Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.0% → 39.5%

Time: 1.2min

Alternatives: 40

Speedup: 3.1×

• 88.6% 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: 30.0% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 39.5% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot y3 - k \cdot y2\\ t_2 := y0 \cdot \left(\left(y5 \cdot t\_1 + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ t_3 := t \cdot j - y \cdot k\\ t_4 := i \cdot y1 - b \cdot y0\\ \mathbf{if}\;y5 \leq -2.4 \cdot 10^{+71}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot t\_1 - i \cdot t\_3\right)\right)\\ \mathbf{elif}\;y5 \leq -4 \cdot 10^{-142}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot t\_4\right)\\ \mathbf{elif}\;y5 \leq -1 \cdot 10^{-268}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t\_3 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq 1.65 \cdot 10^{-286}:\\ \;\;\;\;y \cdot \left(\left(k \cdot \left(i \cdot y5 - b \cdot y4\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) + y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 6.5 \cdot 10^{-150}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y5 \leq 9.5 \cdot 10^{-13}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot t\_4\right)\\ \mathbf{elif}\;y5 \leq 8.5 \cdot 10^{+80}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* j y3) (* k y2)))
        (t_2
         (*
          y0
          (+
           (+ (* y5 t_1) (* c (- (* x y2) (* z y3))))
           (* b (- (* z k) (* x j))))))
        (t_3 (- (* t j) (* y k)))
        (t_4 (- (* i y1) (* b y0))))
   (if (<= y5 -2.4e+71)
     (* y5 (+ (* a (- (* t y2) (* y y3))) (- (* y0 t_1) (* i t_3))))
     (if (<= y5 -4e-142)
       (*
        x
        (+
         (- (* y2 (- (* c y0) (* a y1))) (* y (- (* c i) (* a b))))
         (* j t_4)))
       (if (<= y5 -1e-268)
         (*
          y4
          (+
           (+ (* b t_3) (* y1 (- (* k y2) (* j y3))))
           (* c (- (* y y3) (* t y2)))))
         (if (<= y5 1.65e-286)
           (*
            y
            (+
             (+ (* k (- (* i y5) (* b y4))) (* x (- (* a b) (* c i))))
             (* y3 (- (* c y4) (* a y5)))))
           (if (<= y5 6.5e-150)
             t_2
             (if (<= y5 9.5e-13)
               (*
                j
                (+
                 (+ (* y3 (- (* y0 y5) (* y1 y4))) (* t (- (* b y4) (* i y5))))
                 (* x t_4)))
               (if (<= y5 8.5e+80)
                 t_2
                 (* j (* y0 (- (* y3 y5) (* 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 t_1 = (j * y3) - (k * y2);
	double t_2 = y0 * (((y5 * t_1) + (c * ((x * y2) - (z * y3)))) + (b * ((z * k) - (x * j))));
	double t_3 = (t * j) - (y * k);
	double t_4 = (i * y1) - (b * y0);
	double tmp;
	if (y5 <= -2.4e+71) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * t_1) - (i * t_3)));
	} else if (y5 <= -4e-142) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * t_4));
	} else if (y5 <= -1e-268) {
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (y5 <= 1.65e-286) {
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))));
	} else if (y5 <= 6.5e-150) {
		tmp = t_2;
	} else if (y5 <= 9.5e-13) {
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_4));
	} else if (y5 <= 8.5e+80) {
		tmp = t_2;
	} else {
		tmp = j * (y0 * ((y3 * y5) - (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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = (j * y3) - (k * y2)
    t_2 = y0 * (((y5 * t_1) + (c * ((x * y2) - (z * y3)))) + (b * ((z * k) - (x * j))))
    t_3 = (t * j) - (y * k)
    t_4 = (i * y1) - (b * y0)
    if (y5 <= (-2.4d+71)) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * t_1) - (i * t_3)))
    else if (y5 <= (-4d-142)) then
        tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * t_4))
    else if (y5 <= (-1d-268)) then
        tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (y5 <= 1.65d-286) then
        tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))))
    else if (y5 <= 6.5d-150) then
        tmp = t_2
    else if (y5 <= 9.5d-13) then
        tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_4))
    else if (y5 <= 8.5d+80) then
        tmp = t_2
    else
        tmp = j * (y0 * ((y3 * y5) - (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 t_1 = (j * y3) - (k * y2);
	double t_2 = y0 * (((y5 * t_1) + (c * ((x * y2) - (z * y3)))) + (b * ((z * k) - (x * j))));
	double t_3 = (t * j) - (y * k);
	double t_4 = (i * y1) - (b * y0);
	double tmp;
	if (y5 <= -2.4e+71) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * t_1) - (i * t_3)));
	} else if (y5 <= -4e-142) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * t_4));
	} else if (y5 <= -1e-268) {
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (y5 <= 1.65e-286) {
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))));
	} else if (y5 <= 6.5e-150) {
		tmp = t_2;
	} else if (y5 <= 9.5e-13) {
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_4));
	} else if (y5 <= 8.5e+80) {
		tmp = t_2;
	} else {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (j * y3) - (k * y2)
	t_2 = y0 * (((y5 * t_1) + (c * ((x * y2) - (z * y3)))) + (b * ((z * k) - (x * j))))
	t_3 = (t * j) - (y * k)
	t_4 = (i * y1) - (b * y0)
	tmp = 0
	if y5 <= -2.4e+71:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * t_1) - (i * t_3)))
	elif y5 <= -4e-142:
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * t_4))
	elif y5 <= -1e-268:
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif y5 <= 1.65e-286:
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))))
	elif y5 <= 6.5e-150:
		tmp = t_2
	elif y5 <= 9.5e-13:
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_4))
	elif y5 <= 8.5e+80:
		tmp = t_2
	else:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	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(j * y3) - Float64(k * y2))
	t_2 = Float64(y0 * Float64(Float64(Float64(y5 * t_1) + Float64(c * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(b * Float64(Float64(z * k) - Float64(x * j)))))
	t_3 = Float64(Float64(t * j) - Float64(y * k))
	t_4 = Float64(Float64(i * y1) - Float64(b * y0))
	tmp = 0.0
	if (y5 <= -2.4e+71)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * t_1) - Float64(i * t_3))));
	elseif (y5 <= -4e-142)
		tmp = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * Float64(Float64(c * i) - Float64(a * b)))) + Float64(j * t_4)));
	elseif (y5 <= -1e-268)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_3) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (y5 <= 1.65e-286)
		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)))));
	elseif (y5 <= 6.5e-150)
		tmp = t_2;
	elseif (y5 <= 9.5e-13)
		tmp = Float64(j * Float64(Float64(Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * t_4)));
	elseif (y5 <= 8.5e+80)
		tmp = t_2;
	else
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - 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)
	t_1 = (j * y3) - (k * y2);
	t_2 = y0 * (((y5 * t_1) + (c * ((x * y2) - (z * y3)))) + (b * ((z * k) - (x * j))));
	t_3 = (t * j) - (y * k);
	t_4 = (i * y1) - (b * y0);
	tmp = 0.0;
	if (y5 <= -2.4e+71)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * t_1) - (i * t_3)));
	elseif (y5 <= -4e-142)
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * t_4));
	elseif (y5 <= -1e-268)
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (y5 <= 1.65e-286)
		tmp = y * (((k * ((i * y5) - (b * y4))) + (x * ((a * b) - (c * i)))) + (y3 * ((c * y4) - (a * y5))));
	elseif (y5 <= 6.5e-150)
		tmp = t_2;
	elseif (y5 <= 9.5e-13)
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_4));
	elseif (y5 <= 8.5e+80)
		tmp = t_2;
	else
		tmp = j * (y0 * ((y3 * y5) - (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_] := Block[{t$95$1 = N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y0 * N[(N[(N[(y5 * t$95$1), $MachinePrecision] + N[(c * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -2.4e+71], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * t$95$1), $MachinePrecision] - N[(i * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -4e-142], N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, -1e-268], N[(y4 * N[(N[(N[(b * t$95$3), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.65e-286], 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], If[LessEqual[y5, 6.5e-150], t$95$2, If[LessEqual[y5, 9.5e-13], N[(j * N[(N[(N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 8.5e+80], t$95$2, N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y5 < -2.39999999999999981e71

   1. Initial program 36.7%

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

   3. Taylor expanded in y5 around -inf 68.7%

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

   if -2.39999999999999981e71 < y5 < -4.0000000000000002e-142

   1. Initial program 36.1%

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

   3. Taylor expanded in x around inf 55.7%

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

   if -4.0000000000000002e-142 < y5 < -9.99999999999999958e-269

   1. Initial program 45.8%

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

   3. Taylor expanded in y4 around inf 46.6%

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

   if -9.99999999999999958e-269 < y5 < 1.6499999999999999e-286

   1. Initial program 20.0%

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

   3. Taylor expanded in y around inf 80.0%

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

   if 1.6499999999999999e-286 < y5 < 6.49999999999999997e-150 or 9.49999999999999991e-13 < y5 < 8.50000000000000007e80

   1. Initial program 34.2%

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

   3. Taylor expanded in y0 around inf 58.9%

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

   if 6.49999999999999997e-150 < y5 < 9.49999999999999991e-13

   1. Initial program 35.9%

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

   3. Taylor expanded in j around inf 60.5%

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

   if 8.50000000000000007e80 < y5

   1. Initial program 14.9%

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

   3. Taylor expanded in j around inf 36.1%

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

   4. Taylor expanded in y0 around inf 61.2%

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

4. Final simplification 59.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -2.4 \cdot 10^{+71}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;y5 \leq -4 \cdot 10^{-142}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y5 \leq -1 \cdot 10^{-268}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y5 \leq 1.65 \cdot 10^{-286}:\\ \;\;\;\;y \cdot \left(\left(k \cdot \left(i \cdot y5 - b \cdot y4\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) + y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 6.5 \cdot 10^{-150}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y5 \leq 9.5 \cdot 10^{-13}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y5 \leq 8.5 \cdot 10^{+80}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 55.0% accurate, 0.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot y0 - a \cdot y1\\ t_2 := \left(\left(\left(\left(\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k - x \cdot j\right) - \left(x \cdot y - z \cdot t\right) \cdot \left(c \cdot i - a \cdot b\right)\right) + t\_1 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + \left(c \cdot y4 - a \cdot y5\right) \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{if}\;t\_2 \leq \infty:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, i \cdot \left(-c\right)\right), y2 \cdot t\_1\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

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

C

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

Julia

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

Wolfram

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

Derivation

1. Split input into 2 regimes

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

   1. Initial program 89.8%

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

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

   1. Initial program 0.0%

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

   3. Taylor expanded in x around inf 35.9%

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

      1. fma-define 37.7%

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

      2. fma-neg 38.9%

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

   5. Simplified 38.9%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 57.2%

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

Alternative 3: 53.0% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y2 - z \cdot y3\\ t_2 := z \cdot k - x \cdot j\\ t_3 := \left(\left(\left(\left(\left(b \cdot y0 - i \cdot y1\right) \cdot t\_2 - \left(x \cdot y - z \cdot t\right) \cdot \left(c \cdot i - a \cdot b\right)\right) + \left(c \cdot y0 - a \cdot y1\right) \cdot t\_1\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + \left(c \cdot y4 - a \cdot y5\right) \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{if}\;t\_3 \leq \infty:\\ \;\;\;\;t\_3\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot t\_1\right) + b \cdot t\_2\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y2) (* z y3)))
        (t_2 (- (* z k) (* x j)))
        (t_3
         (+
          (+
           (+
            (+
             (-
              (* (- (* b y0) (* i y1)) t_2)
              (* (- (* x y) (* z t)) (- (* c i) (* a b))))
             (* (- (* c y0) (* a y1)) t_1))
            (* (- (* t j) (* y k)) (- (* b y4) (* i y5))))
           (* (- (* c y4) (* a y5)) (- (* y y3) (* t y2))))
          (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5))))))
   (if (<= t_3 INFINITY)
     t_3
     (* y0 (+ (+ (* y5 (- (* j y3) (* k y2))) (* c t_1)) (* b 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 = (x * y2) - (z * y3);
	double t_2 = (z * k) - (x * j);
	double t_3 = (((((((b * y0) - (i * y1)) * t_2) - (((x * y) - (z * t)) * ((c * i) - (a * b)))) + (((c * y0) - (a * y1)) * t_1)) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((c * y4) - (a * y5)) * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_3 <= ((double) INFINITY)) {
		tmp = t_3;
	} else {
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * t_2));
	}
	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 = (x * y2) - (z * y3);
	double t_2 = (z * k) - (x * j);
	double t_3 = (((((((b * y0) - (i * y1)) * t_2) - (((x * y) - (z * t)) * ((c * i) - (a * b)))) + (((c * y0) - (a * y1)) * t_1)) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((c * y4) - (a * y5)) * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_3 <= Double.POSITIVE_INFINITY) {
		tmp = t_3;
	} else {
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * 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 = (x * y2) - (z * y3)
	t_2 = (z * k) - (x * j)
	t_3 = (((((((b * y0) - (i * y1)) * t_2) - (((x * y) - (z * t)) * ((c * i) - (a * b)))) + (((c * y0) - (a * y1)) * t_1)) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((c * y4) - (a * y5)) * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if t_3 <= math.inf:
		tmp = t_3
	else:
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * 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(Float64(x * y2) - Float64(z * y3))
	t_2 = Float64(Float64(z * k) - Float64(x * j))
	t_3 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_2) - Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(c * i) - Float64(a * b)))) + Float64(Float64(Float64(c * y0) - Float64(a * y1)) * t_1)) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(Float64(Float64(c * y4) - Float64(a * y5)) * Float64(Float64(y * y3) - Float64(t * y2)))) + 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(y0 * Float64(Float64(Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(c * t_1)) + Float64(b * 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 = (x * y2) - (z * y3);
	t_2 = (z * k) - (x * j);
	t_3 = (((((((b * y0) - (i * y1)) * t_2) - (((x * y) - (z * t)) * ((c * i) - (a * b)))) + (((c * y0) - (a * y1)) * t_1)) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((c * y4) - (a * y5)) * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (t_3 <= Inf)
		tmp = t_3;
	else
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * 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[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(N[(N[(N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision] * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $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[(y0 * N[(N[(N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(b * t$95$2), $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 89.8%

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

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

   1. Initial program 0.0%

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

   3. Taylor expanded in y0 around inf 38.1%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 56.7%

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

Alternative 4: 40.6% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot i - a \cdot b\\ t_2 := i \cdot y1 - b \cdot y0\\ t_3 := x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot t\_1\right) + j \cdot t\_2\right)\\ \mathbf{if}\;x \leq -2.15 \cdot 10^{+37}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;x \leq -2.7 \cdot 10^{-24}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -3.6 \cdot 10^{-137}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;x \leq -1.55 \cdot 10^{-168}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -9.2 \cdot 10^{-305}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 1.25 \cdot 10^{-270}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot t\_1\right)\right)\\ \mathbf{elif}\;x \leq 7 \cdot 10^{-216}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 11.5:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot t\_2\right)\\ \mathbf{elif}\;x \leq 8.2 \cdot 10^{+265}:\\ \;\;\;\;t\_3\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* c i) (* a b)))
        (t_2 (- (* i y1) (* b y0)))
        (t_3 (* x (+ (- (* y2 (- (* c y0) (* a y1))) (* y t_1)) (* j t_2)))))
   (if (<= x -2.15e+37)
     t_3
     (if (<= x -2.7e-24)
       (* a (* y3 (- (* z y1) (* y y5))))
       (if (<= x -3.6e-137)
         (*
          y5
          (+
           (* a (- (* t y2) (* y y3)))
           (- (* y0 (- (* j y3) (* k y2))) (* i (- (* t j) (* y k))))))
         (if (<= x -1.55e-168)
           (* c (* y3 (- (* y y4) (* z y0))))
           (if (<= x -9.2e-305)
             (* y (* y3 (- (* c y4) (* a y5))))
             (if (<= x 1.25e-270)
               (*
                z
                (+
                 (* k (- (* b y0) (* i y1)))
                 (+ (* y3 (- (* a y1) (* c y0))) (* t t_1))))
               (if (<= x 7e-216)
                 (* k (* y2 (- (* y1 y4) (* y0 y5))))
                 (if (<= x 11.5)
                   (*
                    j
                    (+
                     (+
                      (* y3 (- (* y0 y5) (* y1 y4)))
                      (* t (- (* b y4) (* i y5))))
                     (* x t_2)))
                   (if (<= x 8.2e+265)
                     t_3
                     (* 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 = (c * i) - (a * b);
	double t_2 = (i * y1) - (b * y0);
	double t_3 = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_1)) + (j * t_2));
	double tmp;
	if (x <= -2.15e+37) {
		tmp = t_3;
	} else if (x <= -2.7e-24) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (x <= -3.6e-137) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (x <= -1.55e-168) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (x <= -9.2e-305) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (x <= 1.25e-270) {
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * ((a * y1) - (c * y0))) + (t * t_1)));
	} else if (x <= 7e-216) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (x <= 11.5) {
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_2));
	} else if (x <= 8.2e+265) {
		tmp = t_3;
	} 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) :: t_3
    real(8) :: tmp
    t_1 = (c * i) - (a * b)
    t_2 = (i * y1) - (b * y0)
    t_3 = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_1)) + (j * t_2))
    if (x <= (-2.15d+37)) then
        tmp = t_3
    else if (x <= (-2.7d-24)) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (x <= (-3.6d-137)) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
    else if (x <= (-1.55d-168)) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (x <= (-9.2d-305)) then
        tmp = y * (y3 * ((c * y4) - (a * y5)))
    else if (x <= 1.25d-270) then
        tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * ((a * y1) - (c * y0))) + (t * t_1)))
    else if (x <= 7d-216) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (x <= 11.5d0) then
        tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_2))
    else if (x <= 8.2d+265) then
        tmp = t_3
    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 = (c * i) - (a * b);
	double t_2 = (i * y1) - (b * y0);
	double t_3 = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_1)) + (j * t_2));
	double tmp;
	if (x <= -2.15e+37) {
		tmp = t_3;
	} else if (x <= -2.7e-24) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (x <= -3.6e-137) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (x <= -1.55e-168) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (x <= -9.2e-305) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (x <= 1.25e-270) {
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * ((a * y1) - (c * y0))) + (t * t_1)));
	} else if (x <= 7e-216) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (x <= 11.5) {
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_2));
	} else if (x <= 8.2e+265) {
		tmp = t_3;
	} 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 = (c * i) - (a * b)
	t_2 = (i * y1) - (b * y0)
	t_3 = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_1)) + (j * t_2))
	tmp = 0
	if x <= -2.15e+37:
		tmp = t_3
	elif x <= -2.7e-24:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif x <= -3.6e-137:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
	elif x <= -1.55e-168:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif x <= -9.2e-305:
		tmp = y * (y3 * ((c * y4) - (a * y5)))
	elif x <= 1.25e-270:
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * ((a * y1) - (c * y0))) + (t * t_1)))
	elif x <= 7e-216:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif x <= 11.5:
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_2))
	elif x <= 8.2e+265:
		tmp = t_3
	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(Float64(c * i) - Float64(a * b))
	t_2 = Float64(Float64(i * y1) - Float64(b * y0))
	t_3 = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * t_1)) + Float64(j * t_2)))
	tmp = 0.0
	if (x <= -2.15e+37)
		tmp = t_3;
	elseif (x <= -2.7e-24)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (x <= -3.6e-137)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * Float64(Float64(t * j) - Float64(y * k))))));
	elseif (x <= -1.55e-168)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (x <= -9.2e-305)
		tmp = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))));
	elseif (x <= 1.25e-270)
		tmp = Float64(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) + Float64(Float64(y3 * Float64(Float64(a * y1) - Float64(c * y0))) + Float64(t * t_1))));
	elseif (x <= 7e-216)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (x <= 11.5)
		tmp = Float64(j * Float64(Float64(Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * t_2)));
	elseif (x <= 8.2e+265)
		tmp = t_3;
	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 = (c * i) - (a * b);
	t_2 = (i * y1) - (b * y0);
	t_3 = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_1)) + (j * t_2));
	tmp = 0.0;
	if (x <= -2.15e+37)
		tmp = t_3;
	elseif (x <= -2.7e-24)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (x <= -3.6e-137)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	elseif (x <= -1.55e-168)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (x <= -9.2e-305)
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	elseif (x <= 1.25e-270)
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * ((a * y1) - (c * y0))) + (t * t_1)));
	elseif (x <= 7e-216)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (x <= 11.5)
		tmp = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * ((b * y4) - (i * y5)))) + (x * t_2));
	elseif (x <= 8.2e+265)
		tmp = t_3;
	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[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -2.15e+37], t$95$3, If[LessEqual[x, -2.7e-24], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3.6e-137], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.55e-168], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -9.2e-305], N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.25e-270], N[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 7e-216], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 11.5], N[(j * N[(N[(N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 8.2e+265], t$95$3, 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 x < -2.1499999999999998e37 or 11.5 < x < 8.2000000000000007e265

   1. Initial program 32.9%

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

   3. Taylor expanded in x around inf 57.0%

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

   if -2.1499999999999998e37 < x < -2.70000000000000007e-24

   1. Initial program 0.5%

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

   3. Taylor expanded in y3 around -inf 36.4%

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

   4. Taylor expanded in a around -inf 73.1%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 73.1%

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

      2. mul-1-neg 73.1%

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

   6. Simplified 73.1%

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

   if -2.70000000000000007e-24 < x < -3.60000000000000006e-137

   1. Initial program 29.1%

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

   3. Taylor expanded in y5 around -inf 54.7%

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

   if -3.60000000000000006e-137 < x < -1.55e-168

   1. Initial program 37.5%

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

   3. Taylor expanded in y3 around -inf 26.8%

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

   4. Taylor expanded in c around inf 75.5%

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

   if -1.55e-168 < x < -9.1999999999999998e-305

   1. Initial program 33.3%

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

   3. Taylor expanded in y3 around -inf 55.7%

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

   4. Taylor expanded in y around inf 56.2%

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

   if -9.1999999999999998e-305 < x < 1.2499999999999999e-270

   1. Initial program 37.3%

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

   3. Taylor expanded in z around -inf 87.5%

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

   if 1.2499999999999999e-270 < x < 6.99999999999999965e-216

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 63.6%

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

   4. Taylor expanded in k around inf 90.9%

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

   if 6.99999999999999965e-216 < x < 11.5

   1. Initial program 47.7%

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

   3. Taylor expanded in j around inf 48.7%

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

   if 8.2000000000000007e265 < x

   1. Initial program 6.7%

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

   3. Taylor expanded in x around inf 53.3%

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

      1. fma-define 53.3%

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

      2. fma-neg 60.0%

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

   5. Simplified 60.0%

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

   6. Taylor expanded in c around inf 73.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 59.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.15 \cdot 10^{+37}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -2.7 \cdot 10^{-24}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -3.6 \cdot 10^{-137}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;x \leq -1.55 \cdot 10^{-168}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -9.2 \cdot 10^{-305}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 1.25 \cdot 10^{-270}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right)\right)\\ \mathbf{elif}\;x \leq 7 \cdot 10^{-216}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 11.5:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq 8.2 \cdot 10^{+265}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 36.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_2 := y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ t_3 := y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{if}\;j \leq -1.45 \cdot 10^{+262}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.8 \cdot 10^{+58}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;j \leq -9.6 \cdot 10^{-191}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.65 \cdot 10^{-268}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;j \leq 5.8 \cdot 10^{-173}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(a \cdot \frac{y5}{c} - y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 4.5 \cdot 10^{-143}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;j \leq 6 \cdot 10^{-29}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq 4.3 \cdot 10^{+43}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq 5.6 \cdot 10^{+208}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;t\_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          x
          (+
           (- (* y2 (- (* c y0) (* a y1))) (* y (- (* c i) (* a b))))
           (* j (- (* i y1) (* b y0))))))
        (t_2 (* y0 (* j (- (* y3 y5) (* x b)))))
        (t_3 (* y5 (* k (- (* y i) (* y0 y2))))))
   (if (<= j -1.45e+262)
     (* y3 (* y4 (- (* y c) (* j y1))))
     (if (<= j -1.8e+58)
       t_2
       (if (<= j -9.6e-191)
         (*
          y3
          (-
           (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0))))
           (* y (- (* a y5) (* c y4)))))
         (if (<= j 1.65e-268)
           t_3
           (if (<= j 5.8e-173)
             (* y2 (* t (* c (- (* a (/ y5 c)) y4))))
             (if (<= j 4.5e-143)
               t_3
               (if (<= j 6e-29)
                 t_1
                 (if (<= j 4.3e+43)
                   (* y1 (* z (- (* a y3) (* i k))))
                   (if (<= j 5.6e+208) t_1 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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	double t_2 = y0 * (j * ((y3 * y5) - (x * b)));
	double t_3 = y5 * (k * ((y * i) - (y0 * y2)));
	double tmp;
	if (j <= -1.45e+262) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.8e+58) {
		tmp = t_2;
	} else if (j <= -9.6e-191) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 1.65e-268) {
		tmp = t_3;
	} else if (j <= 5.8e-173) {
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	} else if (j <= 4.5e-143) {
		tmp = t_3;
	} else if (j <= 6e-29) {
		tmp = t_1;
	} else if (j <= 4.3e+43) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= 5.6e+208) {
		tmp = t_1;
	} 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) :: t_3
    real(8) :: tmp
    t_1 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
    t_2 = y0 * (j * ((y3 * y5) - (x * b)))
    t_3 = y5 * (k * ((y * i) - (y0 * y2)))
    if (j <= (-1.45d+262)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (j <= (-1.8d+58)) then
        tmp = t_2
    else if (j <= (-9.6d-191)) then
        tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))))
    else if (j <= 1.65d-268) then
        tmp = t_3
    else if (j <= 5.8d-173) then
        tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)))
    else if (j <= 4.5d-143) then
        tmp = t_3
    else if (j <= 6d-29) then
        tmp = t_1
    else if (j <= 4.3d+43) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (j <= 5.6d+208) then
        tmp = t_1
    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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	double t_2 = y0 * (j * ((y3 * y5) - (x * b)));
	double t_3 = y5 * (k * ((y * i) - (y0 * y2)));
	double tmp;
	if (j <= -1.45e+262) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.8e+58) {
		tmp = t_2;
	} else if (j <= -9.6e-191) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 1.65e-268) {
		tmp = t_3;
	} else if (j <= 5.8e-173) {
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	} else if (j <= 4.5e-143) {
		tmp = t_3;
	} else if (j <= 6e-29) {
		tmp = t_1;
	} else if (j <= 4.3e+43) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= 5.6e+208) {
		tmp = t_1;
	} 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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
	t_2 = y0 * (j * ((y3 * y5) - (x * b)))
	t_3 = y5 * (k * ((y * i) - (y0 * y2)))
	tmp = 0
	if j <= -1.45e+262:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif j <= -1.8e+58:
		tmp = t_2
	elif j <= -9.6e-191:
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))))
	elif j <= 1.65e-268:
		tmp = t_3
	elif j <= 5.8e-173:
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)))
	elif j <= 4.5e-143:
		tmp = t_3
	elif j <= 6e-29:
		tmp = t_1
	elif j <= 4.3e+43:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif j <= 5.6e+208:
		tmp = t_1
	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(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * Float64(Float64(c * i) - Float64(a * b)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))))
	t_2 = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))))
	t_3 = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))))
	tmp = 0.0
	if (j <= -1.45e+262)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (j <= -1.8e+58)
		tmp = t_2;
	elseif (j <= -9.6e-191)
		tmp = Float64(y3 * Float64(Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))) - Float64(y * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= 1.65e-268)
		tmp = t_3;
	elseif (j <= 5.8e-173)
		tmp = Float64(y2 * Float64(t * Float64(c * Float64(Float64(a * Float64(y5 / c)) - y4))));
	elseif (j <= 4.5e-143)
		tmp = t_3;
	elseif (j <= 6e-29)
		tmp = t_1;
	elseif (j <= 4.3e+43)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (j <= 5.6e+208)
		tmp = t_1;
	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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	t_2 = y0 * (j * ((y3 * y5) - (x * b)));
	t_3 = y5 * (k * ((y * i) - (y0 * y2)));
	tmp = 0.0;
	if (j <= -1.45e+262)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (j <= -1.8e+58)
		tmp = t_2;
	elseif (j <= -9.6e-191)
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	elseif (j <= 1.65e-268)
		tmp = t_3;
	elseif (j <= 5.8e-173)
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	elseif (j <= 4.5e-143)
		tmp = t_3;
	elseif (j <= 6e-29)
		tmp = t_1;
	elseif (j <= 4.3e+43)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (j <= 5.6e+208)
		tmp = t_1;
	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[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.45e+262], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.8e+58], t$95$2, If[LessEqual[j, -9.6e-191], N[(y3 * N[(N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.65e-268], t$95$3, If[LessEqual[j, 5.8e-173], N[(y2 * N[(t * N[(c * N[(N[(a * N[(y5 / c), $MachinePrecision]), $MachinePrecision] - y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.5e-143], t$95$3, If[LessEqual[j, 6e-29], t$95$1, If[LessEqual[j, 4.3e+43], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5.6e+208], t$95$1, t$95$2]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.4499999999999999e262

   1. Initial program 15.4%

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

   3. Taylor expanded in y3 around -inf 54.2%

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

   4. Taylor expanded in y4 around inf 69.8%

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

   if -1.4499999999999999e262 < j < -1.79999999999999998e58 or 5.60000000000000045e208 < j

   1. Initial program 23.5%

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

   3. Taylor expanded in y0 around inf 42.0%

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

   4. Taylor expanded in j around inf 60.4%

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

      1. *-commutative 60.4%

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

   6. Simplified 60.4%

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

   if -1.79999999999999998e58 < j < -9.5999999999999997e-191

   1. Initial program 37.3%

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

   3. Taylor expanded in y3 around -inf 55.9%

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

   if -9.5999999999999997e-191 < j < 1.64999999999999996e-268 or 5.7999999999999997e-173 < j < 4.5e-143

   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. Add Preprocessing

   3. Taylor expanded in y5 around -inf 47.1%

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

   4. Taylor expanded in k around inf 52.6%

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

      1. +-commutative 52.6%

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

      2. mul-1-neg 52.6%

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

      3. unsub-neg 52.6%

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

      4. *-commutative 52.6%

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

   6. Simplified 52.6%

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

   if 1.64999999999999996e-268 < j < 5.7999999999999997e-173

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 30.3%

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

   4. Taylor expanded in t around inf 50.7%

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

      1. *-commutative 50.7%

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

   6. Simplified 50.7%

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

   7. Taylor expanded in c around inf 50.9%

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

      1. associate-/l* 50.9%

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

   9. Simplified 50.9%

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

   if 4.5e-143 < j < 6.0000000000000005e-29 or 4.3e43 < j < 5.60000000000000045e208

   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. Add Preprocessing

   3. Taylor expanded in x around inf 56.7%

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

   if 6.0000000000000005e-29 < j < 4.3e43

   1. Initial program 55.2%

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

   3. Taylor expanded in y1 around inf 44.6%

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

   4. Taylor expanded in z around inf 67.2%

      \[\leadsto \color{blue}{y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 57.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.45 \cdot 10^{+262}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.8 \cdot 10^{+58}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;j \leq -9.6 \cdot 10^{-191}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.65 \cdot 10^{-268}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 5.8 \cdot 10^{-173}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(a \cdot \frac{y5}{c} - y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 4.5 \cdot 10^{-143}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 6 \cdot 10^{-29}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 4.3 \cdot 10^{+43}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq 5.6 \cdot 10^{+208}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 39.9% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y - z \cdot t\\ t_2 := x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_3 := t \cdot j - y \cdot k\\ \mathbf{if}\;x \leq -8.4 \cdot 10^{+38}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq -5.2 \cdot 10^{-31}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -1.55 \cdot 10^{-105}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{-150}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;x \leq -5.6 \cdot 10^{-173}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -1.05 \cdot 10^{-230}:\\ \;\;\;\;a \cdot \left(b \cdot t\_1\right)\\ \mathbf{elif}\;x \leq 1.1 \cdot 10^{-182}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t\_3 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq 1.05 \cdot 10^{-68}:\\ \;\;\;\;b \cdot \left(\left(a \cdot t\_1 + y4 \cdot t\_3\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;x \leq 0.0044:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y) (* z t)))
        (t_2
         (*
          x
          (+
           (- (* y2 (- (* c y0) (* a y1))) (* y (- (* c i) (* a b))))
           (* j (- (* i y1) (* b y0))))))
        (t_3 (- (* t j) (* y k))))
   (if (<= x -8.4e+38)
     t_2
     (if (<= x -5.2e-31)
       (* a (* y3 (- (* z y1) (* y y5))))
       (if (<= x -1.55e-105)
         (* y2 (* y0 (- (* x c) (* k y5))))
         (if (<= x -1.8e-150)
           (* y1 (* z (- (* a y3) (* i k))))
           (if (<= x -5.6e-173)
             (* x (* y (- (* a b) (* c i))))
             (if (<= x -1.05e-230)
               (* a (* b t_1))
               (if (<= x 1.1e-182)
                 (*
                  y4
                  (+
                   (+ (* b t_3) (* y1 (- (* k y2) (* j y3))))
                   (* c (- (* y y3) (* t y2)))))
                 (if (<= x 1.05e-68)
                   (*
                    b
                    (+ (+ (* a t_1) (* y4 t_3)) (* y0 (- (* z k) (* x j)))))
                   (if (<= x 0.0044)
                     (* k (* y2 (- (* y1 y4) (* y0 y5))))
                     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 = (x * y) - (z * t);
	double t_2 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	double t_3 = (t * j) - (y * k);
	double tmp;
	if (x <= -8.4e+38) {
		tmp = t_2;
	} else if (x <= -5.2e-31) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (x <= -1.55e-105) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else if (x <= -1.8e-150) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (x <= -5.6e-173) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -1.05e-230) {
		tmp = a * (b * t_1);
	} else if (x <= 1.1e-182) {
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (x <= 1.05e-68) {
		tmp = b * (((a * t_1) + (y4 * t_3)) + (y0 * ((z * k) - (x * j))));
	} else if (x <= 0.0044) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} 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) :: t_3
    real(8) :: tmp
    t_1 = (x * y) - (z * t)
    t_2 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
    t_3 = (t * j) - (y * k)
    if (x <= (-8.4d+38)) then
        tmp = t_2
    else if (x <= (-5.2d-31)) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (x <= (-1.55d-105)) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else if (x <= (-1.8d-150)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (x <= (-5.6d-173)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (x <= (-1.05d-230)) then
        tmp = a * (b * t_1)
    else if (x <= 1.1d-182) then
        tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (x <= 1.05d-68) then
        tmp = b * (((a * t_1) + (y4 * t_3)) + (y0 * ((z * k) - (x * j))))
    else if (x <= 0.0044d0) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    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 = (x * y) - (z * t);
	double t_2 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	double t_3 = (t * j) - (y * k);
	double tmp;
	if (x <= -8.4e+38) {
		tmp = t_2;
	} else if (x <= -5.2e-31) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (x <= -1.55e-105) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else if (x <= -1.8e-150) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (x <= -5.6e-173) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -1.05e-230) {
		tmp = a * (b * t_1);
	} else if (x <= 1.1e-182) {
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (x <= 1.05e-68) {
		tmp = b * (((a * t_1) + (y4 * t_3)) + (y0 * ((z * k) - (x * j))));
	} else if (x <= 0.0044) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} 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 = (x * y) - (z * t)
	t_2 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
	t_3 = (t * j) - (y * k)
	tmp = 0
	if x <= -8.4e+38:
		tmp = t_2
	elif x <= -5.2e-31:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif x <= -1.55e-105:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	elif x <= -1.8e-150:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif x <= -5.6e-173:
		tmp = x * (y * ((a * b) - (c * i)))
	elif x <= -1.05e-230:
		tmp = a * (b * t_1)
	elif x <= 1.1e-182:
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif x <= 1.05e-68:
		tmp = b * (((a * t_1) + (y4 * t_3)) + (y0 * ((z * k) - (x * j))))
	elif x <= 0.0044:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	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(Float64(x * y) - Float64(z * t))
	t_2 = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * Float64(Float64(c * i) - Float64(a * b)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))))
	t_3 = Float64(Float64(t * j) - Float64(y * k))
	tmp = 0.0
	if (x <= -8.4e+38)
		tmp = t_2;
	elseif (x <= -5.2e-31)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (x <= -1.55e-105)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (x <= -1.8e-150)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (x <= -5.6e-173)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (x <= -1.05e-230)
		tmp = Float64(a * Float64(b * t_1));
	elseif (x <= 1.1e-182)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_3) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (x <= 1.05e-68)
		tmp = Float64(b * Float64(Float64(Float64(a * t_1) + Float64(y4 * t_3)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (x <= 0.0044)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	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 = (x * y) - (z * t);
	t_2 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	t_3 = (t * j) - (y * k);
	tmp = 0.0;
	if (x <= -8.4e+38)
		tmp = t_2;
	elseif (x <= -5.2e-31)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (x <= -1.55e-105)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	elseif (x <= -1.8e-150)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (x <= -5.6e-173)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (x <= -1.05e-230)
		tmp = a * (b * t_1);
	elseif (x <= 1.1e-182)
		tmp = y4 * (((b * t_3) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (x <= 1.05e-68)
		tmp = b * (((a * t_1) + (y4 * t_3)) + (y0 * ((z * k) - (x * j))));
	elseif (x <= 0.0044)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	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[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -8.4e+38], t$95$2, If[LessEqual[x, -5.2e-31], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.55e-105], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.8e-150], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -5.6e-173], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.05e-230], N[(a * N[(b * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.1e-182], N[(y4 * N[(N[(N[(b * t$95$3), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.05e-68], N[(b * N[(N[(N[(a * t$95$1), $MachinePrecision] + N[(y4 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 0.0044], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if x < -8.4e38 or 0.00440000000000000027 < x

   1. Initial program 29.5%

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

   3. Taylor expanded in x around inf 56.1%

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

   if -8.4e38 < x < -5.19999999999999991e-31

   1. Initial program 0.5%

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

   3. Taylor expanded in y3 around -inf 33.4%

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

   4. Taylor expanded in a around -inf 67.3%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 67.3%

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

      2. mul-1-neg 67.3%

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

   6. Simplified 67.3%

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

   if -5.19999999999999991e-31 < x < -1.55000000000000007e-105

   1. Initial program 27.2%

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

   3. Taylor expanded in y2 around inf 53.8%

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

   4. Taylor expanded in y0 around inf 60.4%

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

      1. +-commutative 60.4%

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

      2. mul-1-neg 60.4%

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

      3. unsub-neg 60.4%

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

   6. Simplified 60.4%

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

   if -1.55000000000000007e-105 < x < -1.8000000000000001e-150

   1. Initial program 48.1%

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

   3. Taylor expanded in y1 around inf 35.2%

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

   4. Taylor expanded in z around inf 58.1%

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

   if -1.8000000000000001e-150 < x < -5.5999999999999998e-173

   1. Initial program 25.0%

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

   3. Taylor expanded in x around inf 38.0%

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

      1. fma-define 38.0%

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

      2. fma-neg 38.0%

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

   5. Simplified 38.0%

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

   6. Taylor expanded in y around inf 75.4%

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

   if -5.5999999999999998e-173 < x < -1.0499999999999999e-230

   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. Add Preprocessing

   3. Taylor expanded in b around inf 55.2%

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

   4. Taylor expanded in a around inf 64.1%

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

   if -1.0499999999999999e-230 < x < 1.1e-182

   1. Initial program 40.5%

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

   3. Taylor expanded in y4 around inf 57.2%

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

   if 1.1e-182 < x < 1.05000000000000004e-68

   1. Initial program 50.0%

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

   3. Taylor expanded in b around inf 61.1%

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

   if 1.05000000000000004e-68 < x < 0.00440000000000000027

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.3%

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

   4. Taylor expanded in k around inf 51.3%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 58.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -8.4 \cdot 10^{+38}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -5.2 \cdot 10^{-31}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -1.55 \cdot 10^{-105}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{-150}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;x \leq -5.6 \cdot 10^{-173}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -1.05 \cdot 10^{-230}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 1.1 \cdot 10^{-182}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq 1.05 \cdot 10^{-68}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;x \leq 0.0044:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 38.3% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;x \leq -1.45 \cdot 10^{+37}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -1.05 \cdot 10^{-27}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -2.2 \cdot 10^{-105}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{-151}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;x \leq -4.8 \cdot 10^{-172}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq 8.8 \cdot 10^{-274}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 10^{-215}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq 4.8 \cdot 10^{-74}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;x \leq 0.0018:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          x
          (+
           (- (* y2 (- (* c y0) (* a y1))) (* y (- (* c i) (* a b))))
           (* j (- (* i y1) (* b y0))))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= x -1.45e+37)
     t_1
     (if (<= x -1.05e-27)
       (* a (* y3 (- (* z y1) (* y y5))))
       (if (<= x -2.2e-105)
         (* y2 (* y0 (- (* x c) (* k y5))))
         (if (<= x -8.5e-151)
           (* y1 (* z (- (* a y3) (* i k))))
           (if (<= x -4.8e-172)
             (* x (* y (- (* a b) (* c i))))
             (if (<= x 8.8e-274)
               (* y (* y3 (- (* c y4) (* a y5))))
               (if (<= x 1e-215)
                 t_2
                 (if (<= x 4.8e-74)
                   (*
                    b
                    (+
                     (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
                     (* y0 (- (* z k) (* x j)))))
                   (if (<= x 0.0018) 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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -1.45e+37) {
		tmp = t_1;
	} else if (x <= -1.05e-27) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (x <= -2.2e-105) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else if (x <= -8.5e-151) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (x <= -4.8e-172) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= 8.8e-274) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (x <= 1e-215) {
		tmp = t_2;
	} else if (x <= 4.8e-74) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (x <= 0.0018) {
		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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (x <= (-1.45d+37)) then
        tmp = t_1
    else if (x <= (-1.05d-27)) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (x <= (-2.2d-105)) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else if (x <= (-8.5d-151)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (x <= (-4.8d-172)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (x <= 8.8d-274) then
        tmp = y * (y3 * ((c * y4) - (a * y5)))
    else if (x <= 1d-215) then
        tmp = t_2
    else if (x <= 4.8d-74) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else if (x <= 0.0018d0) 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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -1.45e+37) {
		tmp = t_1;
	} else if (x <= -1.05e-27) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (x <= -2.2e-105) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else if (x <= -8.5e-151) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (x <= -4.8e-172) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= 8.8e-274) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (x <= 1e-215) {
		tmp = t_2;
	} else if (x <= 4.8e-74) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (x <= 0.0018) {
		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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if x <= -1.45e+37:
		tmp = t_1
	elif x <= -1.05e-27:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif x <= -2.2e-105:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	elif x <= -8.5e-151:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif x <= -4.8e-172:
		tmp = x * (y * ((a * b) - (c * i)))
	elif x <= 8.8e-274:
		tmp = y * (y3 * ((c * y4) - (a * y5)))
	elif x <= 1e-215:
		tmp = t_2
	elif x <= 4.8e-74:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	elif x <= 0.0018:
		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(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * Float64(Float64(c * i) - Float64(a * b)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (x <= -1.45e+37)
		tmp = t_1;
	elseif (x <= -1.05e-27)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (x <= -2.2e-105)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (x <= -8.5e-151)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (x <= -4.8e-172)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (x <= 8.8e-274)
		tmp = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))));
	elseif (x <= 1e-215)
		tmp = t_2;
	elseif (x <= 4.8e-74)
		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 (x <= 0.0018)
		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 = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (x <= -1.45e+37)
		tmp = t_1;
	elseif (x <= -1.05e-27)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (x <= -2.2e-105)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	elseif (x <= -8.5e-151)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (x <= -4.8e-172)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (x <= 8.8e-274)
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	elseif (x <= 1e-215)
		tmp = t_2;
	elseif (x <= 4.8e-74)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	elseif (x <= 0.0018)
		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[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $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[x, -1.45e+37], t$95$1, If[LessEqual[x, -1.05e-27], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2.2e-105], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -8.5e-151], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -4.8e-172], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 8.8e-274], N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1e-215], t$95$2, If[LessEqual[x, 4.8e-74], 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[x, 0.0018], t$95$2, t$95$1]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if x < -1.44999999999999989e37 or 0.0018 < x

   1. Initial program 29.5%

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

   3. Taylor expanded in x around inf 56.1%

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

   if -1.44999999999999989e37 < x < -1.05000000000000008e-27

   1. Initial program 0.5%

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

   3. Taylor expanded in y3 around -inf 33.4%

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

   4. Taylor expanded in a around -inf 67.3%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(y3 \cdot \left(y1 \cdot z - y \cdot y5\right)\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 67.3%

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

      2. mul-1-neg 67.3%

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

   6. Simplified 67.3%

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

   if -1.05000000000000008e-27 < x < -2.20000000000000004e-105

   1. Initial program 27.2%

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

   3. Taylor expanded in y2 around inf 53.8%

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

   4. Taylor expanded in y0 around inf 60.4%

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

      1. +-commutative 60.4%

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

      2. mul-1-neg 60.4%

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

      3. unsub-neg 60.4%

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

   6. Simplified 60.4%

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

   if -2.20000000000000004e-105 < x < -8.49999999999999999e-151

   1. Initial program 48.1%

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

   3. Taylor expanded in y1 around inf 35.2%

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

   4. Taylor expanded in z around inf 58.1%

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

   if -8.49999999999999999e-151 < x < -4.8000000000000002e-172

   1. Initial program 14.3%

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

   3. Taylor expanded in x around inf 29.2%

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

      1. fma-define 29.2%

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

      2. fma-neg 29.2%

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

   5. Simplified 29.2%

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

   6. Taylor expanded in y around inf 71.8%

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

   if -4.8000000000000002e-172 < x < 8.7999999999999998e-274

   1. Initial program 36.3%

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

   3. Taylor expanded in y3 around -inf 52.1%

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

   4. Taylor expanded in y around inf 52.1%

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

   if 8.7999999999999998e-274 < x < 1.00000000000000004e-215 or 4.7999999999999998e-74 < x < 0.0018

   1. Initial program 34.4%

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

   3. Taylor expanded in y2 around inf 52.2%

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

   4. Taylor expanded in k around inf 66.3%

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

   if 1.00000000000000004e-215 < x < 4.7999999999999998e-74

   1. Initial program 56.0%

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

   3. Taylor expanded in b around inf 53.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 57.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.45 \cdot 10^{+37}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.05 \cdot 10^{-27}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -2.2 \cdot 10^{-105}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{-151}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;x \leq -4.8 \cdot 10^{-172}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq 8.8 \cdot 10^{-274}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 10^{-215}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 4.8 \cdot 10^{-74}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;x \leq 0.0018:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 31.9% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;y \leq -2.8 \cdot 10^{+278}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -5.8 \cdot 10^{+129}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -2.9 \cdot 10^{+64}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq -5.5 \cdot 10^{-216}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq -1.85 \cdot 10^{-295}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(a \cdot \frac{y5}{c} - y4\right)\right)\right)\\ \mathbf{elif}\;y \leq 7.4 \cdot 10^{-256}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y \leq 1.1 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 1.7 \cdot 10^{-166}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq 4.5 \cdot 10^{-101}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{+117}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 7.6 \cdot 10^{+217}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y0 (* j (- (* y3 y5) (* x b)))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= y -2.8e+278)
     (* c (* y3 (- (* y y4) (* z y0))))
     (if (<= y -5.8e+129)
       (* x (* y (- (* a b) (* c i))))
       (if (<= y -2.9e+64)
         t_2
         (if (<= y -5.5e-216)
           t_1
           (if (<= y -1.85e-295)
             (* y2 (* t (* c (- (* a (/ y5 c)) y4))))
             (if (<= y 7.4e-256)
               (* y1 (* z (- (* a y3) (* i k))))
               (if (<= y 1.1e-226)
                 (* j (* t (- (* b y4) (* i y5))))
                 (if (<= y 1.7e-166)
                   (* b (* y0 (- (* z k) (* x j))))
                   (if (<= y 4.5e-101)
                     t_2
                     (if (<= y 7.5e+117)
                       t_1
                       (if (<= y 7.6e+217)
                         (* a (* b (- (* x y) (* z t))))
                         (* y5 (* k (- (* y i) (* y0 y2)))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y0 * (j * ((y3 * y5) - (x * b)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y <= -2.8e+278) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (y <= -5.8e+129) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -2.9e+64) {
		tmp = t_2;
	} else if (y <= -5.5e-216) {
		tmp = t_1;
	} else if (y <= -1.85e-295) {
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	} else if (y <= 7.4e-256) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (y <= 1.1e-226) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 1.7e-166) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y <= 4.5e-101) {
		tmp = t_2;
	} else if (y <= 7.5e+117) {
		tmp = t_1;
	} else if (y <= 7.6e+217) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y0 * (j * ((y3 * y5) - (x * b)))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (y <= (-2.8d+278)) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (y <= (-5.8d+129)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y <= (-2.9d+64)) then
        tmp = t_2
    else if (y <= (-5.5d-216)) then
        tmp = t_1
    else if (y <= (-1.85d-295)) then
        tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)))
    else if (y <= 7.4d-256) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (y <= 1.1d-226) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y <= 1.7d-166) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (y <= 4.5d-101) then
        tmp = t_2
    else if (y <= 7.5d+117) then
        tmp = t_1
    else if (y <= 7.6d+217) then
        tmp = a * (b * ((x * y) - (z * t)))
    else
        tmp = y5 * (k * ((y * i) - (y0 * y2)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y0 * (j * ((y3 * y5) - (x * b)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (y <= -2.8e+278) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (y <= -5.8e+129) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -2.9e+64) {
		tmp = t_2;
	} else if (y <= -5.5e-216) {
		tmp = t_1;
	} else if (y <= -1.85e-295) {
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	} else if (y <= 7.4e-256) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (y <= 1.1e-226) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 1.7e-166) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y <= 4.5e-101) {
		tmp = t_2;
	} else if (y <= 7.5e+117) {
		tmp = t_1;
	} else if (y <= 7.6e+217) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y0 * (j * ((y3 * y5) - (x * b)))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if y <= -2.8e+278:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif y <= -5.8e+129:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y <= -2.9e+64:
		tmp = t_2
	elif y <= -5.5e-216:
		tmp = t_1
	elif y <= -1.85e-295:
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)))
	elif y <= 7.4e-256:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif y <= 1.1e-226:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y <= 1.7e-166:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif y <= 4.5e-101:
		tmp = t_2
	elif y <= 7.5e+117:
		tmp = t_1
	elif y <= 7.6e+217:
		tmp = a * (b * ((x * y) - (z * t)))
	else:
		tmp = y5 * (k * ((y * i) - (y0 * y2)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (y <= -2.8e+278)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (y <= -5.8e+129)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y <= -2.9e+64)
		tmp = t_2;
	elseif (y <= -5.5e-216)
		tmp = t_1;
	elseif (y <= -1.85e-295)
		tmp = Float64(y2 * Float64(t * Float64(c * Float64(Float64(a * Float64(y5 / c)) - y4))));
	elseif (y <= 7.4e-256)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (y <= 1.1e-226)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y <= 1.7e-166)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (y <= 4.5e-101)
		tmp = t_2;
	elseif (y <= 7.5e+117)
		tmp = t_1;
	elseif (y <= 7.6e+217)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	else
		tmp = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y0 * (j * ((y3 * y5) - (x * b)));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (y <= -2.8e+278)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (y <= -5.8e+129)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y <= -2.9e+64)
		tmp = t_2;
	elseif (y <= -5.5e-216)
		tmp = t_1;
	elseif (y <= -1.85e-295)
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	elseif (y <= 7.4e-256)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (y <= 1.1e-226)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y <= 1.7e-166)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (y <= 4.5e-101)
		tmp = t_2;
	elseif (y <= 7.5e+117)
		tmp = t_1;
	elseif (y <= 7.6e+217)
		tmp = a * (b * ((x * y) - (z * t)));
	else
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	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[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $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[y, -2.8e+278], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -5.8e+129], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -2.9e+64], t$95$2, If[LessEqual[y, -5.5e-216], t$95$1, If[LessEqual[y, -1.85e-295], N[(y2 * N[(t * N[(c * N[(N[(a * N[(y5 / c), $MachinePrecision]), $MachinePrecision] - y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 7.4e-256], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.1e-226], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.7e-166], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 4.5e-101], t$95$2, If[LessEqual[y, 7.5e+117], t$95$1, If[LessEqual[y, 7.6e+217], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y < -2.8000000000000001e278

   1. Initial program 14.1%

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

   3. Taylor expanded in y3 around -inf 59.4%

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

   4. Taylor expanded in c around inf 100.0%

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

   if -2.8000000000000001e278 < y < -5.80000000000000005e129

   1. Initial program 33.3%

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

   3. Taylor expanded in x around inf 54.1%

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

      1. fma-define 60.7%

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

      2. fma-neg 60.7%

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

   5. Simplified 60.7%

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

   6. Taylor expanded in y around inf 64.1%

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

   if -5.80000000000000005e129 < y < -2.89999999999999993e64 or 1.6999999999999999e-166 < y < 4.4999999999999998e-101

   1. Initial program 18.5%

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

   3. Taylor expanded in y2 around inf 52.0%

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

   4. Taylor expanded in k around inf 67.5%

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

   if -2.89999999999999993e64 < y < -5.49999999999999991e-216 or 4.4999999999999998e-101 < y < 7.5e117

   1. Initial program 34.7%

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

   3. Taylor expanded in y0 around inf 41.4%

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

   4. Taylor expanded in j around inf 46.3%

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

      1. *-commutative 46.3%

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

   6. Simplified 46.3%

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

   if -5.49999999999999991e-216 < y < -1.85e-295

   1. Initial program 38.4%

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

   3. Taylor expanded in y2 around inf 43.0%

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

   4. Taylor expanded in t around inf 43.4%

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

      1. *-commutative 43.4%

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

   6. Simplified 43.4%

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

   7. Taylor expanded in c around inf 43.4%

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

      1. associate-/l* 48.3%

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

   9. Simplified 48.3%

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

   if -1.85e-295 < y < 7.40000000000000057e-256

   1. Initial program 33.8%

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

   3. Taylor expanded in y1 around inf 40.2%

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

   4. Taylor expanded in z around inf 54.2%

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

   if 7.40000000000000057e-256 < y < 1.1e-226

   1. Initial program 14.3%

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

   3. Taylor expanded in j around inf 57.2%

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

   4. Taylor expanded in t around inf 85.8%

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

   if 1.1e-226 < y < 1.6999999999999999e-166

   1. Initial program 33.2%

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

   3. Taylor expanded in b around inf 40.8%

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

   4. Taylor expanded in y0 around inf 47.4%

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

   if 7.5e117 < y < 7.60000000000000004e217

   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. Add Preprocessing

   3. Taylor expanded in b around inf 65.5%

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

   4. Taylor expanded in a around inf 65.6%

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

   if 7.60000000000000004e217 < y

   1. Initial program 41.2%

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

   3. Taylor expanded in y5 around -inf 41.8%

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

   4. Taylor expanded in k around inf 66.1%

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

      1. +-commutative 66.1%

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

      2. mul-1-neg 66.1%

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

      3. unsub-neg 66.1%

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

      4. *-commutative 66.1%

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

   6. Simplified 66.1%

      \[\leadsto -1 \cdot \left(y5 \cdot \color{blue}{\left(k \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)}\right) \]
3. Recombined 10 regimes into one program.

4. Final simplification 57.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.8 \cdot 10^{+278}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -5.8 \cdot 10^{+129}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -2.9 \cdot 10^{+64}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -5.5 \cdot 10^{-216}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq -1.85 \cdot 10^{-295}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(a \cdot \frac{y5}{c} - y4\right)\right)\right)\\ \mathbf{elif}\;y \leq 7.4 \cdot 10^{-256}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y \leq 1.1 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 1.7 \cdot 10^{-166}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq 4.5 \cdot 10^{-101}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{+117}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq 7.6 \cdot 10^{+217}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 37.7% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;j \leq -1.35 \cdot 10^{+262}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.95 \cdot 10^{+58}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{-188}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.2 \cdot 10^{-279}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-174}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(i \cdot \left(x \cdot y - z \cdot t\right) - y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-135}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{+207}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y0 (* j (- (* y3 y5) (* x b))))))
   (if (<= j -1.35e+262)
     (* y3 (* y4 (- (* y c) (* j y1))))
     (if (<= j -1.95e+58)
       t_1
       (if (<= j -8.5e-188)
         (*
          y3
          (-
           (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0))))
           (* y (- (* a y5) (* c y4)))))
         (if (<= j 1.2e-279)
           (* y5 (* k (- (* y i) (* y0 y2))))
           (if (<= j 5e-174)
             (*
              c
              (-
               (* y4 (- (* y y3) (* t y2)))
               (- (* i (- (* x y) (* z t))) (* y0 (- (* x y2) (* z y3))))))
             (if (<= j 1.15e-135)
               (*
                y5
                (+
                 (* a (- (* t y2) (* y y3)))
                 (- (* y0 (- (* j y3) (* k y2))) (* i (- (* t j) (* y k))))))
               (if (<= j 2.1e+207)
                 (*
                  x
                  (+
                   (- (* y2 (- (* c y0) (* a y1))) (* y (- (* c i) (* a b))))
                   (* j (- (* i y1) (* b y0)))))
                 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 = y0 * (j * ((y3 * y5) - (x * b)));
	double tmp;
	if (j <= -1.35e+262) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.95e+58) {
		tmp = t_1;
	} else if (j <= -8.5e-188) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 1.2e-279) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (j <= 5e-174) {
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((i * ((x * y) - (z * t))) - (y0 * ((x * y2) - (z * y3)))));
	} else if (j <= 1.15e-135) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (j <= 2.1e+207) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	} 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 = y0 * (j * ((y3 * y5) - (x * b)))
    if (j <= (-1.35d+262)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (j <= (-1.95d+58)) then
        tmp = t_1
    else if (j <= (-8.5d-188)) then
        tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))))
    else if (j <= 1.2d-279) then
        tmp = y5 * (k * ((y * i) - (y0 * y2)))
    else if (j <= 5d-174) then
        tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((i * ((x * y) - (z * t))) - (y0 * ((x * y2) - (z * y3)))))
    else if (j <= 1.15d-135) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
    else if (j <= 2.1d+207) then
        tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
    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 = y0 * (j * ((y3 * y5) - (x * b)));
	double tmp;
	if (j <= -1.35e+262) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -1.95e+58) {
		tmp = t_1;
	} else if (j <= -8.5e-188) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 1.2e-279) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (j <= 5e-174) {
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((i * ((x * y) - (z * t))) - (y0 * ((x * y2) - (z * y3)))));
	} else if (j <= 1.15e-135) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (j <= 2.1e+207) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	} 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 = y0 * (j * ((y3 * y5) - (x * b)))
	tmp = 0
	if j <= -1.35e+262:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif j <= -1.95e+58:
		tmp = t_1
	elif j <= -8.5e-188:
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))))
	elif j <= 1.2e-279:
		tmp = y5 * (k * ((y * i) - (y0 * y2)))
	elif j <= 5e-174:
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((i * ((x * y) - (z * t))) - (y0 * ((x * y2) - (z * y3)))))
	elif j <= 1.15e-135:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
	elif j <= 2.1e+207:
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
	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(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (j <= -1.35e+262)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (j <= -1.95e+58)
		tmp = t_1;
	elseif (j <= -8.5e-188)
		tmp = Float64(y3 * Float64(Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))) - Float64(y * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= 1.2e-279)
		tmp = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (j <= 5e-174)
		tmp = Float64(c * Float64(Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))) - Float64(Float64(i * Float64(Float64(x * y) - Float64(z * t))) - Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))))));
	elseif (j <= 1.15e-135)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * Float64(Float64(t * j) - Float64(y * k))))));
	elseif (j <= 2.1e+207)
		tmp = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * Float64(Float64(c * i) - Float64(a * b)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	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 = y0 * (j * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (j <= -1.35e+262)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (j <= -1.95e+58)
		tmp = t_1;
	elseif (j <= -8.5e-188)
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	elseif (j <= 1.2e-279)
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	elseif (j <= 5e-174)
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((i * ((x * y) - (z * t))) - (y0 * ((x * y2) - (z * y3)))));
	elseif (j <= 1.15e-135)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	elseif (j <= 2.1e+207)
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	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[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.35e+262], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.95e+58], t$95$1, If[LessEqual[j, -8.5e-188], N[(y3 * N[(N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.2e-279], N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5e-174], N[(c * N[(N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(i * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.15e-135], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.1e+207], N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.3500000000000001e262

   1. Initial program 15.4%

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

   3. Taylor expanded in y3 around -inf 54.2%

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

   4. Taylor expanded in y4 around inf 69.8%

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

   if -1.3500000000000001e262 < j < -1.95000000000000005e58 or 2.0999999999999999e207 < j

   1. Initial program 23.5%

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

   3. Taylor expanded in y0 around inf 42.0%

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

   4. Taylor expanded in j around inf 60.4%

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

      1. *-commutative 60.4%

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

   6. Simplified 60.4%

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

   if -1.95000000000000005e58 < j < -8.5000000000000004e-188

   1. Initial program 37.3%

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

   3. Taylor expanded in y3 around -inf 55.9%

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

   if -8.5000000000000004e-188 < j < 1.19999999999999995e-279

   1. Initial program 40.9%

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

   3. Taylor expanded in y5 around -inf 41.7%

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

   4. Taylor expanded in k around inf 49.5%

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

      1. +-commutative 49.5%

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

      2. mul-1-neg 49.5%

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

      3. unsub-neg 49.5%

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

      4. *-commutative 49.5%

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

   6. Simplified 49.5%

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

   if 1.19999999999999995e-279 < j < 5.0000000000000002e-174

   1. Initial program 28.8%

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

   3. Taylor expanded in c around inf 67.3%

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

   if 5.0000000000000002e-174 < j < 1.15e-135

   1. Initial program 29.1%

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

   3. Taylor expanded in y5 around -inf 64.3%

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

   if 1.15e-135 < j < 2.0999999999999999e207

   1. Initial program 37.8%

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

   3. Taylor expanded in x around inf 51.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 57.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.35 \cdot 10^{+262}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -1.95 \cdot 10^{+58}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{-188}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.2 \cdot 10^{-279}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-174}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(i \cdot \left(x \cdot y - z \cdot t\right) - y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-135}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{+207}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 10: 37.6% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ t_2 := a \cdot y1 - c \cdot y0\\ t_3 := c \cdot i - a \cdot b\\ \mathbf{if}\;j \leq -1.4 \cdot 10^{+260}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -4.2 \cdot 10^{+58}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq -1.35 \cdot 10^{-187}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot t\_2\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 7.8 \cdot 10^{-290}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 4.9 \cdot 10^{-176}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y3 \cdot t\_2 + t \cdot t\_3\right)\right)\\ \mathbf{elif}\;j \leq 4.25 \cdot 10^{-137}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.85 \cdot 10^{+204}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot t\_3\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y0 (* j (- (* y3 y5) (* x b)))))
        (t_2 (- (* a y1) (* c y0)))
        (t_3 (- (* c i) (* a b))))
   (if (<= j -1.4e+260)
     (* y3 (* y4 (- (* y c) (* j y1))))
     (if (<= j -4.2e+58)
       t_1
       (if (<= j -1.35e-187)
         (*
          y3
          (-
           (+ (* j (- (* y0 y5) (* y1 y4))) (* z t_2))
           (* y (- (* a y5) (* c y4)))))
         (if (<= j 7.8e-290)
           (* y5 (* k (- (* y i) (* y0 y2))))
           (if (<= j 4.9e-176)
             (* z (+ (* k (- (* b y0) (* i y1))) (+ (* y3 t_2) (* t t_3))))
             (if (<= j 4.25e-137)
               (*
                y5
                (+
                 (* a (- (* t y2) (* y y3)))
                 (- (* y0 (- (* j y3) (* k y2))) (* i (- (* t j) (* y k))))))
               (if (<= j 1.85e+204)
                 (*
                  x
                  (+
                   (- (* y2 (- (* c y0) (* a y1))) (* y t_3))
                   (* j (- (* i y1) (* b y0)))))
                 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 = y0 * (j * ((y3 * y5) - (x * b)));
	double t_2 = (a * y1) - (c * y0);
	double t_3 = (c * i) - (a * b);
	double tmp;
	if (j <= -1.4e+260) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -4.2e+58) {
		tmp = t_1;
	} else if (j <= -1.35e-187) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 7.8e-290) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (j <= 4.9e-176) {
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * t_2) + (t * t_3)));
	} else if (j <= 4.25e-137) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (j <= 1.85e+204) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_3)) + (j * ((i * y1) - (b * y0))));
	} 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) :: t_3
    real(8) :: tmp
    t_1 = y0 * (j * ((y3 * y5) - (x * b)))
    t_2 = (a * y1) - (c * y0)
    t_3 = (c * i) - (a * b)
    if (j <= (-1.4d+260)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (j <= (-4.2d+58)) then
        tmp = t_1
    else if (j <= (-1.35d-187)) then
        tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)) - (y * ((a * y5) - (c * y4))))
    else if (j <= 7.8d-290) then
        tmp = y5 * (k * ((y * i) - (y0 * y2)))
    else if (j <= 4.9d-176) then
        tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * t_2) + (t * t_3)))
    else if (j <= 4.25d-137) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
    else if (j <= 1.85d+204) then
        tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_3)) + (j * ((i * y1) - (b * y0))))
    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 = y0 * (j * ((y3 * y5) - (x * b)));
	double t_2 = (a * y1) - (c * y0);
	double t_3 = (c * i) - (a * b);
	double tmp;
	if (j <= -1.4e+260) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -4.2e+58) {
		tmp = t_1;
	} else if (j <= -1.35e-187) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 7.8e-290) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (j <= 4.9e-176) {
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * t_2) + (t * t_3)));
	} else if (j <= 4.25e-137) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (j <= 1.85e+204) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_3)) + (j * ((i * y1) - (b * y0))));
	} 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 = y0 * (j * ((y3 * y5) - (x * b)))
	t_2 = (a * y1) - (c * y0)
	t_3 = (c * i) - (a * b)
	tmp = 0
	if j <= -1.4e+260:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif j <= -4.2e+58:
		tmp = t_1
	elif j <= -1.35e-187:
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)) - (y * ((a * y5) - (c * y4))))
	elif j <= 7.8e-290:
		tmp = y5 * (k * ((y * i) - (y0 * y2)))
	elif j <= 4.9e-176:
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * t_2) + (t * t_3)))
	elif j <= 4.25e-137:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
	elif j <= 1.85e+204:
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_3)) + (j * ((i * y1) - (b * y0))))
	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(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))))
	t_2 = Float64(Float64(a * y1) - Float64(c * y0))
	t_3 = Float64(Float64(c * i) - Float64(a * b))
	tmp = 0.0
	if (j <= -1.4e+260)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (j <= -4.2e+58)
		tmp = t_1;
	elseif (j <= -1.35e-187)
		tmp = Float64(y3 * Float64(Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * t_2)) - Float64(y * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= 7.8e-290)
		tmp = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (j <= 4.9e-176)
		tmp = Float64(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) + Float64(Float64(y3 * t_2) + Float64(t * t_3))));
	elseif (j <= 4.25e-137)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * Float64(Float64(t * j) - Float64(y * k))))));
	elseif (j <= 1.85e+204)
		tmp = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * t_3)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	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 = y0 * (j * ((y3 * y5) - (x * b)));
	t_2 = (a * y1) - (c * y0);
	t_3 = (c * i) - (a * b);
	tmp = 0.0;
	if (j <= -1.4e+260)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (j <= -4.2e+58)
		tmp = t_1;
	elseif (j <= -1.35e-187)
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)) - (y * ((a * y5) - (c * y4))));
	elseif (j <= 7.8e-290)
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	elseif (j <= 4.9e-176)
		tmp = z * ((k * ((b * y0) - (i * y1))) + ((y3 * t_2) + (t * t_3)));
	elseif (j <= 4.25e-137)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	elseif (j <= 1.85e+204)
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * t_3)) + (j * ((i * y1) - (b * y0))));
	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[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.4e+260], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -4.2e+58], t$95$1, If[LessEqual[j, -1.35e-187], N[(y3 * N[(N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * t$95$2), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.8e-290], N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.9e-176], N[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y3 * t$95$2), $MachinePrecision] + N[(t * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.25e-137], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.85e+204], N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.3999999999999999e260

   1. Initial program 15.4%

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

   3. Taylor expanded in y3 around -inf 54.2%

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

   4. Taylor expanded in y4 around inf 69.8%

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

   if -1.3999999999999999e260 < j < -4.20000000000000024e58 or 1.85e204 < j

   1. Initial program 23.5%

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

   3. Taylor expanded in y0 around inf 42.0%

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

   4. Taylor expanded in j around inf 60.4%

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

      1. *-commutative 60.4%

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

   6. Simplified 60.4%

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

   if -4.20000000000000024e58 < j < -1.35e-187

   1. Initial program 37.3%

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

   3. Taylor expanded in y3 around -inf 55.9%

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

   if -1.35e-187 < j < 7.79999999999999946e-290

   1. Initial program 40.9%

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

   3. Taylor expanded in y5 around -inf 41.7%

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

   4. Taylor expanded in k around inf 49.5%

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

      1. +-commutative 49.5%

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

      2. mul-1-neg 49.5%

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

      3. unsub-neg 49.5%

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

      4. *-commutative 49.5%

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

   6. Simplified 49.5%

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

   if 7.79999999999999946e-290 < j < 4.8999999999999997e-176

   1. Initial program 33.6%

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

   3. Taylor expanded in z around -inf 55.9%

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

   if 4.8999999999999997e-176 < j < 4.2500000000000001e-137

   1. Initial program 24.0%

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

   3. Taylor expanded in y5 around -inf 64.9%

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

   if 4.2500000000000001e-137 < j < 1.85e204

   1. Initial program 37.8%

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

   3. Taylor expanded in x around inf 51.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 56.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.4 \cdot 10^{+260}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -4.2 \cdot 10^{+58}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;j \leq -1.35 \cdot 10^{-187}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 7.8 \cdot 10^{-290}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 4.9 \cdot 10^{-176}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right)\right)\\ \mathbf{elif}\;j \leq 4.25 \cdot 10^{-137}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.85 \cdot 10^{+204}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 37.1% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;j \leq -1.45 \cdot 10^{+262}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -9.8 \cdot 10^{+59}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-189}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 2.75 \cdot 10^{-269}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 9.5 \cdot 10^{-171}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(a \cdot \frac{y5}{c} - y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 6.2 \cdot 10^{-135}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 6.8 \cdot 10^{+204}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y0 (* j (- (* y3 y5) (* x b))))))
   (if (<= j -1.45e+262)
     (* y3 (* y4 (- (* y c) (* j y1))))
     (if (<= j -9.8e+59)
       t_1
       (if (<= j -1.45e-189)
         (*
          y3
          (-
           (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0))))
           (* y (- (* a y5) (* c y4)))))
         (if (<= j 2.75e-269)
           (* y5 (* k (- (* y i) (* y0 y2))))
           (if (<= j 9.5e-171)
             (* y2 (* t (* c (- (* a (/ y5 c)) y4))))
             (if (<= j 6.2e-135)
               (*
                y5
                (+
                 (* a (- (* t y2) (* y y3)))
                 (- (* y0 (- (* j y3) (* k y2))) (* i (- (* t j) (* y k))))))
               (if (<= j 6.8e+204)
                 (*
                  x
                  (+
                   (- (* y2 (- (* c y0) (* a y1))) (* y (- (* c i) (* a b))))
                   (* j (- (* i y1) (* b y0)))))
                 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 = y0 * (j * ((y3 * y5) - (x * b)));
	double tmp;
	if (j <= -1.45e+262) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -9.8e+59) {
		tmp = t_1;
	} else if (j <= -1.45e-189) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 2.75e-269) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (j <= 9.5e-171) {
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	} else if (j <= 6.2e-135) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (j <= 6.8e+204) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	} 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 = y0 * (j * ((y3 * y5) - (x * b)))
    if (j <= (-1.45d+262)) then
        tmp = y3 * (y4 * ((y * c) - (j * y1)))
    else if (j <= (-9.8d+59)) then
        tmp = t_1
    else if (j <= (-1.45d-189)) then
        tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))))
    else if (j <= 2.75d-269) then
        tmp = y5 * (k * ((y * i) - (y0 * y2)))
    else if (j <= 9.5d-171) then
        tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)))
    else if (j <= 6.2d-135) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
    else if (j <= 6.8d+204) then
        tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
    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 = y0 * (j * ((y3 * y5) - (x * b)));
	double tmp;
	if (j <= -1.45e+262) {
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	} else if (j <= -9.8e+59) {
		tmp = t_1;
	} else if (j <= -1.45e-189) {
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	} else if (j <= 2.75e-269) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (j <= 9.5e-171) {
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	} else if (j <= 6.2e-135) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (j <= 6.8e+204) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	} 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 = y0 * (j * ((y3 * y5) - (x * b)))
	tmp = 0
	if j <= -1.45e+262:
		tmp = y3 * (y4 * ((y * c) - (j * y1)))
	elif j <= -9.8e+59:
		tmp = t_1
	elif j <= -1.45e-189:
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))))
	elif j <= 2.75e-269:
		tmp = y5 * (k * ((y * i) - (y0 * y2)))
	elif j <= 9.5e-171:
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)))
	elif j <= 6.2e-135:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
	elif j <= 6.8e+204:
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))))
	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(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (j <= -1.45e+262)
		tmp = Float64(y3 * Float64(y4 * Float64(Float64(y * c) - Float64(j * y1))));
	elseif (j <= -9.8e+59)
		tmp = t_1;
	elseif (j <= -1.45e-189)
		tmp = Float64(y3 * Float64(Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))) - Float64(y * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= 2.75e-269)
		tmp = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (j <= 9.5e-171)
		tmp = Float64(y2 * Float64(t * Float64(c * Float64(Float64(a * Float64(y5 / c)) - y4))));
	elseif (j <= 6.2e-135)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * Float64(Float64(t * j) - Float64(y * k))))));
	elseif (j <= 6.8e+204)
		tmp = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(y * Float64(Float64(c * i) - Float64(a * b)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	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 = y0 * (j * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (j <= -1.45e+262)
		tmp = y3 * (y4 * ((y * c) - (j * y1)));
	elseif (j <= -9.8e+59)
		tmp = t_1;
	elseif (j <= -1.45e-189)
		tmp = y3 * (((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))) - (y * ((a * y5) - (c * y4))));
	elseif (j <= 2.75e-269)
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	elseif (j <= 9.5e-171)
		tmp = y2 * (t * (c * ((a * (y5 / c)) - y4)));
	elseif (j <= 6.2e-135)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	elseif (j <= 6.8e+204)
		tmp = x * (((y2 * ((c * y0) - (a * y1))) - (y * ((c * i) - (a * b)))) + (j * ((i * y1) - (b * y0))));
	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[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.45e+262], N[(y3 * N[(y4 * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -9.8e+59], t$95$1, If[LessEqual[j, -1.45e-189], N[(y3 * N[(N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.75e-269], N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 9.5e-171], N[(y2 * N[(t * N[(c * N[(N[(a * N[(y5 / c), $MachinePrecision]), $MachinePrecision] - y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.2e-135], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.8e+204], N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.4499999999999999e262

   1. Initial program 15.4%

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

   3. Taylor expanded in y3 around -inf 54.2%

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

   4. Taylor expanded in y4 around inf 69.8%

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

   if -1.4499999999999999e262 < j < -9.80000000000000015e59 or 6.8000000000000002e204 < j

   1. Initial program 23.5%

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

   3. Taylor expanded in y0 around inf 42.0%

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

   4. Taylor expanded in j around inf 60.4%

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

      1. *-commutative 60.4%

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

   6. Simplified 60.4%

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

   if -9.80000000000000015e59 < j < -1.45e-189

   1. Initial program 37.3%

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

   3. Taylor expanded in y3 around -inf 55.9%

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

   if -1.45e-189 < j < 2.75000000000000005e-269

   1. Initial program 41.5%

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

   3. Taylor expanded in y5 around -inf 42.3%

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

   4. Taylor expanded in k around inf 49.6%

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

      1. +-commutative 49.6%

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

      2. mul-1-neg 49.6%

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

      3. unsub-neg 49.6%

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

      4. *-commutative 49.6%

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

   6. Simplified 49.6%

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

   if 2.75000000000000005e-269 < j < 9.4999999999999994e-171

   1. Initial program 24.1%

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

   3. Taylor expanded in y2 around inf 28.9%

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

   4. Taylor expanded in t around inf 48.5%

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

      1. *-commutative 48.5%

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

   6. Simplified 48.5%

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

   7. Taylor expanded in c around inf 53.3%

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

      1. associate-/l* 53.3%

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

   9. Simplified 53.3%

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

   if 9.4999999999999994e-171 < j < 6.2000000000000001e-135

   1. Initial program 34.0%

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

   3. Taylor expanded in y5 around -inf 66.7%

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

   if 6.2000000000000001e-135 < j < 6.8000000000000002e204

   1. Initial program 37.8%

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

   3. Taylor expanded in x around inf 51.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 56.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.45 \cdot 10^{+262}:\\ \;\;\;\;y3 \cdot \left(y4 \cdot \left(y \cdot c - j \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -9.8 \cdot 10^{+59}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-189}:\\ \;\;\;\;y3 \cdot \left(\left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right) - y \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 2.75 \cdot 10^{-269}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 9.5 \cdot 10^{-171}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(a \cdot \frac{y5}{c} - y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 6.2 \cdot 10^{-135}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 6.8 \cdot 10^{+204}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - y \cdot \left(c \cdot i - a \cdot b\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 31.9% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;y1 \leq -2.5 \cdot 10^{+207}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;y1 \leq -1.3 \cdot 10^{+126}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y1 \leq -1.1 \cdot 10^{+116}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y1 \leq -3.5 \cdot 10^{-37}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y1 \leq -4.9 \cdot 10^{-68}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq -1 \cdot 10^{-101}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y1 \leq -4.3 \cdot 10^{-255}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq 1.55 \cdot 10^{-176}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 1.9 \cdot 10^{+51}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* b (- (* x y) (* z t))))))
   (if (<= y1 -2.5e+207)
     (* y1 (* i (- (* x j) (* z k))))
     (if (<= y1 -1.3e+126)
       (* k (* y2 (- (* y1 y4) (* y0 y5))))
       (if (<= y1 -1.1e+116)
         t_1
         (if (<= y1 -3.5e-37)
           (* y0 (* y3 (- (* j y5) (* z c))))
           (if (<= y1 -4.9e-68)
             (* b (* y0 (- (* z k) (* x j))))
             (if (<= y1 -1e-101)
               t_1
               (if (<= y1 -4.3e-255)
                 (* x (* y0 (- (* c y2) (* b j))))
                 (if (<= y1 1.55e-176)
                   (* b (* x (- (* y a) (* j y0))))
                   (if (<= y1 1.9e+51)
                     (* y0 (* j (- (* y3 y5) (* x b))))
                     (* k (* y1 (- (* y2 y4) (* z i)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y1 <= -2.5e+207) {
		tmp = y1 * (i * ((x * j) - (z * k)));
	} else if (y1 <= -1.3e+126) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (y1 <= -1.1e+116) {
		tmp = t_1;
	} else if (y1 <= -3.5e-37) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y1 <= -4.9e-68) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y1 <= -1e-101) {
		tmp = t_1;
	} else if (y1 <= -4.3e-255) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (y1 <= 1.55e-176) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y1 <= 1.9e+51) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (b * ((x * y) - (z * t)))
    if (y1 <= (-2.5d+207)) then
        tmp = y1 * (i * ((x * j) - (z * k)))
    else if (y1 <= (-1.3d+126)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (y1 <= (-1.1d+116)) then
        tmp = t_1
    else if (y1 <= (-3.5d-37)) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (y1 <= (-4.9d-68)) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (y1 <= (-1d-101)) then
        tmp = t_1
    else if (y1 <= (-4.3d-255)) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else if (y1 <= 1.55d-176) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y1 <= 1.9d+51) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y1 <= -2.5e+207) {
		tmp = y1 * (i * ((x * j) - (z * k)));
	} else if (y1 <= -1.3e+126) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (y1 <= -1.1e+116) {
		tmp = t_1;
	} else if (y1 <= -3.5e-37) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y1 <= -4.9e-68) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y1 <= -1e-101) {
		tmp = t_1;
	} else if (y1 <= -4.3e-255) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (y1 <= 1.55e-176) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y1 <= 1.9e+51) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (b * ((x * y) - (z * t)))
	tmp = 0
	if y1 <= -2.5e+207:
		tmp = y1 * (i * ((x * j) - (z * k)))
	elif y1 <= -1.3e+126:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif y1 <= -1.1e+116:
		tmp = t_1
	elif y1 <= -3.5e-37:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif y1 <= -4.9e-68:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif y1 <= -1e-101:
		tmp = t_1
	elif y1 <= -4.3e-255:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	elif y1 <= 1.55e-176:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y1 <= 1.9e+51:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	else:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (y1 <= -2.5e+207)
		tmp = Float64(y1 * Float64(i * Float64(Float64(x * j) - Float64(z * k))));
	elseif (y1 <= -1.3e+126)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (y1 <= -1.1e+116)
		tmp = t_1;
	elseif (y1 <= -3.5e-37)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (y1 <= -4.9e-68)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (y1 <= -1e-101)
		tmp = t_1;
	elseif (y1 <= -4.3e-255)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (y1 <= 1.55e-176)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y1 <= 1.9e+51)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	else
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (b * ((x * y) - (z * t)));
	tmp = 0.0;
	if (y1 <= -2.5e+207)
		tmp = y1 * (i * ((x * j) - (z * k)));
	elseif (y1 <= -1.3e+126)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (y1 <= -1.1e+116)
		tmp = t_1;
	elseif (y1 <= -3.5e-37)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (y1 <= -4.9e-68)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (y1 <= -1e-101)
		tmp = t_1;
	elseif (y1 <= -4.3e-255)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	elseif (y1 <= 1.55e-176)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y1 <= 1.9e+51)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	else
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y1, -2.5e+207], N[(y1 * N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -1.3e+126], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -1.1e+116], t$95$1, If[LessEqual[y1, -3.5e-37], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -4.9e-68], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -1e-101], t$95$1, If[LessEqual[y1, -4.3e-255], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.55e-176], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.9e+51], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y1 < -2.5e207

   1. Initial program 19.9%

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

   3. Taylor expanded in y1 around inf 60.0%

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

   4. Taylor expanded in i around inf 65.4%

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

   if -2.5e207 < y1 < -1.3e126

   1. Initial program 26.7%

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

   3. Taylor expanded in y2 around inf 40.0%

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

   4. Taylor expanded in k around inf 68.7%

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

   if -1.3e126 < y1 < -1.1e116 or -4.89999999999999977e-68 < y1 < -1.00000000000000005e-101

   1. Initial program 62.5%

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

   3. Taylor expanded in b around inf 38.7%

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

   4. Taylor expanded in a around inf 75.6%

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

   if -1.1e116 < y1 < -3.5000000000000001e-37

   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. Add Preprocessing

   3. Taylor expanded in y0 around inf 38.1%

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

   4. Taylor expanded in y3 around inf 46.7%

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

      1. +-commutative 46.7%

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

      2. mul-1-neg 46.7%

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

      3. unsub-neg 46.7%

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

   6. Simplified 46.7%

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

   if -3.5000000000000001e-37 < y1 < -4.89999999999999977e-68

   1. Initial program 20.0%

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

   3. Taylor expanded in b around inf 60.0%

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

   4. Taylor expanded in y0 around inf 71.7%

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

   if -1.00000000000000005e-101 < y1 < -4.29999999999999989e-255

   1. Initial program 28.5%

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

   3. Taylor expanded in x around inf 35.3%

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

      1. fma-define 35.3%

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

      2. fma-neg 35.3%

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

   5. Simplified 35.3%

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

   6. Taylor expanded in y0 around inf 43.9%

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

   if -4.29999999999999989e-255 < y1 < 1.54999999999999996e-176

   1. Initial program 31.3%

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

   3. Taylor expanded in x around inf 42.6%

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

      1. fma-define 45.3%

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

      2. fma-neg 45.3%

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

   5. Simplified 45.3%

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

   6. Taylor expanded in b around inf 48.5%

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

   if 1.54999999999999996e-176 < y1 < 1.8999999999999999e51

   1. Initial program 43.1%

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

   3. Taylor expanded in y0 around inf 43.7%

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

   4. Taylor expanded in j around inf 46.5%

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

      1. *-commutative 46.5%

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

   6. Simplified 46.5%

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

   if 1.8999999999999999e51 < y1

   1. Initial program 28.6%

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

   3. Taylor expanded in y1 around inf 59.4%

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

   4. Taylor expanded in k around inf 48.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 51.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -2.5 \cdot 10^{+207}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;y1 \leq -1.3 \cdot 10^{+126}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y1 \leq -1.1 \cdot 10^{+116}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y1 \leq -3.5 \cdot 10^{-37}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y1 \leq -4.9 \cdot 10^{-68}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq -1 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y1 \leq -4.3 \cdot 10^{-255}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq 1.55 \cdot 10^{-176}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 1.9 \cdot 10^{+51}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 30.4% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{if}\;x \leq -4.6 \cdot 10^{+126}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -3.8 \cdot 10^{+39}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -1.9 \cdot 10^{-135}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -5.6 \cdot 10^{-174}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -9.5 \cdot 10^{-247}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 1.35 \cdot 10^{-154} \lor \neg \left(x \leq 6.5 \cdot 10^{-76}\right) \land x \leq 7.5 \cdot 10^{+21}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0))))))
   (if (<= x -4.6e+126)
     (* y0 (* j (- (* y3 y5) (* x b))))
     (if (<= x -3.8e+39)
       t_1
       (if (<= x -1.9e-135)
         (* y0 (* y2 (- (* x c) (* k y5))))
         (if (<= x -5.6e-174)
           (* x (* y (- (* a b) (* c i))))
           (if (<= x -9.5e-247)
             (* a (* b (- (* x y) (* z t))))
             (if (or (<= x 1.35e-154)
                     (and (not (<= x 6.5e-76)) (<= x 7.5e+21)))
               (* k (* y2 (- (* y1 y4) (* y0 y5))))
               t_1))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (x <= -4.6e+126) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (x <= -3.8e+39) {
		tmp = t_1;
	} else if (x <= -1.9e-135) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (x <= -5.6e-174) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -9.5e-247) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 1.35e-154) || (!(x <= 6.5e-76) && (x <= 7.5e+21))) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (x * ((y * a) - (j * y0)))
    if (x <= (-4.6d+126)) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else if (x <= (-3.8d+39)) then
        tmp = t_1
    else if (x <= (-1.9d-135)) then
        tmp = y0 * (y2 * ((x * c) - (k * y5)))
    else if (x <= (-5.6d-174)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (x <= (-9.5d-247)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if ((x <= 1.35d-154) .or. (.not. (x <= 6.5d-76)) .and. (x <= 7.5d+21)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (x <= -4.6e+126) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (x <= -3.8e+39) {
		tmp = t_1;
	} else if (x <= -1.9e-135) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (x <= -5.6e-174) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -9.5e-247) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 1.35e-154) || (!(x <= 6.5e-76) && (x <= 7.5e+21))) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (x * ((y * a) - (j * y0)))
	tmp = 0
	if x <= -4.6e+126:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	elif x <= -3.8e+39:
		tmp = t_1
	elif x <= -1.9e-135:
		tmp = y0 * (y2 * ((x * c) - (k * y5)))
	elif x <= -5.6e-174:
		tmp = x * (y * ((a * b) - (c * i)))
	elif x <= -9.5e-247:
		tmp = a * (b * ((x * y) - (z * t)))
	elif (x <= 1.35e-154) or (not (x <= 6.5e-76) and (x <= 7.5e+21)):
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	tmp = 0.0
	if (x <= -4.6e+126)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (x <= -3.8e+39)
		tmp = t_1;
	elseif (x <= -1.9e-135)
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (x <= -5.6e-174)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (x <= -9.5e-247)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif ((x <= 1.35e-154) || (!(x <= 6.5e-76) && (x <= 7.5e+21)))
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (x * ((y * a) - (j * y0)));
	tmp = 0.0;
	if (x <= -4.6e+126)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	elseif (x <= -3.8e+39)
		tmp = t_1;
	elseif (x <= -1.9e-135)
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	elseif (x <= -5.6e-174)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (x <= -9.5e-247)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif ((x <= 1.35e-154) || (~((x <= 6.5e-76)) && (x <= 7.5e+21)))
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -4.6e+126], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3.8e+39], t$95$1, If[LessEqual[x, -1.9e-135], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -5.6e-174], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -9.5e-247], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, 1.35e-154], And[N[Not[LessEqual[x, 6.5e-76]], $MachinePrecision], LessEqual[x, 7.5e+21]]], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 6 regimes

2. if x < -4.6000000000000001e126

   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. Add Preprocessing

   3. Taylor expanded in y0 around inf 42.0%

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

   4. Taylor expanded in j around inf 59.5%

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

      1. *-commutative 59.5%

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

   6. Simplified 59.5%

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

   if -4.6000000000000001e126 < x < -3.7999999999999998e39 or 1.34999999999999995e-154 < x < 6.5e-76 or 7.5e21 < x

   1. Initial program 35.5%

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

   3. Taylor expanded in x around inf 53.9%

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

      1. fma-define 57.0%

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

      2. fma-neg 58.0%

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

   5. Simplified 58.0%

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

   6. Taylor expanded in b around inf 49.9%

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

   if -3.7999999999999998e39 < x < -1.9000000000000001e-135

   1. Initial program 19.6%

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

   3. Taylor expanded in y0 around inf 46.7%

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

   4. Taylor expanded in y2 around inf 38.2%

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

      1. +-commutative 38.2%

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

      2. mul-1-neg 38.2%

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

      3. unsub-neg 38.2%

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

   6. Simplified 38.2%

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

   if -1.9000000000000001e-135 < x < -5.59999999999999998e-174

   1. Initial program 36.4%

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

   3. Taylor expanded in x around inf 28.0%

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

      1. fma-define 28.0%

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

      2. fma-neg 28.0%

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

   5. Simplified 28.0%

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

   6. Taylor expanded in y around inf 64.2%

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

   if -5.59999999999999998e-174 < x < -9.49999999999999939e-247

   1. Initial program 18.8%

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

   3. Taylor expanded in b around inf 56.7%

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

   4. Taylor expanded in a around inf 56.7%

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

   if -9.49999999999999939e-247 < x < 1.34999999999999995e-154 or 6.5e-76 < x < 7.5e21

   1. Initial program 44.0%

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

   3. Taylor expanded in y2 around inf 39.9%

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

   4. Taylor expanded in k around inf 48.7%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 50.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -4.6 \cdot 10^{+126}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -3.8 \cdot 10^{+39}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.9 \cdot 10^{-135}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -5.6 \cdot 10^{-174}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -9.5 \cdot 10^{-247}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 1.35 \cdot 10^{-154} \lor \neg \left(x \leq 6.5 \cdot 10^{-76}\right) \land x \leq 7.5 \cdot 10^{+21}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 14: 31.0% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;x \leq -2.05 \cdot 10^{+126}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{+41}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{-134}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq -1.85 \cdot 10^{-179}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -2 \cdot 10^{-250}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 9 \cdot 10^{-150} \lor \neg \left(x \leq 3.3 \cdot 10^{-72}\right) \land x \leq 3 \cdot 10^{+18}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0)))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= x -2.05e+126)
     (* y0 (* j (- (* y3 y5) (* x b))))
     (if (<= x -1.8e+41)
       t_1
       (if (<= x -8.5e-134)
         t_2
         (if (<= x -1.85e-179)
           (* x (* y (- (* a b) (* c i))))
           (if (<= x -2e-250)
             (* a (* b (- (* x y) (* z t))))
             (if (or (<= x 9e-150) (and (not (<= x 3.3e-72)) (<= x 3e+18)))
               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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -2.05e+126) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (x <= -1.8e+41) {
		tmp = t_1;
	} else if (x <= -8.5e-134) {
		tmp = t_2;
	} else if (x <= -1.85e-179) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -2e-250) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 9e-150) || (!(x <= 3.3e-72) && (x <= 3e+18))) {
		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 = b * (x * ((y * a) - (j * y0)))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (x <= (-2.05d+126)) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else if (x <= (-1.8d+41)) then
        tmp = t_1
    else if (x <= (-8.5d-134)) then
        tmp = t_2
    else if (x <= (-1.85d-179)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (x <= (-2d-250)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if ((x <= 9d-150) .or. (.not. (x <= 3.3d-72)) .and. (x <= 3d+18)) 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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -2.05e+126) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (x <= -1.8e+41) {
		tmp = t_1;
	} else if (x <= -8.5e-134) {
		tmp = t_2;
	} else if (x <= -1.85e-179) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -2e-250) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 9e-150) || (!(x <= 3.3e-72) && (x <= 3e+18))) {
		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 = b * (x * ((y * a) - (j * y0)))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if x <= -2.05e+126:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	elif x <= -1.8e+41:
		tmp = t_1
	elif x <= -8.5e-134:
		tmp = t_2
	elif x <= -1.85e-179:
		tmp = x * (y * ((a * b) - (c * i)))
	elif x <= -2e-250:
		tmp = a * (b * ((x * y) - (z * t)))
	elif (x <= 9e-150) or (not (x <= 3.3e-72) and (x <= 3e+18)):
		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(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (x <= -2.05e+126)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (x <= -1.8e+41)
		tmp = t_1;
	elseif (x <= -8.5e-134)
		tmp = t_2;
	elseif (x <= -1.85e-179)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (x <= -2e-250)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif ((x <= 9e-150) || (!(x <= 3.3e-72) && (x <= 3e+18)))
		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 = b * (x * ((y * a) - (j * y0)));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (x <= -2.05e+126)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	elseif (x <= -1.8e+41)
		tmp = t_1;
	elseif (x <= -8.5e-134)
		tmp = t_2;
	elseif (x <= -1.85e-179)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (x <= -2e-250)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif ((x <= 9e-150) || (~((x <= 3.3e-72)) && (x <= 3e+18)))
		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[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * 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[x, -2.05e+126], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.8e+41], t$95$1, If[LessEqual[x, -8.5e-134], t$95$2, If[LessEqual[x, -1.85e-179], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2e-250], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, 9e-150], And[N[Not[LessEqual[x, 3.3e-72]], $MachinePrecision], LessEqual[x, 3e+18]]], t$95$2, t$95$1]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -2.05e126

   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. Add Preprocessing

   3. Taylor expanded in y0 around inf 42.0%

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

   4. Taylor expanded in j around inf 59.5%

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

      1. *-commutative 59.5%

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

   6. Simplified 59.5%

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

   if -2.05e126 < x < -1.80000000000000013e41 or 9.0000000000000005e-150 < x < 3.3e-72 or 3e18 < x

   1. Initial program 35.5%

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

   3. Taylor expanded in x around inf 53.9%

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

      1. fma-define 57.0%

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

      2. fma-neg 58.0%

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

   5. Simplified 58.0%

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

   6. Taylor expanded in b around inf 49.9%

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

   if -1.80000000000000013e41 < x < -8.50000000000000015e-134 or -2.0000000000000001e-250 < x < 9.0000000000000005e-150 or 3.3e-72 < x < 3e18

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 37.9%

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

   4. Taylor expanded in k around inf 44.9%

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

   if -8.50000000000000015e-134 < x < -1.84999999999999995e-179

   1. Initial program 36.4%

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

   3. Taylor expanded in x around inf 28.0%

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

      1. fma-define 28.0%

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

      2. fma-neg 28.0%

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

   5. Simplified 28.0%

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

   6. Taylor expanded in y around inf 64.2%

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

   if -1.84999999999999995e-179 < x < -2.0000000000000001e-250

   1. Initial program 18.8%

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

   3. Taylor expanded in b around inf 56.7%

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

   4. Taylor expanded in a around inf 56.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 50.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.05 \cdot 10^{+126}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{+41}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{-134}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -1.85 \cdot 10^{-179}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -2 \cdot 10^{-250}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 9 \cdot 10^{-150} \lor \neg \left(x \leq 3.3 \cdot 10^{-72}\right) \land x \leq 3 \cdot 10^{+18}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 31.0% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;x \leq -1.46 \cdot 10^{+127}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -2.1 \cdot 10^{+38}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -1 \cdot 10^{-136}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq -5.4 \cdot 10^{-177}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -3 \cdot 10^{-248}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 5.4 \cdot 10^{-157} \lor \neg \left(x \leq 2.5 \cdot 10^{-68}\right) \land x \leq 1.76 \cdot 10^{+19}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0)))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= x -1.46e+127)
     (* j (* y0 (- (* y3 y5) (* x b))))
     (if (<= x -2.1e+38)
       t_1
       (if (<= x -1e-136)
         t_2
         (if (<= x -5.4e-177)
           (* x (* y (- (* a b) (* c i))))
           (if (<= x -3e-248)
             (* a (* b (- (* x y) (* z t))))
             (if (or (<= x 5.4e-157)
                     (and (not (<= x 2.5e-68)) (<= x 1.76e+19)))
               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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -1.46e+127) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (x <= -2.1e+38) {
		tmp = t_1;
	} else if (x <= -1e-136) {
		tmp = t_2;
	} else if (x <= -5.4e-177) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -3e-248) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 5.4e-157) || (!(x <= 2.5e-68) && (x <= 1.76e+19))) {
		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 = b * (x * ((y * a) - (j * y0)))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (x <= (-1.46d+127)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (x <= (-2.1d+38)) then
        tmp = t_1
    else if (x <= (-1d-136)) then
        tmp = t_2
    else if (x <= (-5.4d-177)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (x <= (-3d-248)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if ((x <= 5.4d-157) .or. (.not. (x <= 2.5d-68)) .and. (x <= 1.76d+19)) 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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -1.46e+127) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (x <= -2.1e+38) {
		tmp = t_1;
	} else if (x <= -1e-136) {
		tmp = t_2;
	} else if (x <= -5.4e-177) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (x <= -3e-248) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 5.4e-157) || (!(x <= 2.5e-68) && (x <= 1.76e+19))) {
		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 = b * (x * ((y * a) - (j * y0)))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if x <= -1.46e+127:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif x <= -2.1e+38:
		tmp = t_1
	elif x <= -1e-136:
		tmp = t_2
	elif x <= -5.4e-177:
		tmp = x * (y * ((a * b) - (c * i)))
	elif x <= -3e-248:
		tmp = a * (b * ((x * y) - (z * t)))
	elif (x <= 5.4e-157) or (not (x <= 2.5e-68) and (x <= 1.76e+19)):
		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(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (x <= -1.46e+127)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (x <= -2.1e+38)
		tmp = t_1;
	elseif (x <= -1e-136)
		tmp = t_2;
	elseif (x <= -5.4e-177)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (x <= -3e-248)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif ((x <= 5.4e-157) || (!(x <= 2.5e-68) && (x <= 1.76e+19)))
		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 = b * (x * ((y * a) - (j * y0)));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (x <= -1.46e+127)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (x <= -2.1e+38)
		tmp = t_1;
	elseif (x <= -1e-136)
		tmp = t_2;
	elseif (x <= -5.4e-177)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (x <= -3e-248)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif ((x <= 5.4e-157) || (~((x <= 2.5e-68)) && (x <= 1.76e+19)))
		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[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * 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[x, -1.46e+127], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2.1e+38], t$95$1, If[LessEqual[x, -1e-136], t$95$2, If[LessEqual[x, -5.4e-177], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3e-248], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, 5.4e-157], And[N[Not[LessEqual[x, 2.5e-68]], $MachinePrecision], LessEqual[x, 1.76e+19]]], t$95$2, t$95$1]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -1.45999999999999997e127

   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. Add Preprocessing

   3. Taylor expanded in j around inf 41.8%

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

   4. Taylor expanded in y0 around inf 57.3%

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

   if -1.45999999999999997e127 < x < -2.1e38 or 5.4e-157 < x < 2.49999999999999986e-68 or 1.76e19 < x

   1. Initial program 35.5%

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

   3. Taylor expanded in x around inf 53.9%

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

      1. fma-define 57.0%

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

      2. fma-neg 58.0%

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

   5. Simplified 58.0%

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

   6. Taylor expanded in b around inf 49.9%

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

   if -2.1e38 < x < -1e-136 or -3.00000000000000014e-248 < x < 5.4e-157 or 2.49999999999999986e-68 < x < 1.76e19

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 37.9%

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

   4. Taylor expanded in k around inf 44.9%

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

   if -1e-136 < x < -5.4000000000000004e-177

   1. Initial program 36.4%

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

   3. Taylor expanded in x around inf 28.0%

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

      1. fma-define 28.0%

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

      2. fma-neg 28.0%

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

   5. Simplified 28.0%

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

   6. Taylor expanded in y around inf 64.2%

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

   if -5.4000000000000004e-177 < x < -3.00000000000000014e-248

   1. Initial program 18.8%

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

   3. Taylor expanded in b around inf 56.7%

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

   4. Taylor expanded in a around inf 56.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 50.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.46 \cdot 10^{+127}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -2.1 \cdot 10^{+38}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1 \cdot 10^{-136}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -5.4 \cdot 10^{-177}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;x \leq -3 \cdot 10^{-248}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 5.4 \cdot 10^{-157} \lor \neg \left(x \leq 2.5 \cdot 10^{-68}\right) \land x \leq 1.76 \cdot 10^{+19}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 30.0% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ t_2 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{if}\;y4 \leq -2.6 \cdot 10^{+258}:\\ \;\;\;\;\left(y1 \cdot y2\right) \cdot \left(k \cdot y4 - x \cdot a\right)\\ \mathbf{elif}\;y4 \leq -8.2 \cdot 10^{+220}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq -9.6 \cdot 10^{+141}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -7.8 \cdot 10^{-36}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y4 \leq -2.8 \cdot 10^{-291}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 10^{-155}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq 8 \cdot 10^{-118}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;y4 \leq 5.4 \cdot 10^{+188}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y1 (* z (- (* a y3) (* i k)))))
        (t_2 (* b (* x (- (* y a) (* j y0))))))
   (if (<= y4 -2.6e+258)
     (* (* y1 y2) (- (* k y4) (* x a)))
     (if (<= y4 -8.2e+220)
       t_1
       (if (<= y4 -9.6e+141)
         (* y1 (* y4 (- (* k y2) (* j y3))))
         (if (<= y4 -7.8e-36)
           t_2
           (if (<= y4 -2.8e-291)
             (* y0 (* j (- (* y3 y5) (* x b))))
             (if (<= y4 1e-155)
               t_1
               (if (<= y4 8e-118)
                 (* i (* x (- (* j y1) (* y c))))
                 (if (<= y4 5.4e+188)
                   t_2
                   (* y1 (* k (- (* y2 y4) (* z i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (y4 <= -2.6e+258) {
		tmp = (y1 * y2) * ((k * y4) - (x * a));
	} else if (y4 <= -8.2e+220) {
		tmp = t_1;
	} else if (y4 <= -9.6e+141) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -7.8e-36) {
		tmp = t_2;
	} else if (y4 <= -2.8e-291) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (y4 <= 1e-155) {
		tmp = t_1;
	} else if (y4 <= 8e-118) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (y4 <= 5.4e+188) {
		tmp = t_2;
	} else {
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y1 * (z * ((a * y3) - (i * k)))
    t_2 = b * (x * ((y * a) - (j * y0)))
    if (y4 <= (-2.6d+258)) then
        tmp = (y1 * y2) * ((k * y4) - (x * a))
    else if (y4 <= (-8.2d+220)) then
        tmp = t_1
    else if (y4 <= (-9.6d+141)) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y4 <= (-7.8d-36)) then
        tmp = t_2
    else if (y4 <= (-2.8d-291)) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else if (y4 <= 1d-155) then
        tmp = t_1
    else if (y4 <= 8d-118) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (y4 <= 5.4d+188) then
        tmp = t_2
    else
        tmp = y1 * (k * ((y2 * y4) - (z * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (y4 <= -2.6e+258) {
		tmp = (y1 * y2) * ((k * y4) - (x * a));
	} else if (y4 <= -8.2e+220) {
		tmp = t_1;
	} else if (y4 <= -9.6e+141) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -7.8e-36) {
		tmp = t_2;
	} else if (y4 <= -2.8e-291) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (y4 <= 1e-155) {
		tmp = t_1;
	} else if (y4 <= 8e-118) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (y4 <= 5.4e+188) {
		tmp = t_2;
	} else {
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y1 * (z * ((a * y3) - (i * k)))
	t_2 = b * (x * ((y * a) - (j * y0)))
	tmp = 0
	if y4 <= -2.6e+258:
		tmp = (y1 * y2) * ((k * y4) - (x * a))
	elif y4 <= -8.2e+220:
		tmp = t_1
	elif y4 <= -9.6e+141:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y4 <= -7.8e-36:
		tmp = t_2
	elif y4 <= -2.8e-291:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	elif y4 <= 1e-155:
		tmp = t_1
	elif y4 <= 8e-118:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif y4 <= 5.4e+188:
		tmp = t_2
	else:
		tmp = y1 * (k * ((y2 * y4) - (z * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))))
	t_2 = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	tmp = 0.0
	if (y4 <= -2.6e+258)
		tmp = Float64(Float64(y1 * y2) * Float64(Float64(k * y4) - Float64(x * a)));
	elseif (y4 <= -8.2e+220)
		tmp = t_1;
	elseif (y4 <= -9.6e+141)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y4 <= -7.8e-36)
		tmp = t_2;
	elseif (y4 <= -2.8e-291)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (y4 <= 1e-155)
		tmp = t_1;
	elseif (y4 <= 8e-118)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (y4 <= 5.4e+188)
		tmp = t_2;
	else
		tmp = Float64(y1 * Float64(k * Float64(Float64(y2 * y4) - Float64(z * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y1 * (z * ((a * y3) - (i * k)));
	t_2 = b * (x * ((y * a) - (j * y0)));
	tmp = 0.0;
	if (y4 <= -2.6e+258)
		tmp = (y1 * y2) * ((k * y4) - (x * a));
	elseif (y4 <= -8.2e+220)
		tmp = t_1;
	elseif (y4 <= -9.6e+141)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y4 <= -7.8e-36)
		tmp = t_2;
	elseif (y4 <= -2.8e-291)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	elseif (y4 <= 1e-155)
		tmp = t_1;
	elseif (y4 <= 8e-118)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (y4 <= 5.4e+188)
		tmp = t_2;
	else
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -2.6e+258], N[(N[(y1 * y2), $MachinePrecision] * N[(N[(k * y4), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -8.2e+220], t$95$1, If[LessEqual[y4, -9.6e+141], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -7.8e-36], t$95$2, If[LessEqual[y4, -2.8e-291], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1e-155], t$95$1, If[LessEqual[y4, 8e-118], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 5.4e+188], t$95$2, N[(y1 * N[(k * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y4 < -2.60000000000000011e258

   1. Initial program 33.3%

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

   3. Taylor expanded in y2 around inf 25.1%

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

   4. Taylor expanded in y1 around inf 67.0%

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

      1. associate-*r* 66.9%

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

      2. *-commutative 66.9%

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

      3. +-commutative 66.9%

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

      4. mul-1-neg 66.9%

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

      5. unsub-neg 66.9%

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

      6. *-commutative 66.9%

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

   6. Simplified 66.9%

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

   if -2.60000000000000011e258 < y4 < -8.19999999999999962e220 or -2.8e-291 < y4 < 1.00000000000000001e-155

   1. Initial program 27.6%

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

   3. Taylor expanded in y1 around inf 42.6%

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

   4. Taylor expanded in z around inf 53.4%

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

   if -8.19999999999999962e220 < y4 < -9.59999999999999989e141

   1. Initial program 12.8%

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

   3. Taylor expanded in y1 around inf 41.9%

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

   4. Taylor expanded in y4 around inf 59.9%

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

   if -9.59999999999999989e141 < y4 < -7.8000000000000001e-36 or 7.99999999999999988e-118 < y4 < 5.4e188

   1. Initial program 29.5%

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

   3. Taylor expanded in x around inf 35.1%

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

      1. fma-define 38.2%

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

      2. fma-neg 38.2%

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

   5. Simplified 38.2%

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

   6. Taylor expanded in b around inf 47.7%

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

   if -7.8000000000000001e-36 < y4 < -2.8e-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. Add Preprocessing

   3. Taylor expanded in y0 around inf 47.6%

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

   4. Taylor expanded in j around inf 46.3%

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

      1. *-commutative 46.3%

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

   6. Simplified 46.3%

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

   if 1.00000000000000001e-155 < y4 < 7.99999999999999988e-118

   1. Initial program 43.8%

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

   3. Taylor expanded in x around inf 50.8%

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

      1. fma-define 50.8%

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

      2. fma-neg 50.8%

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

   5. Simplified 50.8%

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

   6. Taylor expanded in i around -inf 56.8%

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

      1. associate-*r* 56.8%

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

      2. neg-mul-1 56.8%

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

   8. Simplified 56.8%

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

   if 5.4e188 < y4

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 27.1%

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

   4. Taylor expanded in k around inf 50.4%

      \[\leadsto y1 \cdot \color{blue}{\left(k \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 50.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -2.6 \cdot 10^{+258}:\\ \;\;\;\;\left(y1 \cdot y2\right) \cdot \left(k \cdot y4 - x \cdot a\right)\\ \mathbf{elif}\;y4 \leq -8.2 \cdot 10^{+220}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq -9.6 \cdot 10^{+141}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -7.8 \cdot 10^{-36}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq -2.8 \cdot 10^{-291}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 10^{-155}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq 8 \cdot 10^{-118}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;y4 \leq 5.4 \cdot 10^{+188}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 17: 29.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ t_2 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{if}\;y4 \leq -3.5 \cdot 10^{+259}:\\ \;\;\;\;\left(y1 \cdot y2\right) \cdot \left(k \cdot y4 - x \cdot a\right)\\ \mathbf{elif}\;y4 \leq -8.2 \cdot 10^{+220}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq -4.8 \cdot 10^{+141}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -5.9 \cdot 10^{-40}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y4 \leq -2.05 \cdot 10^{-291}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 3.6 \cdot 10^{-186}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq 7.2 \cdot 10^{-131}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 8.8 \cdot 10^{+189}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y1 (* z (- (* a y3) (* i k)))))
        (t_2 (* b (* x (- (* y a) (* j y0))))))
   (if (<= y4 -3.5e+259)
     (* (* y1 y2) (- (* k y4) (* x a)))
     (if (<= y4 -8.2e+220)
       t_1
       (if (<= y4 -4.8e+141)
         (* y1 (* y4 (- (* k y2) (* j y3))))
         (if (<= y4 -5.9e-40)
           t_2
           (if (<= y4 -2.05e-291)
             (* y0 (* j (- (* y3 y5) (* x b))))
             (if (<= y4 3.6e-186)
               t_1
               (if (<= y4 7.2e-131)
                 (* y2 (* t (- (* a y5) (* c y4))))
                 (if (<= y4 8.8e+189)
                   t_2
                   (* y1 (* k (- (* y2 y4) (* z i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (y4 <= -3.5e+259) {
		tmp = (y1 * y2) * ((k * y4) - (x * a));
	} else if (y4 <= -8.2e+220) {
		tmp = t_1;
	} else if (y4 <= -4.8e+141) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -5.9e-40) {
		tmp = t_2;
	} else if (y4 <= -2.05e-291) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (y4 <= 3.6e-186) {
		tmp = t_1;
	} else if (y4 <= 7.2e-131) {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	} else if (y4 <= 8.8e+189) {
		tmp = t_2;
	} else {
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y1 * (z * ((a * y3) - (i * k)))
    t_2 = b * (x * ((y * a) - (j * y0)))
    if (y4 <= (-3.5d+259)) then
        tmp = (y1 * y2) * ((k * y4) - (x * a))
    else if (y4 <= (-8.2d+220)) then
        tmp = t_1
    else if (y4 <= (-4.8d+141)) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y4 <= (-5.9d-40)) then
        tmp = t_2
    else if (y4 <= (-2.05d-291)) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else if (y4 <= 3.6d-186) then
        tmp = t_1
    else if (y4 <= 7.2d-131) then
        tmp = y2 * (t * ((a * y5) - (c * y4)))
    else if (y4 <= 8.8d+189) then
        tmp = t_2
    else
        tmp = y1 * (k * ((y2 * y4) - (z * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (y4 <= -3.5e+259) {
		tmp = (y1 * y2) * ((k * y4) - (x * a));
	} else if (y4 <= -8.2e+220) {
		tmp = t_1;
	} else if (y4 <= -4.8e+141) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -5.9e-40) {
		tmp = t_2;
	} else if (y4 <= -2.05e-291) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (y4 <= 3.6e-186) {
		tmp = t_1;
	} else if (y4 <= 7.2e-131) {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	} else if (y4 <= 8.8e+189) {
		tmp = t_2;
	} else {
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y1 * (z * ((a * y3) - (i * k)))
	t_2 = b * (x * ((y * a) - (j * y0)))
	tmp = 0
	if y4 <= -3.5e+259:
		tmp = (y1 * y2) * ((k * y4) - (x * a))
	elif y4 <= -8.2e+220:
		tmp = t_1
	elif y4 <= -4.8e+141:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y4 <= -5.9e-40:
		tmp = t_2
	elif y4 <= -2.05e-291:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	elif y4 <= 3.6e-186:
		tmp = t_1
	elif y4 <= 7.2e-131:
		tmp = y2 * (t * ((a * y5) - (c * y4)))
	elif y4 <= 8.8e+189:
		tmp = t_2
	else:
		tmp = y1 * (k * ((y2 * y4) - (z * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))))
	t_2 = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	tmp = 0.0
	if (y4 <= -3.5e+259)
		tmp = Float64(Float64(y1 * y2) * Float64(Float64(k * y4) - Float64(x * a)));
	elseif (y4 <= -8.2e+220)
		tmp = t_1;
	elseif (y4 <= -4.8e+141)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y4 <= -5.9e-40)
		tmp = t_2;
	elseif (y4 <= -2.05e-291)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (y4 <= 3.6e-186)
		tmp = t_1;
	elseif (y4 <= 7.2e-131)
		tmp = Float64(y2 * Float64(t * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y4 <= 8.8e+189)
		tmp = t_2;
	else
		tmp = Float64(y1 * Float64(k * Float64(Float64(y2 * y4) - Float64(z * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y1 * (z * ((a * y3) - (i * k)));
	t_2 = b * (x * ((y * a) - (j * y0)));
	tmp = 0.0;
	if (y4 <= -3.5e+259)
		tmp = (y1 * y2) * ((k * y4) - (x * a));
	elseif (y4 <= -8.2e+220)
		tmp = t_1;
	elseif (y4 <= -4.8e+141)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y4 <= -5.9e-40)
		tmp = t_2;
	elseif (y4 <= -2.05e-291)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	elseif (y4 <= 3.6e-186)
		tmp = t_1;
	elseif (y4 <= 7.2e-131)
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	elseif (y4 <= 8.8e+189)
		tmp = t_2;
	else
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -3.5e+259], N[(N[(y1 * y2), $MachinePrecision] * N[(N[(k * y4), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -8.2e+220], t$95$1, If[LessEqual[y4, -4.8e+141], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -5.9e-40], t$95$2, If[LessEqual[y4, -2.05e-291], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 3.6e-186], t$95$1, If[LessEqual[y4, 7.2e-131], N[(y2 * N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 8.8e+189], t$95$2, N[(y1 * N[(k * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y4 < -3.4999999999999998e259

   1. Initial program 33.3%

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

   3. Taylor expanded in y2 around inf 25.1%

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

   4. Taylor expanded in y1 around inf 67.0%

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

      1. associate-*r* 66.9%

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

      2. *-commutative 66.9%

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

      3. +-commutative 66.9%

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

      4. mul-1-neg 66.9%

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

      5. unsub-neg 66.9%

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

      6. *-commutative 66.9%

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

   6. Simplified 66.9%

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

   if -3.4999999999999998e259 < y4 < -8.19999999999999962e220 or -2.05e-291 < y4 < 3.5999999999999998e-186

   1. Initial program 29.5%

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

   3. Taylor expanded in y1 around inf 41.3%

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

   4. Taylor expanded in z around inf 53.9%

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

   if -8.19999999999999962e220 < y4 < -4.79999999999999995e141

   1. Initial program 12.8%

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

   3. Taylor expanded in y1 around inf 41.9%

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

   4. Taylor expanded in y4 around inf 59.9%

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

   if -4.79999999999999995e141 < y4 < -5.89999999999999966e-40 or 7.1999999999999999e-131 < y4 < 8.8000000000000002e189

   1. Initial program 30.7%

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

   3. Taylor expanded in x around inf 38.0%

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

      1. fma-define 41.0%

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

      2. fma-neg 41.0%

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

   5. Simplified 41.0%

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

   6. Taylor expanded in b around inf 48.0%

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

   if -5.89999999999999966e-40 < y4 < -2.05e-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. Add Preprocessing

   3. Taylor expanded in y0 around inf 47.6%

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

   4. Taylor expanded in j around inf 46.3%

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

      1. *-commutative 46.3%

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

   6. Simplified 46.3%

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

   if 3.5999999999999998e-186 < y4 < 7.1999999999999999e-131

   1. Initial program 31.3%

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

   3. Taylor expanded in y2 around inf 37.9%

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

   4. Taylor expanded in t around inf 51.3%

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

      1. *-commutative 51.3%

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

   6. Simplified 51.3%

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

   if 8.8000000000000002e189 < y4

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 27.1%

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

   4. Taylor expanded in k around inf 50.4%

      \[\leadsto y1 \cdot \color{blue}{\left(k \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 50.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -3.5 \cdot 10^{+259}:\\ \;\;\;\;\left(y1 \cdot y2\right) \cdot \left(k \cdot y4 - x \cdot a\right)\\ \mathbf{elif}\;y4 \leq -8.2 \cdot 10^{+220}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq -4.8 \cdot 10^{+141}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -5.9 \cdot 10^{-40}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq -2.05 \cdot 10^{-291}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 3.6 \cdot 10^{-186}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq 7.2 \cdot 10^{-131}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 8.8 \cdot 10^{+189}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 18: 30.8% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{if}\;y4 \leq -3.1 \cdot 10^{+140}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -2.25 \cdot 10^{-38}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq -2.2 \cdot 10^{-291}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 5.4 \cdot 10^{-187}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq 1.25 \cdot 10^{-130}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 800000000000:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq 1.3 \cdot 10^{+63}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;y4 \leq 5.7 \cdot 10^{+187}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0))))))
   (if (<= y4 -3.1e+140)
     (* y1 (* y4 (- (* k y2) (* j y3))))
     (if (<= y4 -2.25e-38)
       t_1
       (if (<= y4 -2.2e-291)
         (* y0 (* j (- (* y3 y5) (* x b))))
         (if (<= y4 5.4e-187)
           (* y1 (* z (- (* a y3) (* i k))))
           (if (<= y4 1.25e-130)
             (* y2 (* t (- (* a y5) (* c y4))))
             (if (<= y4 800000000000.0)
               t_1
               (if (<= y4 1.3e+63)
                 (* y0 (* y2 (- (* x c) (* k y5))))
                 (if (<= y4 5.7e+187)
                   t_1
                   (* y1 (* k (- (* y2 y4) (* z i))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (y4 <= -3.1e+140) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -2.25e-38) {
		tmp = t_1;
	} else if (y4 <= -2.2e-291) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (y4 <= 5.4e-187) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (y4 <= 1.25e-130) {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	} else if (y4 <= 800000000000.0) {
		tmp = t_1;
	} else if (y4 <= 1.3e+63) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (y4 <= 5.7e+187) {
		tmp = t_1;
	} else {
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (x * ((y * a) - (j * y0)))
    if (y4 <= (-3.1d+140)) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y4 <= (-2.25d-38)) then
        tmp = t_1
    else if (y4 <= (-2.2d-291)) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else if (y4 <= 5.4d-187) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (y4 <= 1.25d-130) then
        tmp = y2 * (t * ((a * y5) - (c * y4)))
    else if (y4 <= 800000000000.0d0) then
        tmp = t_1
    else if (y4 <= 1.3d+63) then
        tmp = y0 * (y2 * ((x * c) - (k * y5)))
    else if (y4 <= 5.7d+187) then
        tmp = t_1
    else
        tmp = y1 * (k * ((y2 * y4) - (z * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (y4 <= -3.1e+140) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -2.25e-38) {
		tmp = t_1;
	} else if (y4 <= -2.2e-291) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else if (y4 <= 5.4e-187) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (y4 <= 1.25e-130) {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	} else if (y4 <= 800000000000.0) {
		tmp = t_1;
	} else if (y4 <= 1.3e+63) {
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	} else if (y4 <= 5.7e+187) {
		tmp = t_1;
	} else {
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (x * ((y * a) - (j * y0)))
	tmp = 0
	if y4 <= -3.1e+140:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y4 <= -2.25e-38:
		tmp = t_1
	elif y4 <= -2.2e-291:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	elif y4 <= 5.4e-187:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif y4 <= 1.25e-130:
		tmp = y2 * (t * ((a * y5) - (c * y4)))
	elif y4 <= 800000000000.0:
		tmp = t_1
	elif y4 <= 1.3e+63:
		tmp = y0 * (y2 * ((x * c) - (k * y5)))
	elif y4 <= 5.7e+187:
		tmp = t_1
	else:
		tmp = y1 * (k * ((y2 * y4) - (z * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	tmp = 0.0
	if (y4 <= -3.1e+140)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y4 <= -2.25e-38)
		tmp = t_1;
	elseif (y4 <= -2.2e-291)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (y4 <= 5.4e-187)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (y4 <= 1.25e-130)
		tmp = Float64(y2 * Float64(t * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y4 <= 800000000000.0)
		tmp = t_1;
	elseif (y4 <= 1.3e+63)
		tmp = Float64(y0 * Float64(y2 * Float64(Float64(x * c) - Float64(k * y5))));
	elseif (y4 <= 5.7e+187)
		tmp = t_1;
	else
		tmp = Float64(y1 * Float64(k * Float64(Float64(y2 * y4) - Float64(z * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (x * ((y * a) - (j * y0)));
	tmp = 0.0;
	if (y4 <= -3.1e+140)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y4 <= -2.25e-38)
		tmp = t_1;
	elseif (y4 <= -2.2e-291)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	elseif (y4 <= 5.4e-187)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (y4 <= 1.25e-130)
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	elseif (y4 <= 800000000000.0)
		tmp = t_1;
	elseif (y4 <= 1.3e+63)
		tmp = y0 * (y2 * ((x * c) - (k * y5)));
	elseif (y4 <= 5.7e+187)
		tmp = t_1;
	else
		tmp = y1 * (k * ((y2 * y4) - (z * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -3.1e+140], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -2.25e-38], t$95$1, If[LessEqual[y4, -2.2e-291], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 5.4e-187], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.25e-130], N[(y2 * N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 800000000000.0], t$95$1, If[LessEqual[y4, 1.3e+63], N[(y0 * N[(y2 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 5.7e+187], t$95$1, N[(y1 * N[(k * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y4 < -3.1e140

   1. Initial program 22.9%

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

   3. Taylor expanded in y1 around inf 35.4%

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

   4. Taylor expanded in y4 around inf 53.1%

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

   if -3.1e140 < y4 < -2.25000000000000004e-38 or 1.2499999999999999e-130 < y4 < 8e11 or 1.3000000000000001e63 < y4 < 5.7000000000000004e187

   1. Initial program 31.9%

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

   3. Taylor expanded in x around inf 39.8%

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

      1. fma-define 43.0%

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

      2. fma-neg 43.0%

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

   5. Simplified 43.0%

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

   6. Taylor expanded in b around inf 50.8%

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

   if -2.25000000000000004e-38 < y4 < -2.20000000000000002e-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. Add Preprocessing

   3. Taylor expanded in y0 around inf 47.6%

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

   4. Taylor expanded in j around inf 46.3%

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

      1. *-commutative 46.3%

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

   6. Simplified 46.3%

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

   if -2.20000000000000002e-291 < y4 < 5.4000000000000002e-187

   1. Initial program 30.6%

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

   3. Taylor expanded in y1 around inf 43.7%

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

   4. Taylor expanded in z around inf 48.8%

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

   if 5.4000000000000002e-187 < y4 < 1.2499999999999999e-130

   1. Initial program 31.3%

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

   3. Taylor expanded in y2 around inf 37.9%

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

   4. Taylor expanded in t around inf 51.3%

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

      1. *-commutative 51.3%

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

   6. Simplified 51.3%

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

   if 8e11 < y4 < 1.3000000000000001e63

   1. Initial program 20.0%

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

   3. Taylor expanded in y0 around inf 41.5%

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

   4. Taylor expanded in y2 around inf 62.2%

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

      1. +-commutative 62.2%

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

      2. mul-1-neg 62.2%

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

      3. unsub-neg 62.2%

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

   6. Simplified 62.2%

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

   if 5.7000000000000004e187 < y4

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 27.1%

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

   4. Taylor expanded in k around inf 50.4%

      \[\leadsto y1 \cdot \color{blue}{\left(k \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 50.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -3.1 \cdot 10^{+140}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -2.25 \cdot 10^{-38}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq -2.2 \cdot 10^{-291}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 5.4 \cdot 10^{-187}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq 1.25 \cdot 10^{-130}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 800000000000:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.3 \cdot 10^{+63}:\\ \;\;\;\;y0 \cdot \left(y2 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{elif}\;y4 \leq 5.7 \cdot 10^{+187}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(k \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 19: 30.9% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;x \leq -2.9 \cdot 10^{+126}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -2.05 \cdot 10^{+37}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -9 \cdot 10^{-106}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;x \leq -7.5 \cdot 10^{-249}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 7.8 \cdot 10^{-150} \lor \neg \left(x \leq 6.2 \cdot 10^{-75}\right) \land x \leq 1.75 \cdot 10^{+21}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0)))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= x -2.9e+126)
     (* j (* y0 (- (* y3 y5) (* x b))))
     (if (<= x -2.05e+37)
       t_1
       (if (<= x -9e-106)
         t_2
         (if (<= x -7.5e-249)
           (* a (* b (- (* x y) (* z t))))
           (if (or (<= x 7.8e-150) (and (not (<= x 6.2e-75)) (<= x 1.75e+21)))
             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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -2.9e+126) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (x <= -2.05e+37) {
		tmp = t_1;
	} else if (x <= -9e-106) {
		tmp = t_2;
	} else if (x <= -7.5e-249) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 7.8e-150) || (!(x <= 6.2e-75) && (x <= 1.75e+21))) {
		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 = b * (x * ((y * a) - (j * y0)))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (x <= (-2.9d+126)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (x <= (-2.05d+37)) then
        tmp = t_1
    else if (x <= (-9d-106)) then
        tmp = t_2
    else if (x <= (-7.5d-249)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if ((x <= 7.8d-150) .or. (.not. (x <= 6.2d-75)) .and. (x <= 1.75d+21)) 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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (x <= -2.9e+126) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (x <= -2.05e+37) {
		tmp = t_1;
	} else if (x <= -9e-106) {
		tmp = t_2;
	} else if (x <= -7.5e-249) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((x <= 7.8e-150) || (!(x <= 6.2e-75) && (x <= 1.75e+21))) {
		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 = b * (x * ((y * a) - (j * y0)))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if x <= -2.9e+126:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif x <= -2.05e+37:
		tmp = t_1
	elif x <= -9e-106:
		tmp = t_2
	elif x <= -7.5e-249:
		tmp = a * (b * ((x * y) - (z * t)))
	elif (x <= 7.8e-150) or (not (x <= 6.2e-75) and (x <= 1.75e+21)):
		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(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (x <= -2.9e+126)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (x <= -2.05e+37)
		tmp = t_1;
	elseif (x <= -9e-106)
		tmp = t_2;
	elseif (x <= -7.5e-249)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif ((x <= 7.8e-150) || (!(x <= 6.2e-75) && (x <= 1.75e+21)))
		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 = b * (x * ((y * a) - (j * y0)));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (x <= -2.9e+126)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (x <= -2.05e+37)
		tmp = t_1;
	elseif (x <= -9e-106)
		tmp = t_2;
	elseif (x <= -7.5e-249)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif ((x <= 7.8e-150) || (~((x <= 6.2e-75)) && (x <= 1.75e+21)))
		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[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * 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[x, -2.9e+126], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2.05e+37], t$95$1, If[LessEqual[x, -9e-106], t$95$2, If[LessEqual[x, -7.5e-249], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, 7.8e-150], And[N[Not[LessEqual[x, 6.2e-75]], $MachinePrecision], LessEqual[x, 1.75e+21]]], t$95$2, t$95$1]]]]]]]

Derivation

1. Split input into 4 regimes

2. if x < -2.89999999999999986e126

   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. Add Preprocessing

   3. Taylor expanded in j around inf 41.8%

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

   4. Taylor expanded in y0 around inf 57.3%

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

   if -2.89999999999999986e126 < x < -2.0499999999999999e37 or 7.8000000000000004e-150 < x < 6.20000000000000013e-75 or 1.75e21 < x

   1. Initial program 35.5%

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

   3. Taylor expanded in x around inf 53.9%

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

      1. fma-define 57.0%

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

      2. fma-neg 58.0%

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

   5. Simplified 58.0%

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

   6. Taylor expanded in b around inf 49.9%

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

   if -2.0499999999999999e37 < x < -8.99999999999999911e-106 or -7.50000000000000034e-249 < x < 7.8000000000000004e-150 or 6.20000000000000013e-75 < x < 1.75e21

   1. Initial program 35.0%

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

   3. Taylor expanded in y2 around inf 39.1%

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

   4. Taylor expanded in k around inf 47.8%

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

   if -8.99999999999999911e-106 < x < -7.50000000000000034e-249

   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. Add Preprocessing

   3. Taylor expanded in b around inf 40.0%

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

   4. Taylor expanded in a around inf 37.1%

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

4. Final simplification 48.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.9 \cdot 10^{+126}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -2.05 \cdot 10^{+37}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -9 \cdot 10^{-106}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -7.5 \cdot 10^{-249}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 7.8 \cdot 10^{-150} \lor \neg \left(x \leq 6.2 \cdot 10^{-75}\right) \land x \leq 1.75 \cdot 10^{+21}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 20: 32.5% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{if}\;y1 \leq -8 \cdot 10^{+129}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y1 \leq -7 \cdot 10^{-37}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y1 \leq -9.6 \cdot 10^{-68}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq -4.6 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y1 \leq -2.7 \cdot 10^{-258}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq 1.7 \cdot 10^{-176}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 1.3 \cdot 10^{+48}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y1 (- (* y2 y4) (* z i))))))
   (if (<= y1 -8e+129)
     t_1
     (if (<= y1 -7e-37)
       (* y0 (* y3 (- (* j y5) (* z c))))
       (if (<= y1 -9.6e-68)
         (* b (* y0 (- (* z k) (* x j))))
         (if (<= y1 -4.6e-101)
           (* a (* b (- (* x y) (* z t))))
           (if (<= y1 -2.7e-258)
             (* x (* y0 (- (* c y2) (* b j))))
             (if (<= y1 1.7e-176)
               (* b (* x (- (* y a) (* j y0))))
               (if (<= y1 1.3e+48)
                 (* y0 (* j (- (* y3 y5) (* x 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 = k * (y1 * ((y2 * y4) - (z * i)));
	double tmp;
	if (y1 <= -8e+129) {
		tmp = t_1;
	} else if (y1 <= -7e-37) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y1 <= -9.6e-68) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y1 <= -4.6e-101) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y1 <= -2.7e-258) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (y1 <= 1.7e-176) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y1 <= 1.3e+48) {
		tmp = y0 * (j * ((y3 * y5) - (x * 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 = k * (y1 * ((y2 * y4) - (z * i)))
    if (y1 <= (-8d+129)) then
        tmp = t_1
    else if (y1 <= (-7d-37)) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (y1 <= (-9.6d-68)) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (y1 <= (-4.6d-101)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y1 <= (-2.7d-258)) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else if (y1 <= 1.7d-176) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y1 <= 1.3d+48) then
        tmp = y0 * (j * ((y3 * y5) - (x * 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 = k * (y1 * ((y2 * y4) - (z * i)));
	double tmp;
	if (y1 <= -8e+129) {
		tmp = t_1;
	} else if (y1 <= -7e-37) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y1 <= -9.6e-68) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y1 <= -4.6e-101) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y1 <= -2.7e-258) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (y1 <= 1.7e-176) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y1 <= 1.3e+48) {
		tmp = y0 * (j * ((y3 * y5) - (x * 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 = k * (y1 * ((y2 * y4) - (z * i)))
	tmp = 0
	if y1 <= -8e+129:
		tmp = t_1
	elif y1 <= -7e-37:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif y1 <= -9.6e-68:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif y1 <= -4.6e-101:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y1 <= -2.7e-258:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	elif y1 <= 1.7e-176:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y1 <= 1.3e+48:
		tmp = y0 * (j * ((y3 * y5) - (x * 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(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))))
	tmp = 0.0
	if (y1 <= -8e+129)
		tmp = t_1;
	elseif (y1 <= -7e-37)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (y1 <= -9.6e-68)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (y1 <= -4.6e-101)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y1 <= -2.7e-258)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (y1 <= 1.7e-176)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y1 <= 1.3e+48)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * 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 = k * (y1 * ((y2 * y4) - (z * i)));
	tmp = 0.0;
	if (y1 <= -8e+129)
		tmp = t_1;
	elseif (y1 <= -7e-37)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (y1 <= -9.6e-68)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (y1 <= -4.6e-101)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y1 <= -2.7e-258)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	elseif (y1 <= 1.7e-176)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y1 <= 1.3e+48)
		tmp = y0 * (j * ((y3 * y5) - (x * 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[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y1, -8e+129], t$95$1, If[LessEqual[y1, -7e-37], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -9.6e-68], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -4.6e-101], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -2.7e-258], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.7e-176], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.3e+48], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y1 < -8e129 or 1.29999999999999998e48 < y1

   1. Initial program 26.4%

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

   3. Taylor expanded in y1 around inf 57.9%

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

   4. Taylor expanded in k around inf 51.8%

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

   if -8e129 < y1 < -7.0000000000000003e-37

   1. Initial program 32.2%

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

   3. Taylor expanded in y0 around inf 37.7%

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

   4. Taylor expanded in y3 around inf 48.4%

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

      1. +-commutative 48.4%

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

      2. mul-1-neg 48.4%

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

      3. unsub-neg 48.4%

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

   6. Simplified 48.4%

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

   if -7.0000000000000003e-37 < y1 < -9.59999999999999965e-68

   1. Initial program 20.0%

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

   3. Taylor expanded in b around inf 60.0%

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

   4. Taylor expanded in y0 around inf 71.7%

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

   if -9.59999999999999965e-68 < y1 < -4.5999999999999999e-101

   1. Initial program 66.7%

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

   3. Taylor expanded in b around inf 35.0%

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

   4. Taylor expanded in a around inf 67.4%

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

   if -4.5999999999999999e-101 < y1 < -2.69999999999999996e-258

   1. Initial program 28.5%

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

   3. Taylor expanded in x around inf 35.3%

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

      1. fma-define 35.3%

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

      2. fma-neg 35.3%

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

   5. Simplified 35.3%

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

   6. Taylor expanded in y0 around inf 43.9%

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

   if -2.69999999999999996e-258 < y1 < 1.6999999999999999e-176

   1. Initial program 31.3%

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

   3. Taylor expanded in x around inf 42.6%

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

      1. fma-define 45.3%

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

      2. fma-neg 45.3%

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

   5. Simplified 45.3%

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

   6. Taylor expanded in b around inf 48.5%

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

   if 1.6999999999999999e-176 < y1 < 1.29999999999999998e48

   1. Initial program 43.1%

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

   3. Taylor expanded in y0 around inf 43.7%

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

   4. Taylor expanded in j around inf 46.5%

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

      1. *-commutative 46.5%

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

   6. Simplified 46.5%

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

4. Final simplification 49.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -8 \cdot 10^{+129}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y1 \leq -7 \cdot 10^{-37}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y1 \leq -9.6 \cdot 10^{-68}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq -4.6 \cdot 10^{-101}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y1 \leq -2.7 \cdot 10^{-258}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y1 \leq 1.7 \cdot 10^{-176}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 1.3 \cdot 10^{+48}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 21: 35.2% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot \left(z \cdot k - x \cdot j\right)\\ \mathbf{if}\;y5 \leq -1.45 \cdot 10^{+32}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - y \cdot a\right)\right)\\ \mathbf{elif}\;y5 \leq 9.5 \cdot 10^{-167}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + t\_1\right)\\ \mathbf{elif}\;y5 \leq 0.39:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 1.9 \cdot 10^{+20}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y5 \leq 1.65 \cdot 10^{+50}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 7.2 \cdot 10^{+80}:\\ \;\;\;\;b \cdot t\_1\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y0 (- (* z k) (* x j)))))
   (if (<= y5 -1.45e+32)
     (* y3 (* y5 (- (* j y0) (* y a))))
     (if (<= y5 9.5e-167)
       (* b (+ (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k)))) t_1))
       (if (<= y5 0.39)
         (* c (* x (- (* y0 y2) (* y i))))
         (if (<= y5 1.9e+20)
           (* y0 (* y3 (- (* j y5) (* z c))))
           (if (<= y5 1.65e+50)
             (* y (* y3 (- (* c y4) (* a y5))))
             (if (<= y5 7.2e+80)
               (* b t_1)
               (* j (* y0 (- (* y3 y5) (* 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 t_1 = y0 * ((z * k) - (x * j));
	double tmp;
	if (y5 <= -1.45e+32) {
		tmp = y3 * (y5 * ((j * y0) - (y * a)));
	} else if (y5 <= 9.5e-167) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_1);
	} else if (y5 <= 0.39) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (y5 <= 1.9e+20) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y5 <= 1.65e+50) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (y5 <= 7.2e+80) {
		tmp = b * t_1;
	} else {
		tmp = j * (y0 * ((y3 * y5) - (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) :: t_1
    real(8) :: tmp
    t_1 = y0 * ((z * k) - (x * j))
    if (y5 <= (-1.45d+32)) then
        tmp = y3 * (y5 * ((j * y0) - (y * a)))
    else if (y5 <= 9.5d-167) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_1)
    else if (y5 <= 0.39d0) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else if (y5 <= 1.9d+20) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (y5 <= 1.65d+50) then
        tmp = y * (y3 * ((c * y4) - (a * y5)))
    else if (y5 <= 7.2d+80) then
        tmp = b * t_1
    else
        tmp = j * (y0 * ((y3 * y5) - (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 t_1 = y0 * ((z * k) - (x * j));
	double tmp;
	if (y5 <= -1.45e+32) {
		tmp = y3 * (y5 * ((j * y0) - (y * a)));
	} else if (y5 <= 9.5e-167) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_1);
	} else if (y5 <= 0.39) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (y5 <= 1.9e+20) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (y5 <= 1.65e+50) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else if (y5 <= 7.2e+80) {
		tmp = b * t_1;
	} else {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y0 * ((z * k) - (x * j))
	tmp = 0
	if y5 <= -1.45e+32:
		tmp = y3 * (y5 * ((j * y0) - (y * a)))
	elif y5 <= 9.5e-167:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_1)
	elif y5 <= 0.39:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	elif y5 <= 1.9e+20:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif y5 <= 1.65e+50:
		tmp = y * (y3 * ((c * y4) - (a * y5)))
	elif y5 <= 7.2e+80:
		tmp = b * t_1
	else:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))
	tmp = 0.0
	if (y5 <= -1.45e+32)
		tmp = Float64(y3 * Float64(y5 * Float64(Float64(j * y0) - Float64(y * a))));
	elseif (y5 <= 9.5e-167)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + t_1));
	elseif (y5 <= 0.39)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	elseif (y5 <= 1.9e+20)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (y5 <= 1.65e+50)
		tmp = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))));
	elseif (y5 <= 7.2e+80)
		tmp = Float64(b * t_1);
	else
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - 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)
	t_1 = y0 * ((z * k) - (x * j));
	tmp = 0.0;
	if (y5 <= -1.45e+32)
		tmp = y3 * (y5 * ((j * y0) - (y * a)));
	elseif (y5 <= 9.5e-167)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_1);
	elseif (y5 <= 0.39)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	elseif (y5 <= 1.9e+20)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (y5 <= 1.65e+50)
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	elseif (y5 <= 7.2e+80)
		tmp = b * t_1;
	else
		tmp = j * (y0 * ((y3 * y5) - (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_] := Block[{t$95$1 = N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -1.45e+32], N[(y3 * N[(y5 * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 9.5e-167], 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] + t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 0.39], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.9e+20], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.65e+50], N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 7.2e+80], N[(b * t$95$1), $MachinePrecision], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y5 < -1.45000000000000001e32

   1. Initial program 36.6%

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

   3. Taylor expanded in y3 around -inf 53.2%

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

   4. Taylor expanded in y5 around -inf 53.3%

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

      1. associate-*r* 53.3%

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

      2. mul-1-neg 53.3%

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

   6. Simplified 53.3%

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

   if -1.45000000000000001e32 < y5 < 9.49999999999999955e-167

   1. Initial program 34.0%

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

   3. Taylor expanded in b around inf 47.7%

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

   if 9.49999999999999955e-167 < y5 < 0.39000000000000001

   1. Initial program 41.5%

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

   3. Taylor expanded in x around inf 39.9%

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

      1. fma-define 42.6%

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

      2. fma-neg 45.4%

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

   5. Simplified 45.4%

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

   6. Taylor expanded in c around inf 43.0%

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

   if 0.39000000000000001 < y5 < 1.9e20

   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. Add Preprocessing

   3. Taylor expanded in y0 around inf 71.8%

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

   4. Taylor expanded in y3 around inf 72.1%

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

      1. +-commutative 72.1%

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

      2. mul-1-neg 72.1%

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

      3. unsub-neg 72.1%

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

   6. Simplified 72.1%

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

   if 1.9e20 < y5 < 1.65e50

   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. Add Preprocessing

   3. Taylor expanded in y3 around -inf 26.7%

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

   4. Taylor expanded in y around inf 51.4%

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

   if 1.65e50 < y5 < 7.1999999999999999e80

   1. Initial program 38.5%

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

   3. Taylor expanded in b around inf 54.7%

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

   4. Taylor expanded in y0 around inf 54.9%

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

   if 7.1999999999999999e80 < y5

   1. Initial program 14.9%

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

   3. Taylor expanded in j around inf 36.1%

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

   4. Taylor expanded in y0 around inf 61.2%

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

4. Final simplification 51.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -1.45 \cdot 10^{+32}:\\ \;\;\;\;y3 \cdot \left(y5 \cdot \left(j \cdot y0 - y \cdot a\right)\right)\\ \mathbf{elif}\;y5 \leq 9.5 \cdot 10^{-167}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y5 \leq 0.39:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;y5 \leq 1.9 \cdot 10^{+20}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;y5 \leq 1.65 \cdot 10^{+50}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq 7.2 \cdot 10^{+80}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 22: 30.5% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -3.15 \cdot 10^{+41}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq -2.3 \cdot 10^{-220}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 2 \cdot 10^{-247}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 3.5 \cdot 10^{-175}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.9 \cdot 10^{-142}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;i \leq 1.6 \cdot 10^{+138}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -3.15e+41)
   (* y5 (* k (- (* y i) (* y0 y2))))
   (if (<= i -2.3e-220)
     (* b (* x (- (* y a) (* j y0))))
     (if (<= i 2e-247)
       (* k (* y2 (- (* y1 y4) (* y0 y5))))
       (if (<= i 3.5e-175)
         (* j (* y3 (- (* y0 y5) (* y1 y4))))
         (if (<= i 1.9e-142)
           (* b (* z (- (* k y0) (* t a))))
           (if (<= i 1.6e+138)
             (* y0 (* j (- (* y3 y5) (* x b))))
             (* 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 tmp;
	if (i <= -3.15e+41) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (i <= -2.3e-220) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (i <= 2e-247) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 3.5e-175) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1.9e-142) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (i <= 1.6e+138) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} 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) :: tmp
    if (i <= (-3.15d+41)) then
        tmp = y5 * (k * ((y * i) - (y0 * y2)))
    else if (i <= (-2.3d-220)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (i <= 2d-247) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (i <= 3.5d-175) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 1.9d-142) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (i <= 1.6d+138) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    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 tmp;
	if (i <= -3.15e+41) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (i <= -2.3e-220) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (i <= 2e-247) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 3.5e-175) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1.9e-142) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (i <= 1.6e+138) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} 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):
	tmp = 0
	if i <= -3.15e+41:
		tmp = y5 * (k * ((y * i) - (y0 * y2)))
	elif i <= -2.3e-220:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif i <= 2e-247:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif i <= 3.5e-175:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 1.9e-142:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif i <= 1.6e+138:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	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)
	tmp = 0.0
	if (i <= -3.15e+41)
		tmp = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (i <= -2.3e-220)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (i <= 2e-247)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (i <= 3.5e-175)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 1.9e-142)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (i <= 1.6e+138)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	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)
	tmp = 0.0;
	if (i <= -3.15e+41)
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	elseif (i <= -2.3e-220)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (i <= 2e-247)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (i <= 3.5e-175)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 1.9e-142)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (i <= 1.6e+138)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	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_] := If[LessEqual[i, -3.15e+41], N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -2.3e-220], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2e-247], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.5e-175], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.9e-142], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.6e+138], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $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 7 regimes

2. if i < -3.1499999999999999e41

   1. Initial program 31.8%

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

   3. Taylor expanded in y5 around -inf 42.6%

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

   4. Taylor expanded in k around inf 48.5%

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

      1. +-commutative 48.5%

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

      2. mul-1-neg 48.5%

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

      3. unsub-neg 48.5%

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

      4. *-commutative 48.5%

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

   6. Simplified 48.5%

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

   if -3.1499999999999999e41 < i < -2.29999999999999981e-220

   1. Initial program 40.3%

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

   3. Taylor expanded in x around inf 41.2%

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

      1. fma-define 43.2%

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

      2. fma-neg 43.2%

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

   5. Simplified 43.2%

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

   6. Taylor expanded in b around inf 45.1%

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

   if -2.29999999999999981e-220 < i < 2e-247

   1. Initial program 46.8%

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

   3. Taylor expanded in y2 around inf 46.6%

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

   4. Taylor expanded in k around inf 44.4%

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

   if 2e-247 < i < 3.49999999999999999e-175

   1. Initial program 28.6%

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

   3. Taylor expanded in j around inf 50.8%

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

   4. Taylor expanded in y3 around inf 51.2%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 51.2%

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

      2. neg-mul-1 51.2%

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

   6. Simplified 51.2%

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

   if 3.49999999999999999e-175 < i < 1.89999999999999986e-142

   1. Initial program 0.0%

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

   3. Taylor expanded in b around inf 44.5%

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

   4. Taylor expanded in z around -inf 56.4%

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

      1. mul-1-neg 56.4%

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

   6. Simplified 56.4%

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

   if 1.89999999999999986e-142 < i < 1.6000000000000001e138

   1. Initial program 29.0%

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

   3. Taylor expanded in y0 around inf 37.0%

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

   4. Taylor expanded in j around inf 49.7%

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

      1. *-commutative 49.7%

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

   6. Simplified 49.7%

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

   if 1.6000000000000001e138 < i

   1. Initial program 25.2%

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

   3. Taylor expanded in x around inf 38.2%

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

      1. fma-define 38.2%

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

      2. fma-neg 41.3%

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

   5. Simplified 41.3%

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

   6. Taylor expanded in c around inf 50.6%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -3.15 \cdot 10^{+41}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq -2.3 \cdot 10^{-220}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 2 \cdot 10^{-247}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 3.5 \cdot 10^{-175}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.9 \cdot 10^{-142}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;i \leq 1.6 \cdot 10^{+138}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 23: 30.8% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -5.7 \cdot 10^{+41}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq -8.2 \cdot 10^{-219}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 1.3 \cdot 10^{-248}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 1.15 \cdot 10^{-174}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.3 \cdot 10^{-143}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;i \leq 3.8 \cdot 10^{+103}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -5.7e+41)
   (* y5 (* k (- (* y i) (* y0 y2))))
   (if (<= i -8.2e-219)
     (* b (* x (- (* y a) (* j y0))))
     (if (<= i 1.3e-248)
       (* k (* y2 (- (* y1 y4) (* y0 y5))))
       (if (<= i 1.15e-174)
         (* j (* y3 (- (* y0 y5) (* y1 y4))))
         (if (<= i 1.3e-143)
           (* b (* z (- (* k y0) (* t a))))
           (if (<= i 3.8e+103)
             (* y0 (* j (- (* y3 y5) (* x b))))
             (* j (* t (- (* b y4) (* i 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 (i <= -5.7e+41) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (i <= -8.2e-219) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (i <= 1.3e-248) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 1.15e-174) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1.3e-143) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (i <= 3.8e+103) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else {
		tmp = j * (t * ((b * y4) - (i * 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 (i <= (-5.7d+41)) then
        tmp = y5 * (k * ((y * i) - (y0 * y2)))
    else if (i <= (-8.2d-219)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (i <= 1.3d-248) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (i <= 1.15d-174) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 1.3d-143) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (i <= 3.8d+103) then
        tmp = y0 * (j * ((y3 * y5) - (x * b)))
    else
        tmp = j * (t * ((b * y4) - (i * 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 (i <= -5.7e+41) {
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	} else if (i <= -8.2e-219) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (i <= 1.3e-248) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 1.15e-174) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1.3e-143) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (i <= 3.8e+103) {
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	} else {
		tmp = j * (t * ((b * y4) - (i * 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 i <= -5.7e+41:
		tmp = y5 * (k * ((y * i) - (y0 * y2)))
	elif i <= -8.2e-219:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif i <= 1.3e-248:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif i <= 1.15e-174:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 1.3e-143:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif i <= 3.8e+103:
		tmp = y0 * (j * ((y3 * y5) - (x * b)))
	else:
		tmp = j * (t * ((b * y4) - (i * 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 (i <= -5.7e+41)
		tmp = Float64(y5 * Float64(k * Float64(Float64(y * i) - Float64(y0 * y2))));
	elseif (i <= -8.2e-219)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (i <= 1.3e-248)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (i <= 1.15e-174)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 1.3e-143)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (i <= 3.8e+103)
		tmp = Float64(y0 * Float64(j * Float64(Float64(y3 * y5) - Float64(x * b))));
	else
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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 (i <= -5.7e+41)
		tmp = y5 * (k * ((y * i) - (y0 * y2)));
	elseif (i <= -8.2e-219)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (i <= 1.3e-248)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (i <= 1.15e-174)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 1.3e-143)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (i <= 3.8e+103)
		tmp = y0 * (j * ((y3 * y5) - (x * b)));
	else
		tmp = j * (t * ((b * y4) - (i * 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[i, -5.7e+41], N[(y5 * N[(k * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -8.2e-219], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.3e-248], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.15e-174], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.3e-143], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.8e+103], N[(y0 * N[(j * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if i < -5.70000000000000021e41

   1. Initial program 31.8%

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

   3. Taylor expanded in y5 around -inf 42.6%

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

   4. Taylor expanded in k around inf 48.5%

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

      1. +-commutative 48.5%

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

      2. mul-1-neg 48.5%

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

      3. unsub-neg 48.5%

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

      4. *-commutative 48.5%

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

   6. Simplified 48.5%

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

   if -5.70000000000000021e41 < i < -8.2e-219

   1. Initial program 40.3%

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

   3. Taylor expanded in x around inf 41.2%

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

      1. fma-define 43.2%

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

      2. fma-neg 43.2%

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

   5. Simplified 43.2%

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

   6. Taylor expanded in b around inf 45.1%

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

   if -8.2e-219 < i < 1.30000000000000003e-248

   1. Initial program 46.8%

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

   3. Taylor expanded in y2 around inf 46.6%

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

   4. Taylor expanded in k around inf 44.4%

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

   if 1.30000000000000003e-248 < i < 1.1499999999999999e-174

   1. Initial program 28.6%

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

   3. Taylor expanded in j around inf 50.8%

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

   4. Taylor expanded in y3 around inf 51.2%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 51.2%

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

      2. neg-mul-1 51.2%

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

   6. Simplified 51.2%

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

   if 1.1499999999999999e-174 < i < 1.29999999999999994e-143

   1. Initial program 0.0%

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

   3. Taylor expanded in b around inf 44.5%

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

   4. Taylor expanded in z around -inf 56.4%

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

      1. mul-1-neg 56.4%

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

   6. Simplified 56.4%

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

   if 1.29999999999999994e-143 < i < 3.7999999999999997e103

   1. Initial program 26.4%

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

   3. Taylor expanded in y0 around inf 36.7%

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

   4. Taylor expanded in j around inf 50.3%

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

      1. *-commutative 50.3%

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

   6. Simplified 50.3%

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

   if 3.7999999999999997e103 < i

   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. Add Preprocessing

   3. Taylor expanded in j around inf 46.2%

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

   4. Taylor expanded in t around inf 46.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -5.7 \cdot 10^{+41}:\\ \;\;\;\;y5 \cdot \left(k \cdot \left(y \cdot i - y0 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq -8.2 \cdot 10^{-219}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 1.3 \cdot 10^{-248}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 1.15 \cdot 10^{-174}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.3 \cdot 10^{-143}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;i \leq 3.8 \cdot 10^{+103}:\\ \;\;\;\;y0 \cdot \left(j \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 24: 28.9% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -120000000:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;a \leq -6.6 \cdot 10^{-274}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;a \leq 1.55 \cdot 10^{-49}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{+26}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{+82}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;a \leq 4.8 \cdot 10^{+193}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= a -120000000.0)
   (* j (* y0 (- (* y3 y5) (* x b))))
   (if (<= a -6.6e-274)
     (* k (* y1 (- (* y2 y4) (* z i))))
     (if (<= a 1.55e-49)
       (* j (* y3 (- (* y0 y5) (* y1 y4))))
       (if (<= a 1.4e+26)
         (* x (* y0 (- (* c y2) (* b j))))
         (if (<= a 5.8e+82)
           (* x (* y (- (* a b) (* c i))))
           (if (<= a 4.8e+193)
             (* y (* y3 (- (* c y4) (* a y5))))
             (* y2 (* t (- (* a y5) (* c y4)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (a <= -120000000.0) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (a <= -6.6e-274) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (a <= 1.55e-49) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (a <= 1.4e+26) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (a <= 5.8e+82) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (a <= 4.8e+193) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (a <= (-120000000.0d0)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (a <= (-6.6d-274)) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (a <= 1.55d-49) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (a <= 1.4d+26) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else if (a <= 5.8d+82) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (a <= 4.8d+193) then
        tmp = y * (y3 * ((c * y4) - (a * y5)))
    else
        tmp = y2 * (t * ((a * y5) - (c * y4)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (a <= -120000000.0) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (a <= -6.6e-274) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (a <= 1.55e-49) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (a <= 1.4e+26) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (a <= 5.8e+82) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (a <= 4.8e+193) {
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	} else {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if a <= -120000000.0:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif a <= -6.6e-274:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif a <= 1.55e-49:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif a <= 1.4e+26:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	elif a <= 5.8e+82:
		tmp = x * (y * ((a * b) - (c * i)))
	elif a <= 4.8e+193:
		tmp = y * (y3 * ((c * y4) - (a * y5)))
	else:
		tmp = y2 * (t * ((a * y5) - (c * y4)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (a <= -120000000.0)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (a <= -6.6e-274)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (a <= 1.55e-49)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (a <= 1.4e+26)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (a <= 5.8e+82)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (a <= 4.8e+193)
		tmp = Float64(y * Float64(y3 * Float64(Float64(c * y4) - Float64(a * y5))));
	else
		tmp = Float64(y2 * Float64(t * Float64(Float64(a * y5) - Float64(c * y4))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (a <= -120000000.0)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (a <= -6.6e-274)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (a <= 1.55e-49)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (a <= 1.4e+26)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	elseif (a <= 5.8e+82)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (a <= 4.8e+193)
		tmp = y * (y3 * ((c * y4) - (a * y5)));
	else
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[a, -120000000.0], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -6.6e-274], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.55e-49], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.4e+26], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.8e+82], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.8e+193], N[(y * N[(y3 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y2 * N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if a < -1.2e8

   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. Add Preprocessing

   3. Taylor expanded in j around inf 38.6%

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

   4. Taylor expanded in y0 around inf 42.2%

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

   if -1.2e8 < a < -6.5999999999999996e-274

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 42.1%

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

   4. Taylor expanded in k around inf 42.3%

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

   if -6.5999999999999996e-274 < a < 1.55e-49

   1. Initial program 38.1%

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

   3. Taylor expanded in j around inf 51.8%

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

   4. Taylor expanded in y3 around inf 47.4%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 47.4%

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

      2. neg-mul-1 47.4%

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

   6. Simplified 47.4%

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

   if 1.55e-49 < a < 1.4e26

   1. Initial program 23.5%

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

   3. Taylor expanded in x around inf 39.6%

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

      1. fma-define 47.3%

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

      2. fma-neg 47.3%

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

   5. Simplified 47.3%

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

   6. Taylor expanded in y0 around inf 62.7%

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

   if 1.4e26 < a < 5.8000000000000003e82

   1. Initial program 39.0%

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

   3. Taylor expanded in x around inf 47.7%

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

      1. fma-define 47.7%

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

      2. fma-neg 47.7%

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

   5. Simplified 47.7%

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

   6. Taylor expanded in y around inf 63.3%

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

   if 5.8000000000000003e82 < a < 4.8e193

   1. Initial program 28.5%

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

   3. Taylor expanded in y3 around -inf 34.6%

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

   4. Taylor expanded in y around inf 47.6%

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

   if 4.8e193 < a

   1. Initial program 26.0%

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

   3. Taylor expanded in y2 around inf 43.7%

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

   4. Taylor expanded in t around inf 57.0%

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

      1. *-commutative 57.0%

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

   6. Simplified 57.0%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 47.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -120000000:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;a \leq -6.6 \cdot 10^{-274}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;a \leq 1.55 \cdot 10^{-49}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{+26}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{+82}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;a \leq 4.8 \cdot 10^{+193}:\\ \;\;\;\;y \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 25: 30.6% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{if}\;x \leq -1.65 \cdot 10^{+126}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{+30}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -3 \cdot 10^{-39}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -2.45 \cdot 10^{-175}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(y2 \cdot y5\right)\\ \mathbf{elif}\;x \leq -5.2 \cdot 10^{-258}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 2.1 \cdot 10^{+23}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0))))))
   (if (<= x -1.65e+126)
     (* j (* y0 (- (* y3 y5) (* x b))))
     (if (<= x -8.5e+30)
       t_1
       (if (<= x -3e-39)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= x -2.45e-175)
           (* (* t a) (* y2 y5))
           (if (<= x -5.2e-258)
             (* a (* b (- (* x y) (* z t))))
             (if (<= x 2.1e+23) (* k (* y1 (- (* y2 y4) (* z 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 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (x <= -1.65e+126) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (x <= -8.5e+30) {
		tmp = t_1;
	} else if (x <= -3e-39) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (x <= -2.45e-175) {
		tmp = (t * a) * (y2 * y5);
	} else if (x <= -5.2e-258) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (x <= 2.1e+23) {
		tmp = k * (y1 * ((y2 * y4) - (z * 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 = b * (x * ((y * a) - (j * y0)))
    if (x <= (-1.65d+126)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (x <= (-8.5d+30)) then
        tmp = t_1
    else if (x <= (-3d-39)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (x <= (-2.45d-175)) then
        tmp = (t * a) * (y2 * y5)
    else if (x <= (-5.2d-258)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (x <= 2.1d+23) then
        tmp = k * (y1 * ((y2 * y4) - (z * 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 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (x <= -1.65e+126) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (x <= -8.5e+30) {
		tmp = t_1;
	} else if (x <= -3e-39) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (x <= -2.45e-175) {
		tmp = (t * a) * (y2 * y5);
	} else if (x <= -5.2e-258) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (x <= 2.1e+23) {
		tmp = k * (y1 * ((y2 * y4) - (z * 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 = b * (x * ((y * a) - (j * y0)))
	tmp = 0
	if x <= -1.65e+126:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif x <= -8.5e+30:
		tmp = t_1
	elif x <= -3e-39:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif x <= -2.45e-175:
		tmp = (t * a) * (y2 * y5)
	elif x <= -5.2e-258:
		tmp = a * (b * ((x * y) - (z * t)))
	elif x <= 2.1e+23:
		tmp = k * (y1 * ((y2 * y4) - (z * 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(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	tmp = 0.0
	if (x <= -1.65e+126)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (x <= -8.5e+30)
		tmp = t_1;
	elseif (x <= -3e-39)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (x <= -2.45e-175)
		tmp = Float64(Float64(t * a) * Float64(y2 * y5));
	elseif (x <= -5.2e-258)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (x <= 2.1e+23)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * 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 = b * (x * ((y * a) - (j * y0)));
	tmp = 0.0;
	if (x <= -1.65e+126)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (x <= -8.5e+30)
		tmp = t_1;
	elseif (x <= -3e-39)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (x <= -2.45e-175)
		tmp = (t * a) * (y2 * y5);
	elseif (x <= -5.2e-258)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (x <= 2.1e+23)
		tmp = k * (y1 * ((y2 * y4) - (z * 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[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.65e+126], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -8.5e+30], t$95$1, If[LessEqual[x, -3e-39], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2.45e-175], N[(N[(t * a), $MachinePrecision] * N[(y2 * y5), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -5.2e-258], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 2.1e+23], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 6 regimes

2. if x < -1.65000000000000006e126

   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. Add Preprocessing

   3. Taylor expanded in j around inf 41.8%

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

   4. Taylor expanded in y0 around inf 57.3%

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

   if -1.65000000000000006e126 < x < -8.4999999999999995e30 or 2.1000000000000001e23 < x

   1. Initial program 31.8%

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

   3. Taylor expanded in x around inf 55.5%

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

      1. fma-define 59.2%

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

      2. fma-neg 60.4%

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

   5. Simplified 60.4%

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

   6. Taylor expanded in b around inf 50.8%

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

   if -8.4999999999999995e30 < x < -3.00000000000000028e-39

   1. Initial program 0.4%

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

   3. Taylor expanded in j around inf 46.6%

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

   4. Taylor expanded in t around inf 54.9%

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

   if -3.00000000000000028e-39 < x < -2.44999999999999999e-175

   1. Initial program 34.7%

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

   3. Taylor expanded in y2 around inf 34.7%

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

   4. Taylor expanded in t around inf 41.2%

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

      1. *-commutative 41.2%

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

   6. Simplified 41.2%

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

   7. Taylor expanded in y5 around inf 28.4%

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

      1. associate-*r* 34.6%

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

      2. *-commutative 34.6%

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

   9. Simplified 34.6%

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

   if -2.44999999999999999e-175 < x < -5.20000000000000036e-258

   1. Initial program 27.8%

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

   3. Taylor expanded in b around inf 56.0%

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

   4. Taylor expanded in a around inf 50.6%

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

   if -5.20000000000000036e-258 < x < 2.1000000000000001e23

   1. Initial program 44.4%

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

   3. Taylor expanded in y1 around inf 46.4%

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

   4. Taylor expanded in k around inf 39.8%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 47.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.65 \cdot 10^{+126}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{+30}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -3 \cdot 10^{-39}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -2.45 \cdot 10^{-175}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(y2 \cdot y5\right)\\ \mathbf{elif}\;x \leq -5.2 \cdot 10^{-258}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 2.1 \cdot 10^{+23}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 26: 21.7% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -4.7 \cdot 10^{+23}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -6.4 \cdot 10^{-74}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{+74}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{+183}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{+199} \lor \neg \left(t \leq 2.3 \cdot 10^{+244}\right):\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= t -4.7e+23)
     t_1
     (if (<= t -6.4e-74)
       (* i (* j (* x y1)))
       (if (<= t 2e+74)
         (* a (* (* x y) b))
         (if (<= t 4.6e+183)
           (* x (* c (* y0 y2)))
           (if (or (<= t 1.4e+199) (not (<= t 2.3e+244)))
             t_1
             (* y2 (* a (* t y5))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (t <= -4.7e+23) {
		tmp = t_1;
	} else if (t <= -6.4e-74) {
		tmp = i * (j * (x * y1));
	} else if (t <= 2e+74) {
		tmp = a * ((x * y) * b);
	} else if (t <= 4.6e+183) {
		tmp = x * (c * (y0 * y2));
	} else if ((t <= 1.4e+199) || !(t <= 2.3e+244)) {
		tmp = t_1;
	} else {
		tmp = y2 * (a * (t * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (j * (t * y4))
    if (t <= (-4.7d+23)) then
        tmp = t_1
    else if (t <= (-6.4d-74)) then
        tmp = i * (j * (x * y1))
    else if (t <= 2d+74) then
        tmp = a * ((x * y) * b)
    else if (t <= 4.6d+183) then
        tmp = x * (c * (y0 * y2))
    else if ((t <= 1.4d+199) .or. (.not. (t <= 2.3d+244))) then
        tmp = t_1
    else
        tmp = y2 * (a * (t * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (t <= -4.7e+23) {
		tmp = t_1;
	} else if (t <= -6.4e-74) {
		tmp = i * (j * (x * y1));
	} else if (t <= 2e+74) {
		tmp = a * ((x * y) * b);
	} else if (t <= 4.6e+183) {
		tmp = x * (c * (y0 * y2));
	} else if ((t <= 1.4e+199) || !(t <= 2.3e+244)) {
		tmp = t_1;
	} else {
		tmp = y2 * (a * (t * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (j * (t * y4))
	tmp = 0
	if t <= -4.7e+23:
		tmp = t_1
	elif t <= -6.4e-74:
		tmp = i * (j * (x * y1))
	elif t <= 2e+74:
		tmp = a * ((x * y) * b)
	elif t <= 4.6e+183:
		tmp = x * (c * (y0 * y2))
	elif (t <= 1.4e+199) or not (t <= 2.3e+244):
		tmp = t_1
	else:
		tmp = y2 * (a * (t * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (t <= -4.7e+23)
		tmp = t_1;
	elseif (t <= -6.4e-74)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (t <= 2e+74)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 4.6e+183)
		tmp = Float64(x * Float64(c * Float64(y0 * y2)));
	elseif ((t <= 1.4e+199) || !(t <= 2.3e+244))
		tmp = t_1;
	else
		tmp = Float64(y2 * Float64(a * Float64(t * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (j * (t * y4));
	tmp = 0.0;
	if (t <= -4.7e+23)
		tmp = t_1;
	elseif (t <= -6.4e-74)
		tmp = i * (j * (x * y1));
	elseif (t <= 2e+74)
		tmp = a * ((x * y) * b);
	elseif (t <= 4.6e+183)
		tmp = x * (c * (y0 * y2));
	elseif ((t <= 1.4e+199) || ~((t <= 2.3e+244)))
		tmp = t_1;
	else
		tmp = y2 * (a * (t * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -4.7e+23], t$95$1, If[LessEqual[t, -6.4e-74], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2e+74], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.6e+183], N[(x * N[(c * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[t, 1.4e+199], N[Not[LessEqual[t, 2.3e+244]], $MachinePrecision]], t$95$1, N[(y2 * N[(a * N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -4.6999999999999997e23 or 4.5999999999999996e183 < t < 1.40000000000000005e199 or 2.2999999999999999e244 < t

   1. Initial program 29.5%

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

   3. Taylor expanded in j around inf 37.3%

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

   4. Taylor expanded in t around inf 43.1%

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

   5. Taylor expanded in b around inf 49.9%

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

   if -4.6999999999999997e23 < t < -6.3999999999999997e-74

   1. Initial program 21.4%

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

   3. Taylor expanded in x around inf 50.1%

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

      1. fma-define 50.1%

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

      2. fma-neg 50.1%

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

   5. Simplified 50.1%

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

   6. Taylor expanded in i around -inf 51.3%

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

      1. associate-*r* 51.3%

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

      2. neg-mul-1 51.3%

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

   8. Simplified 51.3%

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

   9. Taylor expanded in c around 0 44.3%

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

   if -6.3999999999999997e-74 < t < 1.9999999999999999e74

   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. Add Preprocessing

   3. Taylor expanded in b around inf 36.8%

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

   4. Taylor expanded in a around inf 27.3%

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

   5. Taylor expanded in x around inf 25.2%

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

      1. *-commutative 25.2%

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

   7. Simplified 25.2%

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

   if 1.9999999999999999e74 < t < 4.5999999999999996e183

   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. Add Preprocessing

   3. Taylor expanded in x around inf 33.1%

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

      1. fma-define 33.1%

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

      2. fma-neg 33.1%

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

   5. Simplified 33.1%

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

   6. Taylor expanded in y2 around inf 25.7%

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

   7. Taylor expanded in c around inf 37.1%

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

   if 1.40000000000000005e199 < t < 2.2999999999999999e244

   1. Initial program 41.7%

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

   3. Taylor expanded in y2 around inf 42.3%

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

   4. Taylor expanded in t around inf 59.5%

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

      1. *-commutative 59.5%

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

   6. Simplified 59.5%

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

   7. Taylor expanded in y5 around inf 59.8%

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

      1. *-commutative 59.8%

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

   9. Simplified 59.8%

      \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(y5 \cdot t\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 35.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -4.7 \cdot 10^{+23}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -6.4 \cdot 10^{-74}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{+74}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{+183}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{+199} \lor \neg \left(t \leq 2.3 \cdot 10^{+244}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 27: 32.0% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;y0 \leq -1.55 \cdot 10^{+16}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq -3.9 \cdot 10^{-259}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.95 \cdot 10^{-44}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq 5.2 \cdot 10^{+53} \lor \neg \left(y0 \leq 4.5 \cdot 10^{+239}\right):\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= y0 -1.55e+16)
     t_1
     (if (<= y0 -3.9e-259)
       (* j (* t (- (* b y4) (* i y5))))
       (if (<= y0 1.95e-44)
         (* a (* b (- (* x y) (* z t))))
         (if (or (<= y0 5.2e+53) (not (<= y0 4.5e+239)))
           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 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (y0 <= -1.55e+16) {
		tmp = t_1;
	} else if (y0 <= -3.9e-259) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y0 <= 1.95e-44) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((y0 <= 5.2e+53) || !(y0 <= 4.5e+239)) {
		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 = b * (y0 * ((z * k) - (x * j)))
    if (y0 <= (-1.55d+16)) then
        tmp = t_1
    else if (y0 <= (-3.9d-259)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y0 <= 1.95d-44) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if ((y0 <= 5.2d+53) .or. (.not. (y0 <= 4.5d+239))) 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 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (y0 <= -1.55e+16) {
		tmp = t_1;
	} else if (y0 <= -3.9e-259) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y0 <= 1.95e-44) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((y0 <= 5.2e+53) || !(y0 <= 4.5e+239)) {
		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 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if y0 <= -1.55e+16:
		tmp = t_1
	elif y0 <= -3.9e-259:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y0 <= 1.95e-44:
		tmp = a * (b * ((x * y) - (z * t)))
	elif (y0 <= 5.2e+53) or not (y0 <= 4.5e+239):
		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(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (y0 <= -1.55e+16)
		tmp = t_1;
	elseif (y0 <= -3.9e-259)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y0 <= 1.95e-44)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif ((y0 <= 5.2e+53) || !(y0 <= 4.5e+239))
		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 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (y0 <= -1.55e+16)
		tmp = t_1;
	elseif (y0 <= -3.9e-259)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y0 <= 1.95e-44)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif ((y0 <= 5.2e+53) || ~((y0 <= 4.5e+239)))
		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[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -1.55e+16], t$95$1, If[LessEqual[y0, -3.9e-259], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.95e-44], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[y0, 5.2e+53], N[Not[LessEqual[y0, 4.5e+239]], $MachinePrecision]], 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 y0 < -1.55e16 or 1.9500000000000001e-44 < y0 < 5.19999999999999996e53 or 4.4999999999999998e239 < y0

   1. Initial program 28.5%

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

   3. Taylor expanded in b around inf 36.7%

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

   4. Taylor expanded in y0 around inf 48.7%

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

   if -1.55e16 < y0 < -3.90000000000000016e-259

   1. Initial program 33.8%

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

   3. Taylor expanded in j around inf 41.7%

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

   4. Taylor expanded in t around inf 40.4%

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

   if -3.90000000000000016e-259 < y0 < 1.9500000000000001e-44

   1. Initial program 41.2%

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

   3. Taylor expanded in b around inf 35.9%

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

   4. Taylor expanded in a around inf 35.8%

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

   if 5.19999999999999996e53 < y0 < 4.4999999999999998e239

   1. Initial program 24.7%

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

   3. Taylor expanded in x around inf 33.5%

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

      1. fma-define 36.2%

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

      2. fma-neg 36.2%

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

   5. Simplified 36.2%

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

   6. Taylor expanded in b around inf 44.0%

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

4. Final simplification 43.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -1.55 \cdot 10^{+16}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq -3.9 \cdot 10^{-259}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.95 \cdot 10^{-44}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq 5.2 \cdot 10^{+53} \lor \neg \left(y0 \leq 4.5 \cdot 10^{+239}\right):\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 28: 27.6% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{if}\;x \leq -12000000000:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -1.52 \cdot 10^{-177}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 2.55 \cdot 10^{-123}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 9.5 \cdot 10^{+265}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq 2.6 \cdot 10^{+298}:\\ \;\;\;\;\left(y0 \cdot y2\right) \cdot \left(x \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(y2 \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0))))))
   (if (<= x -12000000000.0)
     t_1
     (if (<= x -1.52e-177)
       (* y2 (* a (* t y5)))
       (if (<= x 2.55e-123)
         (* a (* b (- (* x y) (* z t))))
         (if (<= x 9.5e+265)
           t_1
           (if (<= x 2.6e+298)
             (* (* y0 y2) (* x c))
             (* (* t a) (* y2 y5)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (x <= -12000000000.0) {
		tmp = t_1;
	} else if (x <= -1.52e-177) {
		tmp = y2 * (a * (t * y5));
	} else if (x <= 2.55e-123) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (x <= 9.5e+265) {
		tmp = t_1;
	} else if (x <= 2.6e+298) {
		tmp = (y0 * y2) * (x * c);
	} else {
		tmp = (t * a) * (y2 * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (x * ((y * a) - (j * y0)))
    if (x <= (-12000000000.0d0)) then
        tmp = t_1
    else if (x <= (-1.52d-177)) then
        tmp = y2 * (a * (t * y5))
    else if (x <= 2.55d-123) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (x <= 9.5d+265) then
        tmp = t_1
    else if (x <= 2.6d+298) then
        tmp = (y0 * y2) * (x * c)
    else
        tmp = (t * a) * (y2 * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (x * ((y * a) - (j * y0)));
	double tmp;
	if (x <= -12000000000.0) {
		tmp = t_1;
	} else if (x <= -1.52e-177) {
		tmp = y2 * (a * (t * y5));
	} else if (x <= 2.55e-123) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (x <= 9.5e+265) {
		tmp = t_1;
	} else if (x <= 2.6e+298) {
		tmp = (y0 * y2) * (x * c);
	} else {
		tmp = (t * a) * (y2 * y5);
	}
	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)))
	tmp = 0
	if x <= -12000000000.0:
		tmp = t_1
	elif x <= -1.52e-177:
		tmp = y2 * (a * (t * y5))
	elif x <= 2.55e-123:
		tmp = a * (b * ((x * y) - (z * t)))
	elif x <= 9.5e+265:
		tmp = t_1
	elif x <= 2.6e+298:
		tmp = (y0 * y2) * (x * c)
	else:
		tmp = (t * a) * (y2 * 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(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	tmp = 0.0
	if (x <= -12000000000.0)
		tmp = t_1;
	elseif (x <= -1.52e-177)
		tmp = Float64(y2 * Float64(a * Float64(t * y5)));
	elseif (x <= 2.55e-123)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (x <= 9.5e+265)
		tmp = t_1;
	elseif (x <= 2.6e+298)
		tmp = Float64(Float64(y0 * y2) * Float64(x * c));
	else
		tmp = Float64(Float64(t * a) * Float64(y2 * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (x * ((y * a) - (j * y0)));
	tmp = 0.0;
	if (x <= -12000000000.0)
		tmp = t_1;
	elseif (x <= -1.52e-177)
		tmp = y2 * (a * (t * y5));
	elseif (x <= 2.55e-123)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (x <= 9.5e+265)
		tmp = t_1;
	elseif (x <= 2.6e+298)
		tmp = (y0 * y2) * (x * c);
	else
		tmp = (t * a) * (y2 * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -12000000000.0], t$95$1, If[LessEqual[x, -1.52e-177], N[(y2 * N[(a * N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 2.55e-123], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 9.5e+265], t$95$1, If[LessEqual[x, 2.6e+298], N[(N[(y0 * y2), $MachinePrecision] * N[(x * c), $MachinePrecision]), $MachinePrecision], N[(N[(t * a), $MachinePrecision] * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if x < -1.2e10 or 2.55000000000000005e-123 < x < 9.4999999999999993e265

   1. Initial program 33.9%

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

   3. Taylor expanded in x around inf 48.8%

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

      1. fma-define 50.8%

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

      2. fma-neg 51.5%

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

   5. Simplified 51.5%

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

   6. Taylor expanded in b around inf 42.3%

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

   if -1.2e10 < x < -1.52000000000000006e-177

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 34.5%

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

   4. Taylor expanded in t around inf 42.7%

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

      1. *-commutative 42.7%

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

   6. Simplified 42.7%

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

   7. Taylor expanded in y5 around inf 37.3%

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

      1. *-commutative 37.3%

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

   9. Simplified 37.3%

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

   if -1.52000000000000006e-177 < x < 2.55000000000000005e-123

   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. Add Preprocessing

   3. Taylor expanded in b around inf 37.4%

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

   4. Taylor expanded in a around inf 33.9%

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

   if 9.4999999999999993e265 < x < 2.6e298

   1. Initial program 9.1%

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

   3. Taylor expanded in x around inf 54.5%

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

      1. fma-define 54.5%

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

      2. fma-neg 63.6%

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

   5. Simplified 63.6%

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

   6. Taylor expanded in y2 around inf 55.9%

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

   7. Taylor expanded in c around inf 56.0%

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

      1. pow1 56.0%

         \[\leadsto \color{blue}{{\left(c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\right)}^{1}} \]

      2. associate-*r* 73.2%

         \[\leadsto {\color{blue}{\left(\left(c \cdot x\right) \cdot \left(y0 \cdot y2\right)\right)}}^{1} \]

   9. Applied egg-rr 73.2%

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

       1. unpow1 73.2%

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

       2. *-commutative 73.2%

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

   11. Simplified 73.2%

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

   if 2.6e298 < x

   1. Initial program 0.0%

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

   3. Taylor expanded in y2 around inf 33.3%

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

   4. Taylor expanded in t around inf 2.8%

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

      1. *-commutative 2.8%

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

   6. Simplified 2.8%

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

   7. Taylor expanded in y5 around inf 35.4%

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

      1. associate-*r* 67.3%

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

      2. *-commutative 67.3%

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

   9. Simplified 67.3%

      \[\leadsto \color{blue}{\left(a \cdot t\right) \cdot \left(y5 \cdot y2\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 41.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -12000000000:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.52 \cdot 10^{-177}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 2.55 \cdot 10^{-123}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;x \leq 9.5 \cdot 10^{+265}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq 2.6 \cdot 10^{+298}:\\ \;\;\;\;\left(y0 \cdot y2\right) \cdot \left(x \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;\left(t \cdot a\right) \cdot \left(y2 \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 29: 22.1% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -1.85 \cdot 10^{+26}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -8.2 \cdot 10^{-75}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+69}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{+114}:\\ \;\;\;\;i \cdot \left(\left(-j\right) \cdot \left(t \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 3.9 \cdot 10^{+183}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= t -1.85e+26)
     t_1
     (if (<= t -8.2e-75)
       (* i (* j (* x y1)))
       (if (<= t 6.2e+69)
         (* a (* (* x y) b))
         (if (<= t 2.4e+114)
           (* i (* (- j) (* t y5)))
           (if (<= t 3.9e+183) (* x (* c (* y0 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 = b * (j * (t * y4));
	double tmp;
	if (t <= -1.85e+26) {
		tmp = t_1;
	} else if (t <= -8.2e-75) {
		tmp = i * (j * (x * y1));
	} else if (t <= 6.2e+69) {
		tmp = a * ((x * y) * b);
	} else if (t <= 2.4e+114) {
		tmp = i * (-j * (t * y5));
	} else if (t <= 3.9e+183) {
		tmp = x * (c * (y0 * 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) :: tmp
    t_1 = b * (j * (t * y4))
    if (t <= (-1.85d+26)) then
        tmp = t_1
    else if (t <= (-8.2d-75)) then
        tmp = i * (j * (x * y1))
    else if (t <= 6.2d+69) then
        tmp = a * ((x * y) * b)
    else if (t <= 2.4d+114) then
        tmp = i * (-j * (t * y5))
    else if (t <= 3.9d+183) then
        tmp = x * (c * (y0 * 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 = b * (j * (t * y4));
	double tmp;
	if (t <= -1.85e+26) {
		tmp = t_1;
	} else if (t <= -8.2e-75) {
		tmp = i * (j * (x * y1));
	} else if (t <= 6.2e+69) {
		tmp = a * ((x * y) * b);
	} else if (t <= 2.4e+114) {
		tmp = i * (-j * (t * y5));
	} else if (t <= 3.9e+183) {
		tmp = x * (c * (y0 * 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 = b * (j * (t * y4))
	tmp = 0
	if t <= -1.85e+26:
		tmp = t_1
	elif t <= -8.2e-75:
		tmp = i * (j * (x * y1))
	elif t <= 6.2e+69:
		tmp = a * ((x * y) * b)
	elif t <= 2.4e+114:
		tmp = i * (-j * (t * y5))
	elif t <= 3.9e+183:
		tmp = x * (c * (y0 * 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(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (t <= -1.85e+26)
		tmp = t_1;
	elseif (t <= -8.2e-75)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (t <= 6.2e+69)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 2.4e+114)
		tmp = Float64(i * Float64(Float64(-j) * Float64(t * y5)));
	elseif (t <= 3.9e+183)
		tmp = Float64(x * Float64(c * Float64(y0 * 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 = b * (j * (t * y4));
	tmp = 0.0;
	if (t <= -1.85e+26)
		tmp = t_1;
	elseif (t <= -8.2e-75)
		tmp = i * (j * (x * y1));
	elseif (t <= 6.2e+69)
		tmp = a * ((x * y) * b);
	elseif (t <= 2.4e+114)
		tmp = i * (-j * (t * y5));
	elseif (t <= 3.9e+183)
		tmp = x * (c * (y0 * 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[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.85e+26], t$95$1, If[LessEqual[t, -8.2e-75], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.2e+69], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.4e+114], N[(i * N[((-j) * N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.9e+183], N[(x * N[(c * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -1.84999999999999994e26 or 3.8999999999999999e183 < t

   1. Initial program 31.3%

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

   3. Taylor expanded in j around inf 38.0%

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

   4. Taylor expanded in t around inf 44.1%

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

   5. Taylor expanded in b around inf 48.7%

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

   if -1.84999999999999994e26 < t < -8.20000000000000005e-75

   1. Initial program 21.4%

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

   3. Taylor expanded in x around inf 50.1%

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

      1. fma-define 50.1%

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

      2. fma-neg 50.1%

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

   5. Simplified 50.1%

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

   6. Taylor expanded in i around -inf 51.3%

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

      1. associate-*r* 51.3%

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

      2. neg-mul-1 51.3%

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

   8. Simplified 51.3%

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

   9. Taylor expanded in c around 0 44.3%

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

   if -8.20000000000000005e-75 < t < 6.1999999999999997e69

   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. Add Preprocessing

   3. Taylor expanded in b around inf 36.8%

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

   4. Taylor expanded in a around inf 27.3%

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

   5. Taylor expanded in x around inf 25.2%

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

      1. *-commutative 25.2%

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

   7. Simplified 25.2%

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

   if 6.1999999999999997e69 < t < 2.4e114

   1. Initial program 36.4%

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

   3. Taylor expanded in j around inf 37.0%

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

   4. Taylor expanded in t around inf 56.3%

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

   5. Taylor expanded in b around 0 47.4%

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

      1. associate-*r* 47.4%

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

      2. neg-mul-1 47.4%

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

      3. *-commutative 47.4%

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

   7. Simplified 47.4%

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

   if 2.4e114 < t < 3.8999999999999999e183

   1. Initial program 21.4%

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

   3. Taylor expanded in x around inf 43.6%

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

      1. fma-define 43.6%

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

      2. fma-neg 43.6%

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

   5. Simplified 43.6%

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

   6. Taylor expanded in y2 around inf 37.1%

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

   7. Taylor expanded in c around inf 58.0%

      \[\leadsto x \cdot \color{blue}{\left(c \cdot \left(y0 \cdot y2\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 36.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.85 \cdot 10^{+26}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -8.2 \cdot 10^{-75}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+69}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{+114}:\\ \;\;\;\;i \cdot \left(\left(-j\right) \cdot \left(t \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 3.9 \cdot 10^{+183}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 30: 22.0% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -2.5 \cdot 10^{+26}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -2.6 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-25}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 3.3 \cdot 10^{+158}:\\ \;\;\;\;i \cdot \left(\left(x \cdot y\right) \cdot \left(-c\right)\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{+244}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= t -2.5e+26)
     t_1
     (if (<= t -2.6e-73)
       (* i (* j (* x y1)))
       (if (<= t 1.45e-25)
         (* a (* (* x y) b))
         (if (<= t 3.3e+158)
           (* i (* (* x y) (- c)))
           (if (<= t 1.25e+244) (* y2 (* a (* t y5))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (t <= -2.5e+26) {
		tmp = t_1;
	} else if (t <= -2.6e-73) {
		tmp = i * (j * (x * y1));
	} else if (t <= 1.45e-25) {
		tmp = a * ((x * y) * b);
	} else if (t <= 3.3e+158) {
		tmp = i * ((x * y) * -c);
	} else if (t <= 1.25e+244) {
		tmp = y2 * (a * (t * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (j * (t * y4))
    if (t <= (-2.5d+26)) then
        tmp = t_1
    else if (t <= (-2.6d-73)) then
        tmp = i * (j * (x * y1))
    else if (t <= 1.45d-25) then
        tmp = a * ((x * y) * b)
    else if (t <= 3.3d+158) then
        tmp = i * ((x * y) * -c)
    else if (t <= 1.25d+244) then
        tmp = y2 * (a * (t * y5))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (t <= -2.5e+26) {
		tmp = t_1;
	} else if (t <= -2.6e-73) {
		tmp = i * (j * (x * y1));
	} else if (t <= 1.45e-25) {
		tmp = a * ((x * y) * b);
	} else if (t <= 3.3e+158) {
		tmp = i * ((x * y) * -c);
	} else if (t <= 1.25e+244) {
		tmp = y2 * (a * (t * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (j * (t * y4))
	tmp = 0
	if t <= -2.5e+26:
		tmp = t_1
	elif t <= -2.6e-73:
		tmp = i * (j * (x * y1))
	elif t <= 1.45e-25:
		tmp = a * ((x * y) * b)
	elif t <= 3.3e+158:
		tmp = i * ((x * y) * -c)
	elif t <= 1.25e+244:
		tmp = y2 * (a * (t * y5))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (t <= -2.5e+26)
		tmp = t_1;
	elseif (t <= -2.6e-73)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (t <= 1.45e-25)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 3.3e+158)
		tmp = Float64(i * Float64(Float64(x * y) * Float64(-c)));
	elseif (t <= 1.25e+244)
		tmp = Float64(y2 * Float64(a * Float64(t * y5)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (j * (t * y4));
	tmp = 0.0;
	if (t <= -2.5e+26)
		tmp = t_1;
	elseif (t <= -2.6e-73)
		tmp = i * (j * (x * y1));
	elseif (t <= 1.45e-25)
		tmp = a * ((x * y) * b);
	elseif (t <= 3.3e+158)
		tmp = i * ((x * y) * -c);
	elseif (t <= 1.25e+244)
		tmp = y2 * (a * (t * y5));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.5e+26], t$95$1, If[LessEqual[t, -2.6e-73], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.45e-25], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.3e+158], N[(i * N[(N[(x * y), $MachinePrecision] * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.25e+244], N[(y2 * N[(a * N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -2.5e26 or 1.25000000000000006e244 < t

   1. Initial program 26.8%

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

   3. Taylor expanded in j around inf 36.4%

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

   4. Taylor expanded in t around inf 44.0%

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

   5. Taylor expanded in b around inf 49.8%

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

   if -2.5e26 < t < -2.6000000000000001e-73

   1. Initial program 21.4%

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

   3. Taylor expanded in x around inf 50.1%

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

      1. fma-define 50.1%

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

      2. fma-neg 50.1%

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

   5. Simplified 50.1%

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

   6. Taylor expanded in i around -inf 51.3%

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

      1. associate-*r* 51.3%

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

      2. neg-mul-1 51.3%

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

   8. Simplified 51.3%

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

   9. Taylor expanded in c around 0 44.3%

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

   if -2.6000000000000001e-73 < t < 1.45e-25

   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. Add Preprocessing

   3. Taylor expanded in b around inf 36.5%

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

   4. Taylor expanded in a around inf 27.0%

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

   5. Taylor expanded in x around inf 25.4%

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

      1. *-commutative 25.4%

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

   7. Simplified 25.4%

      \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

   if 1.45e-25 < t < 3.30000000000000017e158

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 24.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 24.5%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 27.8%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 27.8%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in i around -inf 30.8%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 30.8%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 30.8%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   8. Simplified 30.8%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   9. Taylor expanded in c around inf 34.3%

      \[\leadsto \left(-i\right) \cdot \color{blue}{\left(c \cdot \left(x \cdot y\right)\right)} \]

   if 3.30000000000000017e158 < t < 1.25000000000000006e244

   1. Initial program 47.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 47.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 53.0%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 53.0%

         \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

   6. Simplified 53.0%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

   7. Taylor expanded in y5 around inf 53.3%

      \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(t \cdot y5\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 53.3%

         \[\leadsto y2 \cdot \left(a \cdot \color{blue}{\left(y5 \cdot t\right)}\right) \]

   9. Simplified 53.3%

      \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(y5 \cdot t\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 36.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.5 \cdot 10^{+26}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -2.6 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-25}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 3.3 \cdot 10^{+158}:\\ \;\;\;\;i \cdot \left(\left(x \cdot y\right) \cdot \left(-c\right)\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{+244}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 31: 22.1% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -2.3 \cdot 10^{+25}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{+69}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{+137}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{+173}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= t -2.3e+25)
     t_1
     (if (<= t -5.2e-73)
       (* i (* j (* x y1)))
       (if (<= t 2.5e+69)
         (* a (* (* x y) b))
         (if (<= t 2.5e+137)
           (* j (* t (* i (- y5))))
           (if (<= t 3.7e+173) (* x (* c (* y0 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 = b * (j * (t * y4));
	double tmp;
	if (t <= -2.3e+25) {
		tmp = t_1;
	} else if (t <= -5.2e-73) {
		tmp = i * (j * (x * y1));
	} else if (t <= 2.5e+69) {
		tmp = a * ((x * y) * b);
	} else if (t <= 2.5e+137) {
		tmp = j * (t * (i * -y5));
	} else if (t <= 3.7e+173) {
		tmp = x * (c * (y0 * 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) :: tmp
    t_1 = b * (j * (t * y4))
    if (t <= (-2.3d+25)) then
        tmp = t_1
    else if (t <= (-5.2d-73)) then
        tmp = i * (j * (x * y1))
    else if (t <= 2.5d+69) then
        tmp = a * ((x * y) * b)
    else if (t <= 2.5d+137) then
        tmp = j * (t * (i * -y5))
    else if (t <= 3.7d+173) then
        tmp = x * (c * (y0 * 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 = b * (j * (t * y4));
	double tmp;
	if (t <= -2.3e+25) {
		tmp = t_1;
	} else if (t <= -5.2e-73) {
		tmp = i * (j * (x * y1));
	} else if (t <= 2.5e+69) {
		tmp = a * ((x * y) * b);
	} else if (t <= 2.5e+137) {
		tmp = j * (t * (i * -y5));
	} else if (t <= 3.7e+173) {
		tmp = x * (c * (y0 * 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 = b * (j * (t * y4))
	tmp = 0
	if t <= -2.3e+25:
		tmp = t_1
	elif t <= -5.2e-73:
		tmp = i * (j * (x * y1))
	elif t <= 2.5e+69:
		tmp = a * ((x * y) * b)
	elif t <= 2.5e+137:
		tmp = j * (t * (i * -y5))
	elif t <= 3.7e+173:
		tmp = x * (c * (y0 * 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(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (t <= -2.3e+25)
		tmp = t_1;
	elseif (t <= -5.2e-73)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (t <= 2.5e+69)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 2.5e+137)
		tmp = Float64(j * Float64(t * Float64(i * Float64(-y5))));
	elseif (t <= 3.7e+173)
		tmp = Float64(x * Float64(c * Float64(y0 * 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 = b * (j * (t * y4));
	tmp = 0.0;
	if (t <= -2.3e+25)
		tmp = t_1;
	elseif (t <= -5.2e-73)
		tmp = i * (j * (x * y1));
	elseif (t <= 2.5e+69)
		tmp = a * ((x * y) * b);
	elseif (t <= 2.5e+137)
		tmp = j * (t * (i * -y5));
	elseif (t <= 3.7e+173)
		tmp = x * (c * (y0 * 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[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.3e+25], t$95$1, If[LessEqual[t, -5.2e-73], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.5e+69], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.5e+137], N[(j * N[(t * N[(i * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.7e+173], N[(x * N[(c * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -2.2999999999999998e25 or 3.69999999999999986e173 < t

   1. Initial program 31.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 38.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 43.1%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 47.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -2.2999999999999998e25 < t < -5.2000000000000002e-73

   1. Initial program 21.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 50.1%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 50.1%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 50.1%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 50.1%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in i around -inf 51.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 51.3%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 51.3%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   8. Simplified 51.3%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   9. Taylor expanded in c around 0 44.3%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if -5.2000000000000002e-73 < t < 2.50000000000000018e69

   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. Add Preprocessing

   3. Taylor expanded in b around inf 36.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 27.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 25.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 25.2%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

   7. Simplified 25.2%

      \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

   if 2.50000000000000018e69 < t < 2.5000000000000001e137

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 38.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 46.7%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around 0 33.8%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y5\right)\right)}\right) \]
   6. Step-by-step derivation

      1. mul-1-neg 33.8%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-i \cdot y5\right)}\right) \]

      2. distribute-lft-neg-out 33.8%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(\left(-i\right) \cdot y5\right)}\right) \]

      3. *-commutative 33.8%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   7. Simplified 33.8%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   if 2.5000000000000001e137 < t < 3.69999999999999986e173

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 58.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 58.5%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 58.5%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 58.5%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in y2 around inf 45.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   7. Taylor expanded in c around inf 72.5%

      \[\leadsto x \cdot \color{blue}{\left(c \cdot \left(y0 \cdot y2\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 35.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.3 \cdot 10^{+25}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{+69}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{+137}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{+173}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 32: 26.8% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ t_2 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y4 \leq -1.02 \cdot 10^{+165}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y4 \leq -9.5 \cdot 10^{-36}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y4 \leq 1.7 \cdot 10^{-120}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y4 \leq 1.02 \cdot 10^{+195}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (- (* y a) (* j y0)))))
        (t_2 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y4 -1.02e+165)
     t_2
     (if (<= y4 -9.5e-36)
       t_1
       (if (<= y4 1.7e-120)
         t_2
         (if (<= y4 1.02e+195) t_1 (* b (* 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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y4 <= -1.02e+165) {
		tmp = t_2;
	} else if (y4 <= -9.5e-36) {
		tmp = t_1;
	} else if (y4 <= 1.7e-120) {
		tmp = t_2;
	} else if (y4 <= 1.02e+195) {
		tmp = t_1;
	} else {
		tmp = b * (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) :: t_2
    real(8) :: tmp
    t_1 = b * (x * ((y * a) - (j * y0)))
    t_2 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y4 <= (-1.02d+165)) then
        tmp = t_2
    else if (y4 <= (-9.5d-36)) then
        tmp = t_1
    else if (y4 <= 1.7d-120) then
        tmp = t_2
    else if (y4 <= 1.02d+195) then
        tmp = t_1
    else
        tmp = b * (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 = b * (x * ((y * a) - (j * y0)));
	double t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y4 <= -1.02e+165) {
		tmp = t_2;
	} else if (y4 <= -9.5e-36) {
		tmp = t_1;
	} else if (y4 <= 1.7e-120) {
		tmp = t_2;
	} else if (y4 <= 1.02e+195) {
		tmp = t_1;
	} else {
		tmp = b * (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 = b * (x * ((y * a) - (j * y0)))
	t_2 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y4 <= -1.02e+165:
		tmp = t_2
	elif y4 <= -9.5e-36:
		tmp = t_1
	elif y4 <= 1.7e-120:
		tmp = t_2
	elif y4 <= 1.02e+195:
		tmp = t_1
	else:
		tmp = b * (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(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))))
	t_2 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y4 <= -1.02e+165)
		tmp = t_2;
	elseif (y4 <= -9.5e-36)
		tmp = t_1;
	elseif (y4 <= 1.7e-120)
		tmp = t_2;
	elseif (y4 <= 1.02e+195)
		tmp = t_1;
	else
		tmp = Float64(b * 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 = b * (x * ((y * a) - (j * y0)));
	t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y4 <= -1.02e+165)
		tmp = t_2;
	elseif (y4 <= -9.5e-36)
		tmp = t_1;
	elseif (y4 <= 1.7e-120)
		tmp = t_2;
	elseif (y4 <= 1.02e+195)
		tmp = t_1;
	else
		tmp = b * (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[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.02e+165], t$95$2, If[LessEqual[y4, -9.5e-36], t$95$1, If[LessEqual[y4, 1.7e-120], t$95$2, If[LessEqual[y4, 1.02e+195], t$95$1, N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 3 regimes

2. if y4 < -1.02000000000000003e165 or -9.5000000000000003e-36 < y4 < 1.70000000000000005e-120

   1. Initial program 34.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 37.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 38.7%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5 - b \cdot x\right)\right)} \]

   if -1.02000000000000003e165 < y4 < -9.5000000000000003e-36 or 1.70000000000000005e-120 < y4 < 1.02e195

   1. Initial program 29.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 35.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 37.9%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 38.8%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 38.8%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in b around inf 45.7%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]

   if 1.02e195 < y4

   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. Add Preprocessing

   3. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 48.8%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 42.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.02 \cdot 10^{+165}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq -9.5 \cdot 10^{-36}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.7 \cdot 10^{-120}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 1.02 \cdot 10^{+195}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 33: 30.5% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;y0 \leq -0.046:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq -4.2 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -9.8 \cdot 10^{-216}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 3.3 \cdot 10^{-44}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= y0 -0.046)
     t_1
     (if (<= y0 -4.2e-104)
       (* j (* t (* i (- y5))))
       (if (<= y0 -9.8e-216)
         (* b (* j (* t y4)))
         (if (<= y0 3.3e-44) (* a (* b (- (* x y) (* z t)))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (y0 <= -0.046) {
		tmp = t_1;
	} else if (y0 <= -4.2e-104) {
		tmp = j * (t * (i * -y5));
	} else if (y0 <= -9.8e-216) {
		tmp = b * (j * (t * y4));
	} else if (y0 <= 3.3e-44) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (y0 * ((z * k) - (x * j)))
    if (y0 <= (-0.046d0)) then
        tmp = t_1
    else if (y0 <= (-4.2d-104)) then
        tmp = j * (t * (i * -y5))
    else if (y0 <= (-9.8d-216)) then
        tmp = b * (j * (t * y4))
    else if (y0 <= 3.3d-44) then
        tmp = a * (b * ((x * y) - (z * t)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (y0 <= -0.046) {
		tmp = t_1;
	} else if (y0 <= -4.2e-104) {
		tmp = j * (t * (i * -y5));
	} else if (y0 <= -9.8e-216) {
		tmp = b * (j * (t * y4));
	} else if (y0 <= 3.3e-44) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if y0 <= -0.046:
		tmp = t_1
	elif y0 <= -4.2e-104:
		tmp = j * (t * (i * -y5))
	elif y0 <= -9.8e-216:
		tmp = b * (j * (t * y4))
	elif y0 <= 3.3e-44:
		tmp = a * (b * ((x * y) - (z * t)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (y0 <= -0.046)
		tmp = t_1;
	elseif (y0 <= -4.2e-104)
		tmp = Float64(j * Float64(t * Float64(i * Float64(-y5))));
	elseif (y0 <= -9.8e-216)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (y0 <= 3.3e-44)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (y0 <= -0.046)
		tmp = t_1;
	elseif (y0 <= -4.2e-104)
		tmp = j * (t * (i * -y5));
	elseif (y0 <= -9.8e-216)
		tmp = b * (j * (t * y4));
	elseif (y0 <= 3.3e-44)
		tmp = a * (b * ((x * y) - (z * t)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -0.046], t$95$1, If[LessEqual[y0, -4.2e-104], N[(j * N[(t * N[(i * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -9.8e-216], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3.3e-44], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -0.045999999999999999 or 3.30000000000000006e-44 < y0

   1. Initial program 27.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 39.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 42.9%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if -0.045999999999999999 < y0 < -4.19999999999999997e-104

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 51.3%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around 0 45.7%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y5\right)\right)}\right) \]
   6. Step-by-step derivation

      1. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-i \cdot y5\right)}\right) \]

      2. distribute-lft-neg-out 45.7%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(\left(-i\right) \cdot y5\right)}\right) \]

      3. *-commutative 45.7%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   7. Simplified 45.7%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   if -4.19999999999999997e-104 < y0 < -9.8000000000000003e-216

   1. Initial program 23.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 27.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 32.6%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 37.5%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -9.8000000000000003e-216 < y0 < 3.30000000000000006e-44

   1. Initial program 42.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 35.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 35.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 40.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -0.046:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq -4.2 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -9.8 \cdot 10^{-216}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 3.3 \cdot 10^{-44}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 34: 26.3% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -2.2 \cdot 10^{-113}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 5.6 \cdot 10^{+91}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y2 \leq 1.05 \cdot 10^{+181}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.15e+112)
   (* a (* t (* y2 y5)))
   (if (<= y2 -2.2e-113)
     (* y2 (* t (* c (- y4))))
     (if (<= y2 5.6e+91)
       (* a (* b (- (* x y) (* z t))))
       (if (<= y2 1.05e+181)
         (* b (* j (* t y4)))
         (* c (* t (* y2 (- 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 (y2 <= -1.15e+112) {
		tmp = a * (t * (y2 * y5));
	} else if (y2 <= -2.2e-113) {
		tmp = y2 * (t * (c * -y4));
	} else if (y2 <= 5.6e+91) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y2 <= 1.05e+181) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = c * (t * (y2 * -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 (y2 <= (-1.15d+112)) then
        tmp = a * (t * (y2 * y5))
    else if (y2 <= (-2.2d-113)) then
        tmp = y2 * (t * (c * -y4))
    else if (y2 <= 5.6d+91) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y2 <= 1.05d+181) then
        tmp = b * (j * (t * y4))
    else
        tmp = c * (t * (y2 * -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 (y2 <= -1.15e+112) {
		tmp = a * (t * (y2 * y5));
	} else if (y2 <= -2.2e-113) {
		tmp = y2 * (t * (c * -y4));
	} else if (y2 <= 5.6e+91) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y2 <= 1.05e+181) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = c * (t * (y2 * -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 y2 <= -1.15e+112:
		tmp = a * (t * (y2 * y5))
	elif y2 <= -2.2e-113:
		tmp = y2 * (t * (c * -y4))
	elif y2 <= 5.6e+91:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y2 <= 1.05e+181:
		tmp = b * (j * (t * y4))
	else:
		tmp = c * (t * (y2 * -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 (y2 <= -1.15e+112)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	elseif (y2 <= -2.2e-113)
		tmp = Float64(y2 * Float64(t * Float64(c * Float64(-y4))));
	elseif (y2 <= 5.6e+91)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y2 <= 1.05e+181)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(c * Float64(t * Float64(y2 * Float64(-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 (y2 <= -1.15e+112)
		tmp = a * (t * (y2 * y5));
	elseif (y2 <= -2.2e-113)
		tmp = y2 * (t * (c * -y4));
	elseif (y2 <= 5.6e+91)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y2 <= 1.05e+181)
		tmp = b * (j * (t * y4));
	else
		tmp = c * (t * (y2 * -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[y2, -1.15e+112], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -2.2e-113], N[(y2 * N[(t * N[(c * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5.6e+91], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 1.05e+181], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y2 < -1.15e112

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 47.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 40.0%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 40.0%

         \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

   6. Simplified 40.0%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

   7. Taylor expanded in y5 around inf 45.7%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 45.7%

         \[\leadsto a \cdot \left(t \cdot \color{blue}{\left(y5 \cdot y2\right)}\right) \]

   9. Simplified 45.7%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y5 \cdot y2\right)\right)} \]

   if -1.15e112 < y2 < -2.20000000000000004e-113

   1. Initial program 37.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 38.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 34.7%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 34.7%

         \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

   6. Simplified 34.7%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

   7. Taylor expanded in y5 around 0 30.2%

      \[\leadsto y2 \cdot \left(t \cdot \color{blue}{\left(-1 \cdot \left(c \cdot y4\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 30.2%

         \[\leadsto y2 \cdot \left(t \cdot \color{blue}{\left(-c \cdot y4\right)}\right) \]

      2. distribute-lft-neg-in 30.2%

         \[\leadsto y2 \cdot \left(t \cdot \color{blue}{\left(\left(-c\right) \cdot y4\right)}\right) \]

      3. *-commutative 30.2%

         \[\leadsto y2 \cdot \left(t \cdot \color{blue}{\left(y4 \cdot \left(-c\right)\right)}\right) \]

   9. Simplified 30.2%

      \[\leadsto y2 \cdot \left(t \cdot \color{blue}{\left(y4 \cdot \left(-c\right)\right)}\right) \]

   if -2.20000000000000004e-113 < y2 < 5.5999999999999997e91

   1. Initial program 35.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 36.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 37.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if 5.5999999999999997e91 < y2 < 1.04999999999999999e181

   1. Initial program 42.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 47.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 33.3%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 48.3%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if 1.04999999999999999e181 < y2

   1. Initial program 19.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 43.9%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.9%

         \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

   6. Simplified 43.9%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

   7. Taylor expanded in y5 around 0 39.1%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 39.1%

         \[\leadsto \color{blue}{\left(-1 \cdot c\right) \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. neg-mul-1 39.1%

         \[\leadsto \color{blue}{\left(-c\right)} \cdot \left(t \cdot \left(y2 \cdot y4\right)\right) \]

   9. Simplified 39.1%

      \[\leadsto \color{blue}{\left(-c\right) \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 38.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{elif}\;y2 \leq -2.2 \cdot 10^{-113}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(c \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 5.6 \cdot 10^{+91}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y2 \leq 1.05 \cdot 10^{+181}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 35: 29.7% accurate, 3.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -2.2 \cdot 10^{-79}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y3 \leq 1.32 \cdot 10^{+20}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y3 \leq 1.42 \cdot 10^{+142}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -2.2e-79)
   (* j (* y0 (- (* y3 y5) (* x b))))
   (if (<= y3 1.32e+20)
     (* b (* x (- (* y a) (* j y0))))
     (if (<= y3 1.42e+142)
       (* x (* y (- (* a b) (* c i))))
       (* y1 (* z (- (* a y3) (* i k))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.2e-79) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (y3 <= 1.32e+20) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y3 <= 1.42e+142) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y3 <= (-2.2d-79)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (y3 <= 1.32d+20) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y3 <= 1.42d+142) then
        tmp = x * (y * ((a * b) - (c * i)))
    else
        tmp = y1 * (z * ((a * y3) - (i * k)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -2.2e-79) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (y3 <= 1.32e+20) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y3 <= 1.42e+142) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	}
	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 <= -2.2e-79:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif y3 <= 1.32e+20:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y3 <= 1.42e+142:
		tmp = x * (y * ((a * b) - (c * i)))
	else:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	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 <= -2.2e-79)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (y3 <= 1.32e+20)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y3 <= 1.42e+142)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	else
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y3 <= -2.2e-79)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (y3 <= 1.32e+20)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y3 <= 1.42e+142)
		tmp = x * (y * ((a * b) - (c * i)));
	else
		tmp = y1 * (z * ((a * y3) - (i * k)));
	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, -2.2e-79], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.32e+20], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.42e+142], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y3 < -2.1999999999999999e-79

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 45.4%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5 - b \cdot x\right)\right)} \]

   if -2.1999999999999999e-79 < y3 < 1.32e20

   1. Initial program 33.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 41.8%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 41.8%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 41.8%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 41.8%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in b around inf 37.5%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]

   if 1.32e20 < y3 < 1.42e142

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 42.6%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 42.6%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 42.6%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 42.6%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in y around inf 53.0%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 1.42e142 < y3

   1. Initial program 19.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 33.4%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in z around inf 53.8%

      \[\leadsto \color{blue}{y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 44.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -2.2 \cdot 10^{-79}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y3 \leq 1.32 \cdot 10^{+20}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y3 \leq 1.42 \cdot 10^{+142}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 36: 20.4% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -8.2 \cdot 10^{+169}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq -5.1 \cdot 10^{-172}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 1.35 \cdot 10^{+194}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -8.2e+169)
   (* i (* j (* x y1)))
   (if (<= x -5.1e-172)
     (* y2 (* a (* t y5)))
     (if (<= x 1.35e+194) (* b (* j (* t y4))) (* c (* x (* y0 y2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -8.2e+169) {
		tmp = i * (j * (x * y1));
	} else if (x <= -5.1e-172) {
		tmp = y2 * (a * (t * y5));
	} else if (x <= 1.35e+194) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = c * (x * (y0 * y2));
	}
	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 <= (-8.2d+169)) then
        tmp = i * (j * (x * y1))
    else if (x <= (-5.1d-172)) then
        tmp = y2 * (a * (t * y5))
    else if (x <= 1.35d+194) then
        tmp = b * (j * (t * y4))
    else
        tmp = c * (x * (y0 * y2))
    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 <= -8.2e+169) {
		tmp = i * (j * (x * y1));
	} else if (x <= -5.1e-172) {
		tmp = y2 * (a * (t * y5));
	} else if (x <= 1.35e+194) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = c * (x * (y0 * y2));
	}
	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 <= -8.2e+169:
		tmp = i * (j * (x * y1))
	elif x <= -5.1e-172:
		tmp = y2 * (a * (t * y5))
	elif x <= 1.35e+194:
		tmp = b * (j * (t * y4))
	else:
		tmp = c * (x * (y0 * y2))
	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 <= -8.2e+169)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (x <= -5.1e-172)
		tmp = Float64(y2 * Float64(a * Float64(t * y5)));
	elseif (x <= 1.35e+194)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	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 <= -8.2e+169)
		tmp = i * (j * (x * y1));
	elseif (x <= -5.1e-172)
		tmp = y2 * (a * (t * y5));
	elseif (x <= 1.35e+194)
		tmp = b * (j * (t * y4));
	else
		tmp = c * (x * (y0 * y2));
	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, -8.2e+169], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -5.1e-172], N[(y2 * N[(a * N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.35e+194], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if x < -8.2000000000000006e169

   1. Initial program 20.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 61.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 61.7%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 64.7%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 64.7%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in i around -inf 53.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 53.7%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 53.7%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   8. Simplified 53.7%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   9. Taylor expanded in c around 0 41.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if -8.2000000000000006e169 < x < -5.0999999999999998e-172

   1. Initial program 24.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 34.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 35.9%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 35.9%

         \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

   6. Simplified 35.9%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

   7. Taylor expanded in y5 around inf 30.5%

      \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(t \cdot y5\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 30.5%

         \[\leadsto y2 \cdot \left(a \cdot \color{blue}{\left(y5 \cdot t\right)}\right) \]

   9. Simplified 30.5%

      \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(y5 \cdot t\right)\right)} \]

   if -5.0999999999999998e-172 < x < 1.3500000000000001e194

   1. Initial program 44.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 41.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 27.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 25.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if 1.3500000000000001e194 < x

   1. Initial program 11.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 61.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 65.4%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 69.2%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 69.2%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in y2 around inf 43.5%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   7. Taylor expanded in c around inf 36.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 29.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -8.2 \cdot 10^{+169}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq -5.1 \cdot 10^{-172}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(t \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 1.35 \cdot 10^{+194}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 37: 21.6% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -2.85 \cdot 10^{+22}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -9.5 \cdot 10^{-257}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 3.9 \cdot 10^{+183}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= t -2.85e+22)
     t_1
     (if (<= t -9.5e-257)
       (* i (* j (* x y1)))
       (if (<= t 3.9e+183) (* c (* x (* y0 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 = b * (j * (t * y4));
	double tmp;
	if (t <= -2.85e+22) {
		tmp = t_1;
	} else if (t <= -9.5e-257) {
		tmp = i * (j * (x * y1));
	} else if (t <= 3.9e+183) {
		tmp = c * (x * (y0 * 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) :: tmp
    t_1 = b * (j * (t * y4))
    if (t <= (-2.85d+22)) then
        tmp = t_1
    else if (t <= (-9.5d-257)) then
        tmp = i * (j * (x * y1))
    else if (t <= 3.9d+183) then
        tmp = c * (x * (y0 * 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 = b * (j * (t * y4));
	double tmp;
	if (t <= -2.85e+22) {
		tmp = t_1;
	} else if (t <= -9.5e-257) {
		tmp = i * (j * (x * y1));
	} else if (t <= 3.9e+183) {
		tmp = c * (x * (y0 * 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 = b * (j * (t * y4))
	tmp = 0
	if t <= -2.85e+22:
		tmp = t_1
	elif t <= -9.5e-257:
		tmp = i * (j * (x * y1))
	elif t <= 3.9e+183:
		tmp = c * (x * (y0 * 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(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (t <= -2.85e+22)
		tmp = t_1;
	elseif (t <= -9.5e-257)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (t <= 3.9e+183)
		tmp = Float64(c * Float64(x * Float64(y0 * 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 = b * (j * (t * y4));
	tmp = 0.0;
	if (t <= -2.85e+22)
		tmp = t_1;
	elseif (t <= -9.5e-257)
		tmp = i * (j * (x * y1));
	elseif (t <= 3.9e+183)
		tmp = c * (x * (y0 * 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[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.85e+22], t$95$1, If[LessEqual[t, -9.5e-257], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.9e+183], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if t < -2.8499999999999999e22 or 3.8999999999999999e183 < t

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 38.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 44.1%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 48.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -2.8499999999999999e22 < t < -9.49999999999999941e-257

   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. Add Preprocessing

   3. Taylor expanded in x around inf 47.9%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 47.9%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 47.9%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 47.9%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in i around -inf 26.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 26.7%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 26.7%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   8. Simplified 26.7%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   9. Taylor expanded in c around 0 21.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if -9.49999999999999941e-257 < t < 3.8999999999999999e183

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 39.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 40.7%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 41.6%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 41.6%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in y2 around inf 21.9%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   7. Taylor expanded in c around inf 20.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 38: 21.6% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3.3 \cdot 10^{-50} \lor \neg \left(t \leq 3.9 \cdot 10^{+183}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= t -3.3e-50) (not (<= t 3.9e+183)))
   (* b (* j (* t y4)))
   (* c (* x (* y0 y2)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((t <= -3.3e-50) || !(t <= 3.9e+183)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = c * (x * (y0 * y2));
	}
	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 ((t <= (-3.3d-50)) .or. (.not. (t <= 3.9d+183))) then
        tmp = b * (j * (t * y4))
    else
        tmp = c * (x * (y0 * y2))
    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 ((t <= -3.3e-50) || !(t <= 3.9e+183)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = c * (x * (y0 * y2));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (t <= -3.3e-50) or not (t <= 3.9e+183):
		tmp = b * (j * (t * y4))
	else:
		tmp = c * (x * (y0 * y2))
	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 ((t <= -3.3e-50) || !(t <= 3.9e+183))
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	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 ((t <= -3.3e-50) || ~((t <= 3.9e+183)))
		tmp = b * (j * (t * y4));
	else
		tmp = c * (x * (y0 * y2));
	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[t, -3.3e-50], N[Not[LessEqual[t, 3.9e+183]], $MachinePrecision]], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < -3.2999999999999998e-50 or 3.8999999999999999e183 < t

   1. Initial program 31.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 36.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 41.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 45.1%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -3.2999999999999998e-50 < t < 3.8999999999999999e183

   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. Add Preprocessing

   3. Taylor expanded in x around inf 41.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. fma-define 42.5%

         \[\leadsto x \cdot \left(\color{blue}{\mathsf{fma}\left(y, a \cdot b - c \cdot i, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. fma-neg 43.1%

         \[\leadsto x \cdot \left(\mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(a, b, -c \cdot i\right)}, y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

   5. Simplified 43.1%

      \[\leadsto \color{blue}{x \cdot \left(\mathsf{fma}\left(y, \mathsf{fma}\left(a, b, -c \cdot i\right), y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   6. Taylor expanded in y2 around inf 22.9%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   7. Taylor expanded in c around inf 17.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 27.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.3 \cdot 10^{-50} \lor \neg \left(t \leq 3.9 \cdot 10^{+183}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 39: 22.8% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y4 \leq -2.05 \cdot 10^{+32} \lor \neg \left(y4 \leq 9 \cdot 10^{+68}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= y4 -2.05e+32) (not (<= y4 9e+68)))
   (* b (* j (* t y4)))
   (* a (* t (* y2 y5)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((y4 <= -2.05e+32) || !(y4 <= 9e+68)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if ((y4 <= (-2.05d+32)) .or. (.not. (y4 <= 9d+68))) then
        tmp = b * (j * (t * y4))
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((y4 <= -2.05e+32) || !(y4 <= 9e+68)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (y4 <= -2.05e+32) or not (y4 <= 9e+68):
		tmp = b * (j * (t * y4))
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if ((y4 <= -2.05e+32) || !(y4 <= 9e+68))
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if ((y4 <= -2.05e+32) || ~((y4 <= 9e+68)))
		tmp = b * (j * (t * y4));
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[Or[LessEqual[y4, -2.05e+32], N[Not[LessEqual[y4, 9e+68]], $MachinePrecision]], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y4 < -2.0499999999999999e32 or 9.0000000000000007e68 < y4

   1. Initial program 30.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 37.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 32.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 33.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -2.0499999999999999e32 < y4 < 9.0000000000000007e68

   1. Initial program 33.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 36.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 23.5%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 23.5%

         \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

   6. Simplified 23.5%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

   7. Taylor expanded in y5 around inf 21.5%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 21.5%

         \[\leadsto a \cdot \left(t \cdot \color{blue}{\left(y5 \cdot y2\right)}\right) \]

   9. Simplified 21.5%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y5 \cdot y2\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 26.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -2.05 \cdot 10^{+32} \lor \neg \left(y4 \leq 9 \cdot 10^{+68}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 40: 17.5% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* t (* y2 y5))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (t * (y2 * y5));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = a * (t * (y2 * y5))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (t * (y2 * y5));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (t * (y2 * y5))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(t * Float64(y2 * y5)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (t * (y2 * y5));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 32.3%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
2. Add Preprocessing

3. Taylor expanded in y2 around inf 32.4%

   \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

4. Taylor expanded in t around inf 27.3%

   \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
5. Step-by-step derivation

   1. *-commutative 27.3%

      \[\leadsto y2 \cdot \left(t \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

6. Simplified 27.3%

   \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(y5 \cdot a - c \cdot y4\right)\right)} \]

7. Taylor expanded in y5 around inf 18.3%

   \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
8. Step-by-step derivation

   1. *-commutative 18.3%

      \[\leadsto a \cdot \left(t \cdot \color{blue}{\left(y5 \cdot y2\right)}\right) \]

9. Simplified 18.3%

   \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y5 \cdot y2\right)\right)} \]

10. Final simplification 18.3%

    \[\leadsto a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right) \]
11. Add Preprocessing

Developer target: 27.3% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t\_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t\_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t\_9\\ t_11 := t\_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t\_4 \cdot t\_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t\_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t\_3 \cdot t\_1 - t\_14\right)\right) + \left(t\_8 - \left(t\_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t\_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t\_13\right)\right) + \left(t\_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t\_10 - \left(y \cdot x - z \cdot t\right) \cdot t\_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t\_8 - \left(t\_11 - t\_6\right)\right) - \left(\frac{t\_3}{\frac{1}{t\_1}} - t\_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t\_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t\_2 - \left(t\_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t\_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t\_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t\_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t\_5\right) - t\_17 \cdot t\_1\right) + t\_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2024089 
(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

  :alt
  (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)))))