e-120)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (b <= 4.4e+83)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	else
		tmp = Float64(b * Float64(y * Float64(Float64(x * a) - Float64(k * 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)
	tmp = 0.0;
	if (b <= -9.2e+116)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (b <= -2.8e-9)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (b <= -1.15e-120)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (b <= 4.4e+83)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	else
		tmp = b * (y * ((x * a) - (k * y4)));
	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[b, -9.2e+116], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -2.8e-9], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -1.15e-120], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 4.4e+83], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(y * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if b < -9.19999999999999979e116

   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. Taylor expanded in b around inf 50.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 50.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 50.5%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

      2. *-commutative 50.5%

         \[\leadsto b \cdot \left(x \cdot \left(y \cdot a - \color{blue}{y0 \cdot j}\right)\right) \]

   5. Simplified 50.5%

      \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a - y0 \cdot j\right)\right)} \]

   if -9.19999999999999979e116 < b < -2.79999999999999984e-9

   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. Taylor expanded in a around -inf 37.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 37.5%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 37.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 37.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 37.5%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y5 around -inf 33.1%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 33.1%

         \[\leadsto a \cdot \left(y5 \cdot \left(\color{blue}{y2 \cdot t} - y \cdot y3\right)\right) \]

      2. *-commutative 33.1%

         \[\leadsto a \cdot \left(y5 \cdot \left(y2 \cdot t - \color{blue}{y3 \cdot y}\right)\right) \]

   7. Simplified 33.1%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(y2 \cdot t - y3 \cdot y\right)\right)} \]

   if -2.79999999999999984e-9 < b < -1.14999999999999993e-120

   1. Initial program 43.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 48.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 48.3%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 48.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 48.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 48.3%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 44.1%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 44.1%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 44.1%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 44.1%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 44.1%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 44.1%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   if -1.14999999999999993e-120 < b < 4.39999999999999997e83

   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. Taylor expanded in c around inf 48.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 48.1%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + -1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      2. mul-1-neg 48.1%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) + \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)}\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      3. unsub-neg 48.1%

         \[\leadsto c \cdot \left(\color{blue}{\left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right)} - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      4. *-commutative 48.1%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      5. *-commutative 48.1%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right) - i \cdot \left(x \cdot y - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      6. *-commutative 48.1%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(\color{blue}{y \cdot x} - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \]

      7. *-commutative 48.1%

         \[\leadsto c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) \]

   4. Simplified 48.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(y0 \cdot \left(y2 \cdot x - z \cdot y3\right) - i \cdot \left(y \cdot x - t \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} \]

   5. Taylor expanded in x around inf 35.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]

   if 4.39999999999999997e83 < b

   1. Initial program 17.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 51.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 45.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right)\right) \]

      3. unsub-neg 45.8%

         \[\leadsto b \cdot \left(y \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)}\right) \]

      4. *-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(\color{blue}{x \cdot a} - k \cdot y4\right)\right) \]

      5. *-commutative 45.8%

         \[\leadsto b \cdot \left(y \cdot \left(x \cdot a - \color{blue}{y4 \cdot k}\right)\right) \]

   5. Simplified 45.8%

      \[\leadsto b \cdot \color{blue}{\left(y \cdot \left(x \cdot a - y4 \cdot k\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 40.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \leq -9.2 \cdot 10^{+116}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;b \leq -2.8 \cdot 10^{-9}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;b \leq -1.15 \cdot 10^{-120}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;b \leq 4.4 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y \cdot \left(x \cdot a - k \cdot y4\right)\right)\\ \end{array} \]

Alternative 27: 22.5% accurate, 5.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{if}\;y3 \leq -1.25 \cdot 10^{+68}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y3 \leq -6.4 \cdot 10^{-203}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y3 \leq -4.4 \cdot 10^{-281}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;y3 \leq 9 \cdot 10^{-157}:\\ \;\;\;\;\left(x \cdot y1\right) \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;y3 \leq 2.6 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y5 (* y3 (- y))))))
   (if (<= y3 -1.25e+68)
     t_1
     (if (<= y3 -6.4e-203)
       (* (* x y) (* a b))
       (if (<= y3 -4.4e-281)
         (* (* b j) (* x (- y0)))
         (if (<= y3 9e-157)
           (* (* x y1) (* i j))
           (if (<= y3 2.6e+111) (* j (* y4 (* t b))) 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 = a * (y5 * (y3 * -y));
	double tmp;
	if (y3 <= -1.25e+68) {
		tmp = t_1;
	} else if (y3 <= -6.4e-203) {
		tmp = (x * y) * (a * b);
	} else if (y3 <= -4.4e-281) {
		tmp = (b * j) * (x * -y0);
	} else if (y3 <= 9e-157) {
		tmp = (x * y1) * (i * j);
	} else if (y3 <= 2.6e+111) {
		tmp = j * (y4 * (t * b));
	} 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 = a * (y5 * (y3 * -y))
    if (y3 <= (-1.25d+68)) then
        tmp = t_1
    else if (y3 <= (-6.4d-203)) then
        tmp = (x * y) * (a * b)
    else if (y3 <= (-4.4d-281)) then
        tmp = (b * j) * (x * -y0)
    else if (y3 <= 9d-157) then
        tmp = (x * y1) * (i * j)
    else if (y3 <= 2.6d+111) then
        tmp = j * (y4 * (t * b))
    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 = a * (y5 * (y3 * -y));
	double tmp;
	if (y3 <= -1.25e+68) {
		tmp = t_1;
	} else if (y3 <= -6.4e-203) {
		tmp = (x * y) * (a * b);
	} else if (y3 <= -4.4e-281) {
		tmp = (b * j) * (x * -y0);
	} else if (y3 <= 9e-157) {
		tmp = (x * y1) * (i * j);
	} else if (y3 <= 2.6e+111) {
		tmp = j * (y4 * (t * b));
	} 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 = a * (y5 * (y3 * -y))
	tmp = 0
	if y3 <= -1.25e+68:
		tmp = t_1
	elif y3 <= -6.4e-203:
		tmp = (x * y) * (a * b)
	elif y3 <= -4.4e-281:
		tmp = (b * j) * (x * -y0)
	elif y3 <= 9e-157:
		tmp = (x * y1) * (i * j)
	elif y3 <= 2.6e+111:
		tmp = j * (y4 * (t * b))
	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(a * Float64(y5 * Float64(y3 * Float64(-y))))
	tmp = 0.0
	if (y3 <= -1.25e+68)
		tmp = t_1;
	elseif (y3 <= -6.4e-203)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (y3 <= -4.4e-281)
		tmp = Float64(Float64(b * j) * Float64(x * Float64(-y0)));
	elseif (y3 <= 9e-157)
		tmp = Float64(Float64(x * y1) * Float64(i * j));
	elseif (y3 <= 2.6e+111)
		tmp = Float64(j * Float64(y4 * Float64(t * b)));
	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 = a * (y5 * (y3 * -y));
	tmp = 0.0;
	if (y3 <= -1.25e+68)
		tmp = t_1;
	elseif (y3 <= -6.4e-203)
		tmp = (x * y) * (a * b);
	elseif (y3 <= -4.4e-281)
		tmp = (b * j) * (x * -y0);
	elseif (y3 <= 9e-157)
		tmp = (x * y1) * (i * j);
	elseif (y3 <= 2.6e+111)
		tmp = j * (y4 * (t * b));
	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[(a * N[(y5 * N[(y3 * (-y)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y3, -1.25e+68], t$95$1, If[LessEqual[y3, -6.4e-203], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -4.4e-281], N[(N[(b * j), $MachinePrecision] * N[(x * (-y0)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 9e-157], N[(N[(x * y1), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 2.6e+111], N[(j * N[(y4 * N[(t * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if y3 < -1.2500000000000001e68 or 2.5999999999999999e111 < y3

   1. Initial program 25.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 42.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.7%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 42.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 42.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 42.7%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 43.0%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 43.0%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 43.0%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 43.0%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 43.0%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 43.0%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around 0 38.0%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 38.0%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. associate-*r* 40.0%

         \[\leadsto a \cdot \left(-\color{blue}{\left(y \cdot y3\right) \cdot y5}\right) \]

   10. Simplified 40.0%

       \[\leadsto a \cdot \color{blue}{\left(-\left(y \cdot y3\right) \cdot y5\right)} \]

   if -1.2500000000000001e68 < y3 < -6.40000000000000001e-203

   1. Initial program 32.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 31.5%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 31.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 31.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 31.5%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 28.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 28.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 28.6%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 28.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 28.6%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 28.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 25.6%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 15.6%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 15.5%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 16.9%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 16.9%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 16.9%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 17.0%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 27.0%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 27.0%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 27.0%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

   12. Simplified 27.0%

       \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(b \cdot a\right)} \]

   if -6.40000000000000001e-203 < y3 < -4.40000000000000008e-281

   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. Taylor expanded in j around inf 28.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 28.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 28.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 28.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 28.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 28.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 24.3%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 24.3%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 34.6%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 34.6%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. associate-*r* 39.8%

         \[\leadsto -\color{blue}{\left(b \cdot j\right) \cdot \left(x \cdot y0\right)} \]

      3. *-commutative 39.8%

         \[\leadsto -\left(b \cdot j\right) \cdot \color{blue}{\left(y0 \cdot x\right)} \]

   10. Simplified 39.8%

       \[\leadsto \color{blue}{-\left(b \cdot j\right) \cdot \left(y0 \cdot x\right)} \]

   if -4.40000000000000008e-281 < y3 < 8.99999999999999997e-157

   1. Initial program 36.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 37.1%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around inf 29.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 26.4%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      2. *-commutative 26.4%

         \[\leadsto \left(j \cdot x\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      3. *-commutative 26.4%

         \[\leadsto \left(j \cdot x\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   5. Simplified 26.4%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   6. Taylor expanded in y1 around inf 21.2%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 28.7%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(x \cdot y1\right)} \]

      2. *-commutative 28.7%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(y1 \cdot x\right)} \]

   8. Simplified 28.7%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(y1 \cdot x\right)} \]

   if 8.99999999999999997e-157 < y3 < 2.5999999999999999e111

   1. Initial program 37.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 32.1%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 30.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 26.2%

      \[\leadsto j \cdot \color{blue}{\left(b \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 28.4%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot t\right) \cdot y4\right)} \]

   6. Simplified 28.4%

      \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot t\right) \cdot y4\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 33.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -1.25 \cdot 10^{+68}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;y3 \leq -6.4 \cdot 10^{-203}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y3 \leq -4.4 \cdot 10^{-281}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;y3 \leq 9 \cdot 10^{-157}:\\ \;\;\;\;\left(x \cdot y1\right) \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;y3 \leq 2.6 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \end{array} \]

Alternative 28: 22.5% accurate, 5.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -7.6 \cdot 10^{+68}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;y3 \leq -3.7 \cdot 10^{-202}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y3 \leq -5.5 \cdot 10^{-281}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;y3 \leq 7.6 \cdot 10^{-153}:\\ \;\;\;\;\left(x \cdot y1\right) \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;y3 \leq 3.9 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -7.6e+68)
   (* a (* y5 (* y3 (- y))))
   (if (<= y3 -3.7e-202)
     (* (* x y) (* a b))
     (if (<= y3 -5.5e-281)
       (* (* b j) (* x (- y0)))
       (if (<= y3 7.6e-153)
         (* (* x y1) (* i j))
         (if (<= y3 3.9e+111)
           (* j (* y4 (* t b)))
           (* a (* y (* y3 (- 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 (y3 <= -7.6e+68) {
		tmp = a * (y5 * (y3 * -y));
	} else if (y3 <= -3.7e-202) {
		tmp = (x * y) * (a * b);
	} else if (y3 <= -5.5e-281) {
		tmp = (b * j) * (x * -y0);
	} else if (y3 <= 7.6e-153) {
		tmp = (x * y1) * (i * j);
	} else if (y3 <= 3.9e+111) {
		tmp = j * (y4 * (t * b));
	} else {
		tmp = a * (y * (y3 * -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 (y3 <= (-7.6d+68)) then
        tmp = a * (y5 * (y3 * -y))
    else if (y3 <= (-3.7d-202)) then
        tmp = (x * y) * (a * b)
    else if (y3 <= (-5.5d-281)) then
        tmp = (b * j) * (x * -y0)
    else if (y3 <= 7.6d-153) then
        tmp = (x * y1) * (i * j)
    else if (y3 <= 3.9d+111) then
        tmp = j * (y4 * (t * b))
    else
        tmp = a * (y * (y3 * -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 (y3 <= -7.6e+68) {
		tmp = a * (y5 * (y3 * -y));
	} else if (y3 <= -3.7e-202) {
		tmp = (x * y) * (a * b);
	} else if (y3 <= -5.5e-281) {
		tmp = (b * j) * (x * -y0);
	} else if (y3 <= 7.6e-153) {
		tmp = (x * y1) * (i * j);
	} else if (y3 <= 3.9e+111) {
		tmp = j * (y4 * (t * b));
	} else {
		tmp = a * (y * (y3 * -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 y3 <= -7.6e+68:
		tmp = a * (y5 * (y3 * -y))
	elif y3 <= -3.7e-202:
		tmp = (x * y) * (a * b)
	elif y3 <= -5.5e-281:
		tmp = (b * j) * (x * -y0)
	elif y3 <= 7.6e-153:
		tmp = (x * y1) * (i * j)
	elif y3 <= 3.9e+111:
		tmp = j * (y4 * (t * b))
	else:
		tmp = a * (y * (y3 * -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 (y3 <= -7.6e+68)
		tmp = Float64(a * Float64(y5 * Float64(y3 * Float64(-y))));
	elseif (y3 <= -3.7e-202)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (y3 <= -5.5e-281)
		tmp = Float64(Float64(b * j) * Float64(x * Float64(-y0)));
	elseif (y3 <= 7.6e-153)
		tmp = Float64(Float64(x * y1) * Float64(i * j));
	elseif (y3 <= 3.9e+111)
		tmp = Float64(j * Float64(y4 * Float64(t * b)));
	else
		tmp = Float64(a * Float64(y * Float64(y3 * Float64(-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 (y3 <= -7.6e+68)
		tmp = a * (y5 * (y3 * -y));
	elseif (y3 <= -3.7e-202)
		tmp = (x * y) * (a * b);
	elseif (y3 <= -5.5e-281)
		tmp = (b * j) * (x * -y0);
	elseif (y3 <= 7.6e-153)
		tmp = (x * y1) * (i * j);
	elseif (y3 <= 3.9e+111)
		tmp = j * (y4 * (t * b));
	else
		tmp = a * (y * (y3 * -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[LessEqual[y3, -7.6e+68], N[(a * N[(y5 * N[(y3 * (-y)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -3.7e-202], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -5.5e-281], N[(N[(b * j), $MachinePrecision] * N[(x * (-y0)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 7.6e-153], N[(N[(x * y1), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 3.9e+111], N[(j * N[(y4 * N[(t * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(y * N[(y3 * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if y3 < -7.6000000000000002e68

   1. Initial program 22.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 39.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 39.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 39.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 39.0%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 41.0%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 41.0%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 41.0%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 41.0%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 41.0%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 41.0%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around 0 32.8%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 32.8%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. associate-*r* 36.1%

         \[\leadsto a \cdot \left(-\color{blue}{\left(y \cdot y3\right) \cdot y5}\right) \]

   10. Simplified 36.1%

       \[\leadsto a \cdot \color{blue}{\left(-\left(y \cdot y3\right) \cdot y5\right)} \]

   if -7.6000000000000002e68 < y3 < -3.69999999999999991e-202

   1. Initial program 32.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 31.5%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 31.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 31.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 31.5%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 28.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 28.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 28.6%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 28.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 28.6%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 28.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 25.6%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 15.6%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 15.5%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 16.9%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 16.9%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 16.9%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 17.0%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 27.0%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 27.0%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 27.0%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

   12. Simplified 27.0%

       \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(b \cdot a\right)} \]

   if -3.69999999999999991e-202 < y3 < -5.5000000000000003e-281

   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. Taylor expanded in j around inf 28.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 28.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 28.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 28.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 28.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 28.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 24.3%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 24.3%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 24.3%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 34.6%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 34.6%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. associate-*r* 39.8%

         \[\leadsto -\color{blue}{\left(b \cdot j\right) \cdot \left(x \cdot y0\right)} \]

      3. *-commutative 39.8%

         \[\leadsto -\left(b \cdot j\right) \cdot \color{blue}{\left(y0 \cdot x\right)} \]

   10. Simplified 39.8%

       \[\leadsto \color{blue}{-\left(b \cdot j\right) \cdot \left(y0 \cdot x\right)} \]

   if -5.5000000000000003e-281 < y3 < 7.60000000000000046e-153

   1. Initial program 36.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 37.1%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around inf 29.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 26.4%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      2. *-commutative 26.4%

         \[\leadsto \left(j \cdot x\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      3. *-commutative 26.4%

         \[\leadsto \left(j \cdot x\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   5. Simplified 26.4%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   6. Taylor expanded in y1 around inf 21.2%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 28.7%

         \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(x \cdot y1\right)} \]

      2. *-commutative 28.7%

         \[\leadsto \left(i \cdot j\right) \cdot \color{blue}{\left(y1 \cdot x\right)} \]

   8. Simplified 28.7%

      \[\leadsto \color{blue}{\left(i \cdot j\right) \cdot \left(y1 \cdot x\right)} \]

   if 7.60000000000000046e-153 < y3 < 3.89999999999999979e111

   1. Initial program 37.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 32.1%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 30.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 26.2%

      \[\leadsto j \cdot \color{blue}{\left(b \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 28.4%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot t\right) \cdot y4\right)} \]

   6. Simplified 28.4%

      \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot t\right) \cdot y4\right)} \]

   if 3.89999999999999979e111 < y3

   1. Initial program 28.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 48.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 48.7%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 48.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 48.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 48.7%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 46.2%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 46.2%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 46.2%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 46.2%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 46.2%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 46.2%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around 0 46.4%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 46.4%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 46.4%

         \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

      3. distribute-rgt-neg-in 46.4%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(y3 \cdot \left(-y5\right)\right)}\right) \]

   10. Simplified 46.4%

       \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 33.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -7.6 \cdot 10^{+68}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;y3 \leq -3.7 \cdot 10^{-202}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y3 \leq -5.5 \cdot 10^{-281}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;y3 \leq 7.6 \cdot 10^{-153}:\\ \;\;\;\;\left(x \cdot y1\right) \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;y3 \leq 3.9 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \end{array} \]

Alternative 29: 20.7% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -1.6 \cdot 10^{+68}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 9.6 \cdot 10^{-31}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;j \leq 32000000000:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 2.05 \cdot 10^{+119}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= j -1.6e+68)
   (* b (* y4 (* t j)))
   (if (<= j 9.6e-31)
     (* (* x y) (* a b))
     (if (<= j 32000000000.0)
       (* j (* y0 (* y3 y5)))
       (if (<= j 2.05e+119) (* i (* j (* x y1))) (* (* b j) (* x (- 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 (j <= -1.6e+68) {
		tmp = b * (y4 * (t * j));
	} else if (j <= 9.6e-31) {
		tmp = (x * y) * (a * b);
	} else if (j <= 32000000000.0) {
		tmp = j * (y0 * (y3 * y5));
	} else if (j <= 2.05e+119) {
		tmp = i * (j * (x * y1));
	} else {
		tmp = (b * j) * (x * -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 (j <= (-1.6d+68)) then
        tmp = b * (y4 * (t * j))
    else if (j <= 9.6d-31) then
        tmp = (x * y) * (a * b)
    else if (j <= 32000000000.0d0) then
        tmp = j * (y0 * (y3 * y5))
    else if (j <= 2.05d+119) then
        tmp = i * (j * (x * y1))
    else
        tmp = (b * j) * (x * -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 (j <= -1.6e+68) {
		tmp = b * (y4 * (t * j));
	} else if (j <= 9.6e-31) {
		tmp = (x * y) * (a * b);
	} else if (j <= 32000000000.0) {
		tmp = j * (y0 * (y3 * y5));
	} else if (j <= 2.05e+119) {
		tmp = i * (j * (x * y1));
	} else {
		tmp = (b * j) * (x * -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 j <= -1.6e+68:
		tmp = b * (y4 * (t * j))
	elif j <= 9.6e-31:
		tmp = (x * y) * (a * b)
	elif j <= 32000000000.0:
		tmp = j * (y0 * (y3 * y5))
	elif j <= 2.05e+119:
		tmp = i * (j * (x * y1))
	else:
		tmp = (b * j) * (x * -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 (j <= -1.6e+68)
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	elseif (j <= 9.6e-31)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (j <= 32000000000.0)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	elseif (j <= 2.05e+119)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	else
		tmp = Float64(Float64(b * j) * Float64(x * Float64(-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 (j <= -1.6e+68)
		tmp = b * (y4 * (t * j));
	elseif (j <= 9.6e-31)
		tmp = (x * y) * (a * b);
	elseif (j <= 32000000000.0)
		tmp = j * (y0 * (y3 * y5));
	elseif (j <= 2.05e+119)
		tmp = i * (j * (x * y1));
	else
		tmp = (b * j) * (x * -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[j, -1.6e+68], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 9.6e-31], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 32000000000.0], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.05e+119], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * j), $MachinePrecision] * N[(x * (-y0)), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if j < -1.59999999999999997e68

   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. Taylor expanded in t around inf 37.1%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 40.5%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 31.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 34.6%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

   6. Simplified 34.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(j \cdot t\right) \cdot y4\right)} \]

   if -1.59999999999999997e68 < j < 9.6000000000000001e-31

   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. Taylor expanded in a around -inf 41.1%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 41.1%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 41.1%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 41.1%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 41.1%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 28.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 28.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 28.7%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 28.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 28.7%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 28.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 20.6%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 10.4%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 10.3%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 13.0%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 13.0%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 13.0%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 13.0%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 23.3%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 23.3%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 23.3%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

   12. Simplified 23.3%

       \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(b \cdot a\right)} \]

   if 9.6000000000000001e-31 < j < 3.2e10

   1. Initial program 37.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 22.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 22.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 22.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 22.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 22.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 22.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 37.8%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 37.8%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 37.8%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 37.8%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 37.8%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 37.8%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around inf 33.2%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   9. Step-by-step derivation

      1. *-commutative 33.2%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \]

   10. Simplified 33.2%

       \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y5 \cdot y3\right)\right)} \]

   if 3.2e10 < j < 2.0499999999999999e119

   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. Taylor expanded in x around inf 38.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around inf 39.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 39.5%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      2. *-commutative 39.5%

         \[\leadsto \left(j \cdot x\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      3. *-commutative 39.5%

         \[\leadsto \left(j \cdot x\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   5. Simplified 39.5%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   6. Taylor expanded in y1 around inf 39.0%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 39.0%

         \[\leadsto i \cdot \left(j \cdot \color{blue}{\left(y1 \cdot x\right)}\right) \]

   8. Simplified 39.0%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(y1 \cdot x\right)\right)} \]

   if 2.0499999999999999e119 < j

   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. Taylor expanded in j around inf 47.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 47.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 47.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 47.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 47.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 47.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 34.9%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 34.9%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 34.9%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 34.9%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 34.9%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 34.9%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 39.6%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. associate-*r* 43.6%

         \[\leadsto -\color{blue}{\left(b \cdot j\right) \cdot \left(x \cdot y0\right)} \]

      3. *-commutative 43.6%

         \[\leadsto -\left(b \cdot j\right) \cdot \color{blue}{\left(y0 \cdot x\right)} \]

   10. Simplified 43.6%

       \[\leadsto \color{blue}{-\left(b \cdot j\right) \cdot \left(y0 \cdot x\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 30.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.6 \cdot 10^{+68}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 9.6 \cdot 10^{-31}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;j \leq 32000000000:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 2.05 \cdot 10^{+119}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \end{array} \]

Alternative 30: 21.7% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(-y0\right)\\ \mathbf{if}\;x \leq -3.3 \cdot 10^{+221}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;x \leq -6.5 \cdot 10^{-96}:\\ \;\;\;\;\left(b \cdot j\right) \cdot t_1\\ \mathbf{elif}\;x \leq 3 \cdot 10^{-80}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;x \leq 9.2 \cdot 10^{+82}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot t_1\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (- y0))))
   (if (<= x -3.3e+221)
     (* b (* (* x y) a))
     (if (<= x -6.5e-96)
       (* (* b j) t_1)
       (if (<= x 3e-80)
         (* a (* y5 (* y3 (- y))))
         (if (<= x 9.2e+82) (* b (* y4 (* t j))) (* j (* b 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 = x * -y0;
	double tmp;
	if (x <= -3.3e+221) {
		tmp = b * ((x * y) * a);
	} else if (x <= -6.5e-96) {
		tmp = (b * j) * t_1;
	} else if (x <= 3e-80) {
		tmp = a * (y5 * (y3 * -y));
	} else if (x <= 9.2e+82) {
		tmp = b * (y4 * (t * j));
	} else {
		tmp = j * (b * 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 = x * -y0
    if (x <= (-3.3d+221)) then
        tmp = b * ((x * y) * a)
    else if (x <= (-6.5d-96)) then
        tmp = (b * j) * t_1
    else if (x <= 3d-80) then
        tmp = a * (y5 * (y3 * -y))
    else if (x <= 9.2d+82) then
        tmp = b * (y4 * (t * j))
    else
        tmp = j * (b * 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 = x * -y0;
	double tmp;
	if (x <= -3.3e+221) {
		tmp = b * ((x * y) * a);
	} else if (x <= -6.5e-96) {
		tmp = (b * j) * t_1;
	} else if (x <= 3e-80) {
		tmp = a * (y5 * (y3 * -y));
	} else if (x <= 9.2e+82) {
		tmp = b * (y4 * (t * j));
	} else {
		tmp = j * (b * 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 = x * -y0
	tmp = 0
	if x <= -3.3e+221:
		tmp = b * ((x * y) * a)
	elif x <= -6.5e-96:
		tmp = (b * j) * t_1
	elif x <= 3e-80:
		tmp = a * (y5 * (y3 * -y))
	elif x <= 9.2e+82:
		tmp = b * (y4 * (t * j))
	else:
		tmp = j * (b * 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(x * Float64(-y0))
	tmp = 0.0
	if (x <= -3.3e+221)
		tmp = Float64(b * Float64(Float64(x * y) * a));
	elseif (x <= -6.5e-96)
		tmp = Float64(Float64(b * j) * t_1);
	elseif (x <= 3e-80)
		tmp = Float64(a * Float64(y5 * Float64(y3 * Float64(-y))));
	elseif (x <= 9.2e+82)
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	else
		tmp = Float64(j * Float64(b * 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 = x * -y0;
	tmp = 0.0;
	if (x <= -3.3e+221)
		tmp = b * ((x * y) * a);
	elseif (x <= -6.5e-96)
		tmp = (b * j) * t_1;
	elseif (x <= 3e-80)
		tmp = a * (y5 * (y3 * -y));
	elseif (x <= 9.2e+82)
		tmp = b * (y4 * (t * j));
	else
		tmp = j * (b * 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[(x * (-y0)), $MachinePrecision]}, If[LessEqual[x, -3.3e+221], N[(b * N[(N[(x * y), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -6.5e-96], N[(N[(b * j), $MachinePrecision] * t$95$1), $MachinePrecision], If[LessEqual[x, 3e-80], N[(a * N[(y5 * N[(y3 * (-y)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 9.2e+82], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(b * t$95$1), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -3.29999999999999991e221

   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. Taylor expanded in a around -inf 31.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 31.0%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 31.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 31.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 31.0%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 48.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 48.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 48.7%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 48.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 48.7%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 48.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 48.7%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 22.2%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 22.2%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 22.0%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 22.0%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 22.0%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 22.0%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 48.5%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 48.5%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 48.5%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

       5. associate-*r* 48.7%

          \[\leadsto \color{blue}{\left(\left(y \cdot x\right) \cdot b\right) \cdot a} \]

       6. *-commutative 48.7%

          \[\leadsto \color{blue}{\left(b \cdot \left(y \cdot x\right)\right)} \cdot a \]

       7. associate-*l* 52.9%

          \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   12. Simplified 52.9%

       \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   if -3.29999999999999991e221 < x < -6.50000000000000001e-96

   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. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 25.6%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 25.6%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 30.1%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 30.1%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. associate-*r* 30.2%

         \[\leadsto -\color{blue}{\left(b \cdot j\right) \cdot \left(x \cdot y0\right)} \]

      3. *-commutative 30.2%

         \[\leadsto -\left(b \cdot j\right) \cdot \color{blue}{\left(y0 \cdot x\right)} \]

   10. Simplified 30.2%

       \[\leadsto \color{blue}{-\left(b \cdot j\right) \cdot \left(y0 \cdot x\right)} \]

   if -6.50000000000000001e-96 < x < 3.00000000000000007e-80

   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. Taylor expanded in a around -inf 38.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 38.7%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 38.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 38.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 38.7%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 27.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 27.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 27.8%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 27.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 27.8%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 27.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around 0 22.6%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 22.6%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. associate-*r* 24.8%

         \[\leadsto a \cdot \left(-\color{blue}{\left(y \cdot y3\right) \cdot y5}\right) \]

   10. Simplified 24.8%

       \[\leadsto a \cdot \color{blue}{\left(-\left(y \cdot y3\right) \cdot y5\right)} \]

   if 3.00000000000000007e-80 < x < 9.19999999999999953e82

   1. Initial program 50.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 47.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 35.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 29.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

   6. Simplified 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(j \cdot t\right) \cdot y4\right)} \]

   if 9.19999999999999953e82 < x

   1. Initial program 25.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 28.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 28.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 28.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 28.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 28.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 28.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 32.7%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 32.7%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 36.7%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 36.7%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(x \cdot y0\right)\right)} \]

      2. neg-mul-1 36.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(-b\right)} \cdot \left(x \cdot y0\right)\right) \]

      3. *-commutative 36.7%

         \[\leadsto j \cdot \left(\left(-b\right) \cdot \color{blue}{\left(y0 \cdot x\right)}\right) \]

   10. Simplified 36.7%

       \[\leadsto j \cdot \color{blue}{\left(\left(-b\right) \cdot \left(y0 \cdot x\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 31.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -3.3 \cdot 10^{+221}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;x \leq -6.5 \cdot 10^{-96}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;x \leq 3 \cdot 10^{-80}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;x \leq 9.2 \cdot 10^{+82}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(x \cdot \left(-y0\right)\right)\right)\\ \end{array} \]

Alternative 31: 21.7% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -4.8 \cdot 10^{+220}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;x \leq -9.4 \cdot 10^{-91}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;x \leq 9 \cdot 10^{-81}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;x \leq 1.02 \cdot 10^{+83}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -4.8e+220)
   (* b (* (* x y) a))
   (if (<= x -9.4e-91)
     (* (* b j) (* x (- y0)))
     (if (<= x 9e-81)
       (* a (* y5 (* y3 (- y))))
       (if (<= x 1.02e+83) (* b (* y4 (* t j))) (* b (* y0 (* x (- j)))))))))

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 <= -4.8e+220) {
		tmp = b * ((x * y) * a);
	} else if (x <= -9.4e-91) {
		tmp = (b * j) * (x * -y0);
	} else if (x <= 9e-81) {
		tmp = a * (y5 * (y3 * -y));
	} else if (x <= 1.02e+83) {
		tmp = b * (y4 * (t * j));
	} else {
		tmp = b * (y0 * (x * -j));
	}
	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 <= (-4.8d+220)) then
        tmp = b * ((x * y) * a)
    else if (x <= (-9.4d-91)) then
        tmp = (b * j) * (x * -y0)
    else if (x <= 9d-81) then
        tmp = a * (y5 * (y3 * -y))
    else if (x <= 1.02d+83) then
        tmp = b * (y4 * (t * j))
    else
        tmp = b * (y0 * (x * -j))
    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 <= -4.8e+220) {
		tmp = b * ((x * y) * a);
	} else if (x <= -9.4e-91) {
		tmp = (b * j) * (x * -y0);
	} else if (x <= 9e-81) {
		tmp = a * (y5 * (y3 * -y));
	} else if (x <= 1.02e+83) {
		tmp = b * (y4 * (t * j));
	} else {
		tmp = b * (y0 * (x * -j));
	}
	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 <= -4.8e+220:
		tmp = b * ((x * y) * a)
	elif x <= -9.4e-91:
		tmp = (b * j) * (x * -y0)
	elif x <= 9e-81:
		tmp = a * (y5 * (y3 * -y))
	elif x <= 1.02e+83:
		tmp = b * (y4 * (t * j))
	else:
		tmp = b * (y0 * (x * -j))
	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 <= -4.8e+220)
		tmp = Float64(b * Float64(Float64(x * y) * a));
	elseif (x <= -9.4e-91)
		tmp = Float64(Float64(b * j) * Float64(x * Float64(-y0)));
	elseif (x <= 9e-81)
		tmp = Float64(a * Float64(y5 * Float64(y3 * Float64(-y))));
	elseif (x <= 1.02e+83)
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	else
		tmp = Float64(b * Float64(y0 * Float64(x * Float64(-j))));
	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 <= -4.8e+220)
		tmp = b * ((x * y) * a);
	elseif (x <= -9.4e-91)
		tmp = (b * j) * (x * -y0);
	elseif (x <= 9e-81)
		tmp = a * (y5 * (y3 * -y));
	elseif (x <= 1.02e+83)
		tmp = b * (y4 * (t * j));
	else
		tmp = b * (y0 * (x * -j));
	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, -4.8e+220], N[(b * N[(N[(x * y), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -9.4e-91], N[(N[(b * j), $MachinePrecision] * N[(x * (-y0)), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 9e-81], N[(a * N[(y5 * N[(y3 * (-y)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.02e+83], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(y0 * N[(x * (-j)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -4.7999999999999996e220

   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. Taylor expanded in a around -inf 31.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 31.0%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 31.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 31.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 31.0%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 48.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 48.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 48.7%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 48.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 48.7%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 48.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 48.7%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 22.2%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 22.2%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 22.0%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 22.0%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 22.0%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 22.0%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 48.5%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 48.5%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 48.5%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

       5. associate-*r* 48.7%

          \[\leadsto \color{blue}{\left(\left(y \cdot x\right) \cdot b\right) \cdot a} \]

       6. *-commutative 48.7%

          \[\leadsto \color{blue}{\left(b \cdot \left(y \cdot x\right)\right)} \cdot a \]

       7. associate-*l* 52.9%

          \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   12. Simplified 52.9%

       \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   if -4.7999999999999996e220 < x < -9.40000000000000013e-91

   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. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 25.6%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 25.6%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 25.6%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 30.1%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 30.1%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. associate-*r* 30.2%

         \[\leadsto -\color{blue}{\left(b \cdot j\right) \cdot \left(x \cdot y0\right)} \]

      3. *-commutative 30.2%

         \[\leadsto -\left(b \cdot j\right) \cdot \color{blue}{\left(y0 \cdot x\right)} \]

   10. Simplified 30.2%

       \[\leadsto \color{blue}{-\left(b \cdot j\right) \cdot \left(y0 \cdot x\right)} \]

   if -9.40000000000000013e-91 < x < 9.000000000000001e-81

   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. Taylor expanded in a around -inf 38.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 38.7%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 38.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 38.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 38.7%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 27.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 27.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 27.8%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 27.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 27.8%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 27.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around 0 22.6%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 22.6%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. associate-*r* 24.8%

         \[\leadsto a \cdot \left(-\color{blue}{\left(y \cdot y3\right) \cdot y5}\right) \]

   10. Simplified 24.8%

       \[\leadsto a \cdot \color{blue}{\left(-\left(y \cdot y3\right) \cdot y5\right)} \]

   if 9.000000000000001e-81 < x < 1.0200000000000001e83

   1. Initial program 50.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 47.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 35.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 29.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

   6. Simplified 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(j \cdot t\right) \cdot y4\right)} \]

   if 1.0200000000000001e83 < x

   1. Initial program 25.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 28.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 28.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 28.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 28.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 28.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 28.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 32.7%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 32.7%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 32.7%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around 0 40.5%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 40.5%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. *-commutative 40.5%

         \[\leadsto -\color{blue}{\left(j \cdot \left(x \cdot y0\right)\right) \cdot b} \]

      3. distribute-rgt-neg-in 40.5%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y0\right)\right) \cdot \left(-b\right)} \]

      4. *-commutative 40.5%

         \[\leadsto \color{blue}{\left(\left(x \cdot y0\right) \cdot j\right)} \cdot \left(-b\right) \]

      5. *-commutative 40.5%

         \[\leadsto \left(\color{blue}{\left(y0 \cdot x\right)} \cdot j\right) \cdot \left(-b\right) \]

      6. associate-*l* 38.5%

         \[\leadsto \color{blue}{\left(y0 \cdot \left(x \cdot j\right)\right)} \cdot \left(-b\right) \]

      7. *-commutative 38.5%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(j \cdot x\right)}\right) \cdot \left(-b\right) \]

   10. Simplified 38.5%

       \[\leadsto \color{blue}{\left(y0 \cdot \left(j \cdot x\right)\right) \cdot \left(-b\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 32.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -4.8 \cdot 10^{+220}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;x \leq -9.4 \cdot 10^{-91}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(x \cdot \left(-y0\right)\right)\\ \mathbf{elif}\;x \leq 9 \cdot 10^{-81}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(y3 \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;x \leq 1.02 \cdot 10^{+83}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \end{array} \]

Alternative 32: 21.7% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{if}\;y4 \leq -3.5 \cdot 10^{+107}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 2500000000:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;y4 \leq 2.55 \cdot 10^{+58}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y4 \leq 3.8 \cdot 10^{+87}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (* b y4)))))
   (if (<= y4 -3.5e+107)
     t_1
     (if (<= y4 2500000000.0)
       (* b (* (* x y) a))
       (if (<= y4 2.55e+58)
         (* y0 (* j (* y3 y5)))
         (if (<= y4 3.8e+87) (* a (* (* x y) b)) 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 = j * (t * (b * y4));
	double tmp;
	if (y4 <= -3.5e+107) {
		tmp = t_1;
	} else if (y4 <= 2500000000.0) {
		tmp = b * ((x * y) * a);
	} else if (y4 <= 2.55e+58) {
		tmp = y0 * (j * (y3 * y5));
	} else if (y4 <= 3.8e+87) {
		tmp = a * ((x * y) * b);
	} 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 = j * (t * (b * y4))
    if (y4 <= (-3.5d+107)) then
        tmp = t_1
    else if (y4 <= 2500000000.0d0) then
        tmp = b * ((x * y) * a)
    else if (y4 <= 2.55d+58) then
        tmp = y0 * (j * (y3 * y5))
    else if (y4 <= 3.8d+87) then
        tmp = a * ((x * y) * b)
    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 = j * (t * (b * y4));
	double tmp;
	if (y4 <= -3.5e+107) {
		tmp = t_1;
	} else if (y4 <= 2500000000.0) {
		tmp = b * ((x * y) * a);
	} else if (y4 <= 2.55e+58) {
		tmp = y0 * (j * (y3 * y5));
	} else if (y4 <= 3.8e+87) {
		tmp = a * ((x * y) * b);
	} 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 = j * (t * (b * y4))
	tmp = 0
	if y4 <= -3.5e+107:
		tmp = t_1
	elif y4 <= 2500000000.0:
		tmp = b * ((x * y) * a)
	elif y4 <= 2.55e+58:
		tmp = y0 * (j * (y3 * y5))
	elif y4 <= 3.8e+87:
		tmp = a * ((x * y) * b)
	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(j * Float64(t * Float64(b * y4)))
	tmp = 0.0
	if (y4 <= -3.5e+107)
		tmp = t_1;
	elseif (y4 <= 2500000000.0)
		tmp = Float64(b * Float64(Float64(x * y) * a));
	elseif (y4 <= 2.55e+58)
		tmp = Float64(y0 * Float64(j * Float64(y3 * y5)));
	elseif (y4 <= 3.8e+87)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	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 = j * (t * (b * y4));
	tmp = 0.0;
	if (y4 <= -3.5e+107)
		tmp = t_1;
	elseif (y4 <= 2500000000.0)
		tmp = b * ((x * y) * a);
	elseif (y4 <= 2.55e+58)
		tmp = y0 * (j * (y3 * y5));
	elseif (y4 <= 3.8e+87)
		tmp = a * ((x * y) * b);
	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[(j * N[(t * N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -3.5e+107], t$95$1, If[LessEqual[y4, 2500000000.0], N[(b * N[(N[(x * y), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 2.55e+58], N[(y0 * N[(j * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 3.8e+87], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if y4 < -3.4999999999999997e107 or 3.80000000000000011e87 < y4

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 40.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 35.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 32.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4\right)}\right) \]

   if -3.4999999999999997e107 < y4 < 2.5e9

   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. Taylor expanded in a around -inf 40.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 40.5%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 40.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 40.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 40.5%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 32.3%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 32.3%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 32.3%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 32.3%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 32.3%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 32.3%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 20.4%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 9.8%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 9.8%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 13.2%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 13.2%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 13.2%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 13.2%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 23.7%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 23.7%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 23.7%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

       5. associate-*r* 20.4%

          \[\leadsto \color{blue}{\left(\left(y \cdot x\right) \cdot b\right) \cdot a} \]

       6. *-commutative 20.4%

          \[\leadsto \color{blue}{\left(b \cdot \left(y \cdot x\right)\right)} \cdot a \]

       7. associate-*l* 22.5%

          \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   12. Simplified 22.5%

       \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   if 2.5e9 < y4 < 2.55000000000000004e58

   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. Taylor expanded in j around inf 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 31.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 39.4%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 39.4%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around inf 32.6%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 32.6%

         \[\leadsto \color{blue}{\left(j \cdot y0\right) \cdot \left(y3 \cdot y5\right)} \]

      2. *-commutative 32.6%

         \[\leadsto \color{blue}{\left(y0 \cdot j\right)} \cdot \left(y3 \cdot y5\right) \]

      3. *-commutative 32.6%

         \[\leadsto \left(y0 \cdot j\right) \cdot \color{blue}{\left(y5 \cdot y3\right)} \]

      4. associate-*l* 39.8%

         \[\leadsto \color{blue}{y0 \cdot \left(j \cdot \left(y5 \cdot y3\right)\right)} \]

   10. Simplified 39.8%

       \[\leadsto \color{blue}{y0 \cdot \left(j \cdot \left(y5 \cdot y3\right)\right)} \]

   if 2.55000000000000004e58 < y4 < 3.80000000000000011e87

   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. Taylor expanded in a around -inf 62.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 62.5%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 62.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 62.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 62.5%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 62.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 62.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 62.8%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 62.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 62.8%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 62.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 75.3%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 28.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -3.5 \cdot 10^{+107}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 2500000000:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;y4 \leq 2.55 \cdot 10^{+58}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y4 \leq 3.8 \cdot 10^{+87}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \end{array} \]

Alternative 33: 21.4% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ t_2 := \left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{if}\;y4 \leq -2.4 \cdot 10^{+107}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 3000000000:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq 3.5 \cdot 10^{+55}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y4 \leq 3.5 \cdot 10^{+86}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (* b y4)))) (t_2 (* (* x y) (* a b))))
   (if (<= y4 -2.4e+107)
     t_1
     (if (<= y4 3000000000.0)
       t_2
       (if (<= y4 3.5e+55)
         (* y0 (* j (* y3 y5)))
         (if (<= y4 3.5e+86) t_2 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 = j * (t * (b * y4));
	double t_2 = (x * y) * (a * b);
	double tmp;
	if (y4 <= -2.4e+107) {
		tmp = t_1;
	} else if (y4 <= 3000000000.0) {
		tmp = t_2;
	} else if (y4 <= 3.5e+55) {
		tmp = y0 * (j * (y3 * y5));
	} else if (y4 <= 3.5e+86) {
		tmp = t_2;
	} 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) :: t_2
    real(8) :: tmp
    t_1 = j * (t * (b * y4))
    t_2 = (x * y) * (a * b)
    if (y4 <= (-2.4d+107)) then
        tmp = t_1
    else if (y4 <= 3000000000.0d0) then
        tmp = t_2
    else if (y4 <= 3.5d+55) then
        tmp = y0 * (j * (y3 * y5))
    else if (y4 <= 3.5d+86) then
        tmp = t_2
    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 = j * (t * (b * y4));
	double t_2 = (x * y) * (a * b);
	double tmp;
	if (y4 <= -2.4e+107) {
		tmp = t_1;
	} else if (y4 <= 3000000000.0) {
		tmp = t_2;
	} else if (y4 <= 3.5e+55) {
		tmp = y0 * (j * (y3 * y5));
	} else if (y4 <= 3.5e+86) {
		tmp = t_2;
	} 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 = j * (t * (b * y4))
	t_2 = (x * y) * (a * b)
	tmp = 0
	if y4 <= -2.4e+107:
		tmp = t_1
	elif y4 <= 3000000000.0:
		tmp = t_2
	elif y4 <= 3.5e+55:
		tmp = y0 * (j * (y3 * y5))
	elif y4 <= 3.5e+86:
		tmp = t_2
	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(j * Float64(t * Float64(b * y4)))
	t_2 = Float64(Float64(x * y) * Float64(a * b))
	tmp = 0.0
	if (y4 <= -2.4e+107)
		tmp = t_1;
	elseif (y4 <= 3000000000.0)
		tmp = t_2;
	elseif (y4 <= 3.5e+55)
		tmp = Float64(y0 * Float64(j * Float64(y3 * y5)));
	elseif (y4 <= 3.5e+86)
		tmp = t_2;
	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 = j * (t * (b * y4));
	t_2 = (x * y) * (a * b);
	tmp = 0.0;
	if (y4 <= -2.4e+107)
		tmp = t_1;
	elseif (y4 <= 3000000000.0)
		tmp = t_2;
	elseif (y4 <= 3.5e+55)
		tmp = y0 * (j * (y3 * y5));
	elseif (y4 <= 3.5e+86)
		tmp = t_2;
	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[(j * N[(t * N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -2.4e+107], t$95$1, If[LessEqual[y4, 3000000000.0], t$95$2, If[LessEqual[y4, 3.5e+55], N[(y0 * N[(j * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 3.5e+86], t$95$2, t$95$1]]]]]]

Derivation

1. Split input into 3 regimes

2. if y4 < -2.4000000000000001e107 or 3.50000000000000019e86 < y4

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 40.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 35.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 32.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4\right)}\right) \]

   if -2.4000000000000001e107 < y4 < 3e9 or 3.5000000000000001e55 < y4 < 3.50000000000000019e86

   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. Taylor expanded in a around -inf 41.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 41.7%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 41.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 41.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 41.7%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 33.9%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 33.9%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 33.9%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 33.9%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 33.9%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 33.9%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 23.4%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 11.4%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 11.4%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 14.5%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 14.5%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 14.5%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 14.5%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 26.6%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 26.6%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 26.6%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

   12. Simplified 26.6%

       \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(b \cdot a\right)} \]

   if 3e9 < y4 < 3.5000000000000001e55

   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. Taylor expanded in j around inf 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 31.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 39.4%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. *-commutative 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \left(-\color{blue}{x \cdot b}\right)\right)\right) \]

      4. unsub-neg 39.4%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - x \cdot b\right)}\right) \]

   7. Simplified 39.4%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)} \]

   8. Taylor expanded in y3 around inf 32.6%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 32.6%

         \[\leadsto \color{blue}{\left(j \cdot y0\right) \cdot \left(y3 \cdot y5\right)} \]

      2. *-commutative 32.6%

         \[\leadsto \color{blue}{\left(y0 \cdot j\right)} \cdot \left(y3 \cdot y5\right) \]

      3. *-commutative 32.6%

         \[\leadsto \left(y0 \cdot j\right) \cdot \color{blue}{\left(y5 \cdot y3\right)} \]

      4. associate-*l* 39.8%

         \[\leadsto \color{blue}{y0 \cdot \left(j \cdot \left(y5 \cdot y3\right)\right)} \]

   10. Simplified 39.8%

       \[\leadsto \color{blue}{y0 \cdot \left(j \cdot \left(y5 \cdot y3\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 29.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -2.4 \cdot 10^{+107}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 3000000000:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y4 \leq 3.5 \cdot 10^{+55}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y4 \leq 3.5 \cdot 10^{+86}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \end{array} \]

Alternative 34: 20.9% accurate, 7.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y4 \leq -3.6 \cdot 10^{+160}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;y4 \leq -3.3 \cdot 10^{-27}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 1.9 \cdot 10^{+86}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y4 -3.6e+160)
   (* b (* y4 (* t j)))
   (if (<= y4 -3.3e-27)
     (* i (* j (* x y1)))
     (if (<= y4 1.9e+86) (* b (* (* x y) a)) (* j (* b (* 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 tmp;
	if (y4 <= -3.6e+160) {
		tmp = b * (y4 * (t * j));
	} else if (y4 <= -3.3e-27) {
		tmp = i * (j * (x * y1));
	} else if (y4 <= 1.9e+86) {
		tmp = b * ((x * y) * a);
	} else {
		tmp = j * (b * (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) :: tmp
    if (y4 <= (-3.6d+160)) then
        tmp = b * (y4 * (t * j))
    else if (y4 <= (-3.3d-27)) then
        tmp = i * (j * (x * y1))
    else if (y4 <= 1.9d+86) then
        tmp = b * ((x * y) * a)
    else
        tmp = j * (b * (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 tmp;
	if (y4 <= -3.6e+160) {
		tmp = b * (y4 * (t * j));
	} else if (y4 <= -3.3e-27) {
		tmp = i * (j * (x * y1));
	} else if (y4 <= 1.9e+86) {
		tmp = b * ((x * y) * a);
	} else {
		tmp = j * (b * (t * y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y4 <= -3.6e+160:
		tmp = b * (y4 * (t * j))
	elif y4 <= -3.3e-27:
		tmp = i * (j * (x * y1))
	elif y4 <= 1.9e+86:
		tmp = b * ((x * y) * a)
	else:
		tmp = j * (b * (t * y4))
	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 (y4 <= -3.6e+160)
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	elseif (y4 <= -3.3e-27)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (y4 <= 1.9e+86)
		tmp = Float64(b * Float64(Float64(x * y) * a));
	else
		tmp = Float64(j * Float64(b * 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)
	tmp = 0.0;
	if (y4 <= -3.6e+160)
		tmp = b * (y4 * (t * j));
	elseif (y4 <= -3.3e-27)
		tmp = i * (j * (x * y1));
	elseif (y4 <= 1.9e+86)
		tmp = b * ((x * y) * a);
	else
		tmp = j * (b * (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_] := If[LessEqual[y4, -3.6e+160], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -3.3e-27], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.9e+86], N[(b * N[(N[(x * y), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision], N[(j * N[(b * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y4 < -3.60000000000000021e160

   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. Taylor expanded in t around inf 44.9%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 38.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 28.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 28.6%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

   6. Simplified 28.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(j \cdot t\right) \cdot y4\right)} \]

   if -3.60000000000000021e160 < y4 < -3.29999999999999998e-27

   1. Initial program 25.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 42.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around inf 26.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 23.9%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

      2. *-commutative 23.9%

         \[\leadsto \left(j \cdot x\right) \cdot \left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \]

      3. *-commutative 23.9%

         \[\leadsto \left(j \cdot x\right) \cdot \left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \]

   5. Simplified 23.9%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(y1 \cdot i - y0 \cdot b\right)} \]

   6. Taylor expanded in y1 around inf 16.0%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 16.0%

         \[\leadsto i \cdot \left(j \cdot \color{blue}{\left(y1 \cdot x\right)}\right) \]

   8. Simplified 16.0%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(y1 \cdot x\right)\right)} \]

   if -3.29999999999999998e-27 < y4 < 1.89999999999999989e86

   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. Taylor expanded in a around -inf 41.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 41.7%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 41.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 41.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 41.7%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 35.5%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 35.5%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 35.5%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 35.5%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 35.5%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 35.5%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 24.9%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 12.8%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 12.8%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 15.5%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 15.5%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 15.5%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 15.5%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 27.6%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 27.6%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 27.6%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

       5. associate-*r* 24.9%

          \[\leadsto \color{blue}{\left(\left(y \cdot x\right) \cdot b\right) \cdot a} \]

       6. *-commutative 24.9%

          \[\leadsto \color{blue}{\left(b \cdot \left(y \cdot x\right)\right)} \cdot a \]

       7. associate-*l* 26.3%

          \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   12. Simplified 26.3%

       \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   if 1.89999999999999989e86 < y4

   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. Taylor expanded in t around inf 40.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 40.6%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 37.0%

      \[\leadsto j \cdot \color{blue}{\left(b \cdot \left(t \cdot y4\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 27.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -3.6 \cdot 10^{+160}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;y4 \leq -3.3 \cdot 10^{-27}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 1.9 \cdot 10^{+86}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 35: 21.7% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -2.85 \cdot 10^{-61} \lor \neg \left(x \leq 1.9 \cdot 10^{+83}\right):\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= x -2.85e-61) (not (<= x 1.9e+83)))
   (* a (* y (* x b)))
   (* b (* y4 (* t j)))))

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 <= -2.85e-61) || !(x <= 1.9e+83)) {
		tmp = a * (y * (x * b));
	} else {
		tmp = b * (y4 * (t * j));
	}
	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 <= (-2.85d-61)) .or. (.not. (x <= 1.9d+83))) then
        tmp = a * (y * (x * b))
    else
        tmp = b * (y4 * (t * j))
    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 <= -2.85e-61) || !(x <= 1.9e+83)) {
		tmp = a * (y * (x * b));
	} else {
		tmp = b * (y4 * (t * j));
	}
	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 <= -2.85e-61) or not (x <= 1.9e+83):
		tmp = a * (y * (x * b))
	else:
		tmp = b * (y4 * (t * j))
	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 <= -2.85e-61) || !(x <= 1.9e+83))
		tmp = Float64(a * Float64(y * Float64(x * b)));
	else
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	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 <= -2.85e-61) || ~((x <= 1.9e+83)))
		tmp = a * (y * (x * b));
	else
		tmp = b * (y4 * (t * j));
	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[x, -2.85e-61], N[Not[LessEqual[x, 1.9e+83]], $MachinePrecision]], N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < -2.85000000000000003e-61 or 1.9000000000000001e83 < x

   1. Initial program 26.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 40.2%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 40.2%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 40.2%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 40.2%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 40.2%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 33.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 33.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 33.6%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 33.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 33.6%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 33.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 29.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
   9. Step-by-step derivation

      1. *-commutative 29.9%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   10. Simplified 29.9%

       \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   if -2.85000000000000003e-61 < x < 1.9000000000000001e83

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 35.9%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 28.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 20.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 20.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

   6. Simplified 20.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(j \cdot t\right) \cdot y4\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 25.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.85 \cdot 10^{-61} \lor \neg \left(x \leq 1.9 \cdot 10^{+83}\right):\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \end{array} \]

Alternative 36: 21.8% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y4 \leq -2.45 \cdot 10^{+107} \lor \neg \left(y4 \leq 5.5 \cdot 10^{+87}\right):\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= y4 -2.45e+107) (not (<= y4 5.5e+87)))
   (* j (* t (* b y4)))
   (* b (* (* x y) a))))

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 ((y4 <= -2.45e+107) || !(y4 <= 5.5e+87)) {
		tmp = j * (t * (b * y4));
	} else {
		tmp = b * ((x * y) * a);
	}
	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 ((y4 <= (-2.45d+107)) .or. (.not. (y4 <= 5.5d+87))) then
        tmp = j * (t * (b * y4))
    else
        tmp = b * ((x * y) * a)
    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 ((y4 <= -2.45e+107) || !(y4 <= 5.5e+87)) {
		tmp = j * (t * (b * y4));
	} else {
		tmp = b * ((x * y) * a);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (y4 <= -2.45e+107) or not (y4 <= 5.5e+87):
		tmp = j * (t * (b * y4))
	else:
		tmp = b * ((x * y) * a)
	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 ((y4 <= -2.45e+107) || !(y4 <= 5.5e+87))
		tmp = Float64(j * Float64(t * Float64(b * y4)));
	else
		tmp = Float64(b * Float64(Float64(x * y) * a));
	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 ((y4 <= -2.45e+107) || ~((y4 <= 5.5e+87)))
		tmp = j * (t * (b * y4));
	else
		tmp = b * ((x * y) * a);
	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[y4, -2.45e+107], N[Not[LessEqual[y4, 5.5e+87]], $MachinePrecision]], N[(j * N[(t * N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(x * y), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y4 < -2.4500000000000001e107 or 5.50000000000000022e87 < y4

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 40.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 35.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 32.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4\right)}\right) \]

   if -2.4500000000000001e107 < y4 < 5.50000000000000022e87

   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. Taylor expanded in a around -inf 42.1%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.1%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 42.1%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 42.1%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 42.1%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 33.1%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 33.1%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 33.1%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 33.1%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 33.1%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 33.1%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 22.2%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 11.2%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 11.1%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 14.0%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 14.0%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 14.0%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 14.1%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 25.1%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 25.1%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 25.1%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

       5. associate-*r* 22.2%

          \[\leadsto \color{blue}{\left(\left(y \cdot x\right) \cdot b\right) \cdot a} \]

       6. *-commutative 22.2%

          \[\leadsto \color{blue}{\left(b \cdot \left(y \cdot x\right)\right)} \cdot a \]

       7. associate-*l* 24.0%

          \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   12. Simplified 24.0%

       \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 27.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -2.45 \cdot 10^{+107} \lor \neg \left(y4 \leq 5.5 \cdot 10^{+87}\right):\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \end{array} \]

Alternative 37: 21.9% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -1.65 \cdot 10^{-61}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;x \leq 9.2 \cdot 10^{+82}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -1.65e-61)
   (* b (* (* x y) a))
   (if (<= x 9.2e+82) (* b (* y4 (* t j))) (* a (* y (* x b))))))

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 <= -1.65e-61) {
		tmp = b * ((x * y) * a);
	} else if (x <= 9.2e+82) {
		tmp = b * (y4 * (t * j));
	} else {
		tmp = a * (y * (x * b));
	}
	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 <= (-1.65d-61)) then
        tmp = b * ((x * y) * a)
    else if (x <= 9.2d+82) then
        tmp = b * (y4 * (t * j))
    else
        tmp = a * (y * (x * b))
    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 <= -1.65e-61) {
		tmp = b * ((x * y) * a);
	} else if (x <= 9.2e+82) {
		tmp = b * (y4 * (t * j));
	} else {
		tmp = a * (y * (x * b));
	}
	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 <= -1.65e-61:
		tmp = b * ((x * y) * a)
	elif x <= 9.2e+82:
		tmp = b * (y4 * (t * j))
	else:
		tmp = a * (y * (x * b))
	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 <= -1.65e-61)
		tmp = Float64(b * Float64(Float64(x * y) * a));
	elseif (x <= 9.2e+82)
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	else
		tmp = Float64(a * Float64(y * Float64(x * b)));
	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 <= -1.65e-61)
		tmp = b * ((x * y) * a);
	elseif (x <= 9.2e+82)
		tmp = b * (y4 * (t * j));
	else
		tmp = a * (y * (x * b));
	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, -1.65e-61], N[(b * N[(N[(x * y), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 9.2e+82], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if x < -1.64999999999999998e-61

   1. Initial program 27.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 42.6%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.6%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 42.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 42.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 42.6%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 36.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 36.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 36.7%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 36.7%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 36.7%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 36.7%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 29.3%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. expm1-log1p-u 15.0%

         \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)\right)} \]

      2. expm1-udef 15.0%

         \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(a \cdot \left(b \cdot \left(x \cdot y\right)\right)\right)} - 1} \]

      3. associate-*r* 17.3%

         \[\leadsto e^{\mathsf{log1p}\left(\color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)}\right)} - 1 \]

      4. *-commutative 17.3%

         \[\leadsto e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)}\right)} - 1 \]

   10. Applied egg-rr 17.3%

       \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)} - 1} \]
   11. Step-by-step derivation

       1. expm1-def 17.3%

          \[\leadsto \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\left(a \cdot b\right) \cdot \left(y \cdot x\right)\right)\right)} \]

       2. expm1-log1p 31.7%

          \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

       3. *-commutative 31.7%

          \[\leadsto \color{blue}{\left(y \cdot x\right) \cdot \left(a \cdot b\right)} \]

       4. *-commutative 31.7%

          \[\leadsto \left(y \cdot x\right) \cdot \color{blue}{\left(b \cdot a\right)} \]

       5. associate-*r* 29.3%

          \[\leadsto \color{blue}{\left(\left(y \cdot x\right) \cdot b\right) \cdot a} \]

       6. *-commutative 29.3%

          \[\leadsto \color{blue}{\left(b \cdot \left(y \cdot x\right)\right)} \cdot a \]

       7. associate-*l* 31.7%

          \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   12. Simplified 31.7%

       \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot x\right) \cdot a\right)} \]

   if -1.64999999999999998e-61 < x < 9.19999999999999953e82

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in t around inf 35.9%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in j around inf 28.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   4. Taylor expanded in b around inf 20.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 20.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

   6. Simplified 20.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(j \cdot t\right) \cdot y4\right)} \]

   if 9.19999999999999953e82 < x

   1. Initial program 25.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in a around -inf 36.4%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 36.4%

         \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. *-commutative 36.4%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 36.4%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

   4. Simplified 36.4%

      \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

   5. Taylor expanded in y around inf 28.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 28.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 28.8%

         \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

      3. unsub-neg 28.8%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

      4. *-commutative 28.8%

         \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

   7. Simplified 28.8%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

   8. Taylor expanded in x around inf 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
   9. Step-by-step derivation

      1. *-commutative 29.1%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   10. Simplified 29.1%

       \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]
3. Recombined 3 regimes into one program.

4. Final simplification 25.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.65 \cdot 10^{-61}:\\ \;\;\;\;b \cdot \left(\left(x \cdot y\right) \cdot a\right)\\ \mathbf{elif}\;x \leq 9.2 \cdot 10^{+82}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \end{array} \]

Alternative 38: 26.0% accurate, 8.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* y (- (* x b) (* y3 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 * (y * ((x * b) - (y3 * 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 * (y * ((x * b) - (y3 * 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 * (y * ((x * b) - (y3 * y5)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (y * ((x * b) - (y3 * y5)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (y * ((x * b) - (y3 * y5)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 31.4%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in a around -inf 38.5%

   \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
3. Step-by-step derivation

   1. mul-1-neg 38.5%

      \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   2. *-commutative 38.5%

      \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

   3. distribute-rgt-neg-in 38.5%

      \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

4. Simplified 38.5%

   \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

5. Taylor expanded in y around inf 29.1%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
6. Step-by-step derivation

   1. +-commutative 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

   2. mul-1-neg 29.1%

      \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

   3. unsub-neg 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   4. *-commutative 29.1%

      \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

7. Simplified 29.1%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

8. Final simplification 29.1%

   \[\leadsto a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right) \]

Alternative 39: 16.3% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(\left(x \cdot y\right) \cdot b\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* (* x y) b)))

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 * ((x * y) * b);
}

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 * ((x * y) * b)
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 * ((x * y) * b);
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * ((x * y) * b)

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(Float64(x * y) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * ((x * y) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 31.4%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in a around -inf 38.5%

   \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
3. Step-by-step derivation

   1. mul-1-neg 38.5%

      \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   2. *-commutative 38.5%

      \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

   3. distribute-rgt-neg-in 38.5%

      \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

4. Simplified 38.5%

   \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

5. Taylor expanded in y around inf 29.1%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
6. Step-by-step derivation

   1. +-commutative 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

   2. mul-1-neg 29.1%

      \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

   3. unsub-neg 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   4. *-commutative 29.1%

      \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

7. Simplified 29.1%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

8. Taylor expanded in x around inf 18.6%

   \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]

9. Final simplification 18.6%

   \[\leadsto a \cdot \left(\left(x \cdot y\right) \cdot b\right) \]

Alternative 40: 16.5% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(y \cdot \left(x \cdot b\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* y (* x b))))

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 * (y * (x * b));
}

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 * (y * (x * b))
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 * (y * (x * b));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (y * (x * b))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(y * Float64(x * b)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (y * (x * b));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 31.4%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in a around -inf 38.5%

   \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
3. Step-by-step derivation

   1. mul-1-neg 38.5%

      \[\leadsto \color{blue}{-a \cdot \left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   2. *-commutative 38.5%

      \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot a} \]

   3. distribute-rgt-neg-in 38.5%

      \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right) + y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right) \cdot \left(-a\right)} \]

4. Simplified 38.5%

   \[\leadsto \color{blue}{\left(\left(y1 \cdot \left(y2 \cdot x - z \cdot y3\right) - b \cdot \left(y \cdot x - t \cdot z\right)\right) - y5 \cdot \left(t \cdot y2 - y3 \cdot y\right)\right) \cdot \left(-a\right)} \]

5. Taylor expanded in y around inf 29.1%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(-1 \cdot \left(y3 \cdot y5\right) + b \cdot x\right)\right)} \]
6. Step-by-step derivation

   1. +-commutative 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x + -1 \cdot \left(y3 \cdot y5\right)\right)}\right) \]

   2. mul-1-neg 29.1%

      \[\leadsto a \cdot \left(y \cdot \left(b \cdot x + \color{blue}{\left(-y3 \cdot y5\right)}\right)\right) \]

   3. unsub-neg 29.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x - y3 \cdot y5\right)}\right) \]

   4. *-commutative 29.1%

      \[\leadsto a \cdot \left(y \cdot \left(\color{blue}{x \cdot b} - y3 \cdot y5\right)\right) \]

7. Simplified 29.1%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)} \]

8. Taylor expanded in x around inf 18.9%

   \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
9. Step-by-step derivation

   1. *-commutative 18.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

10. Simplified 18.9%

    \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

11. Final simplification 18.9%

    \[\leadsto a \cdot \left(y \cdot \left(x \cdot b\right)\right) \]

Developer target: 28.0% accurate, 0.8× 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 2023336 
(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)))))