Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.4% → 40.6%

Time: 1.9min

Alternatives: 37

Speedup: 6.3×

• 88.9% 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: 30.4% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 40.6% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot y0 - a \cdot y1\\ t_2 := y2 \cdot t_1\\ t_3 := y0 \cdot y5 - y1 \cdot y4\\ t_4 := t \cdot j - y \cdot k\\ t_5 := y4 \cdot \left(\left(b \cdot t_4 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ t_6 := a \cdot b - c \cdot i\\ t_7 := i \cdot y1 - b \cdot y0\\ t_8 := j \cdot t_7\\ t_9 := x \cdot \left(\left(y \cdot t_6 + t_2\right) + t_8\right)\\ t_10 := x \cdot j - z \cdot k\\ \mathbf{if}\;y4 \leq -3.7 \cdot 10^{+182}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;y4 \leq -7.1 \cdot 10^{+143}:\\ \;\;\;\;x \cdot t_2\\ \mathbf{elif}\;y4 \leq -2.15 \cdot 10^{+71}:\\ \;\;\;\;y3 \cdot \left(c \cdot \left(y \cdot y4\right) - \left(c \cdot \left(z \cdot y0\right) - j \cdot t_3\right)\right)\\ \mathbf{elif}\;y4 \leq -1.25 \cdot 10^{-221}:\\ \;\;\;\;x \cdot \left(t_2 + t_8\right)\\ \mathbf{elif}\;y4 \leq -2.6 \cdot 10^{-286}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot t_3 + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot t_7\right)\\ \mathbf{elif}\;y4 \leq 7.2 \cdot 10^{-225}:\\ \;\;\;\;t_9\\ \mathbf{elif}\;y4 \leq 8.5 \cdot 10^{-193}:\\ \;\;\;\;i \cdot \left(y1 \cdot t_10 - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 \leq 14000000:\\ \;\;\;\;t_9\\ \mathbf{elif}\;y4 \leq 2 \cdot 10^{+75}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) - b \cdot t_10\right)\\ \mathbf{elif}\;y4 \leq 1.05 \cdot 10^{+181}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(t \cdot t_6 + y3 \cdot t_1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_5\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* c y0) (* a y1)))
        (t_2 (* y2 t_1))
        (t_3 (- (* y0 y5) (* y1 y4)))
        (t_4 (- (* t j) (* y k)))
        (t_5
         (*
          y4
          (+
           (+ (* b t_4) (* y1 (- (* k y2) (* j y3))))
           (* c (- (* y y3) (* t y2))))))
        (t_6 (- (* a b) (* c i)))
        (t_7 (- (* i y1) (* b y0)))
        (t_8 (* j t_7))
        (t_9 (* x (+ (+ (* y t_6) t_2) t_8)))
        (t_10 (- (* x j) (* z k))))
   (if (<= y4 -3.7e+182)
     t_5
     (if (<= y4 -7.1e+143)
       (* x t_2)
       (if (<= y4 -2.15e+71)
         (* y3 (- (* c (* y y4)) (- (* c (* z y0)) (* j t_3))))
         (if (<= y4 -1.25e-221)
           (* x (+ t_2 t_8))
           (if (<= y4 -2.6e-286)
             (* j (+ (+ (* y3 t_3) (* t (- (* b y4) (* i y5)))) (* x t_7)))
             (if (<= y4 7.2e-225)
               t_9
               (if (<= y4 8.5e-193)
                 (* i (- (* y1 t_10) (+ (* c (- (* x y) (* z t))) (* y5 t_4))))
                 (if (<= y4 14000000.0)
                   t_9
                   (if (<= y4 2e+75)
                     (*
                      y0
                      (-
                       (+
                        (* y5 (- (* j y3) (* k y2)))
                        (* c (- (* x y2) (* z y3))))
                       (* b t_10)))
                     (if (<= y4 1.05e+181)
                       (*
                        z
                        (-
                         (* k (- (* b y0) (* i y1)))
                         (+ (* t t_6) (* y3 t_1))))
                       t_5))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (c * y0) - (a * y1);
	double t_2 = y2 * t_1;
	double t_3 = (y0 * y5) - (y1 * y4);
	double t_4 = (t * j) - (y * k);
	double t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_6 = (a * b) - (c * i);
	double t_7 = (i * y1) - (b * y0);
	double t_8 = j * t_7;
	double t_9 = x * (((y * t_6) + t_2) + t_8);
	double t_10 = (x * j) - (z * k);
	double tmp;
	if (y4 <= -3.7e+182) {
		tmp = t_5;
	} else if (y4 <= -7.1e+143) {
		tmp = x * t_2;
	} else if (y4 <= -2.15e+71) {
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_3)));
	} else if (y4 <= -1.25e-221) {
		tmp = x * (t_2 + t_8);
	} else if (y4 <= -2.6e-286) {
		tmp = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_7));
	} else if (y4 <= 7.2e-225) {
		tmp = t_9;
	} else if (y4 <= 8.5e-193) {
		tmp = i * ((y1 * t_10) - ((c * ((x * y) - (z * t))) + (y5 * t_4)));
	} else if (y4 <= 14000000.0) {
		tmp = t_9;
	} else if (y4 <= 2e+75) {
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_10));
	} else if (y4 <= 1.05e+181) {
		tmp = z * ((k * ((b * y0) - (i * y1))) - ((t * t_6) + (y3 * t_1)));
	} else {
		tmp = t_5;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    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 = (c * y0) - (a * y1)
    t_2 = y2 * t_1
    t_3 = (y0 * y5) - (y1 * y4)
    t_4 = (t * j) - (y * k)
    t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    t_6 = (a * b) - (c * i)
    t_7 = (i * y1) - (b * y0)
    t_8 = j * t_7
    t_9 = x * (((y * t_6) + t_2) + t_8)
    t_10 = (x * j) - (z * k)
    if (y4 <= (-3.7d+182)) then
        tmp = t_5
    else if (y4 <= (-7.1d+143)) then
        tmp = x * t_2
    else if (y4 <= (-2.15d+71)) then
        tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_3)))
    else if (y4 <= (-1.25d-221)) then
        tmp = x * (t_2 + t_8)
    else if (y4 <= (-2.6d-286)) then
        tmp = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_7))
    else if (y4 <= 7.2d-225) then
        tmp = t_9
    else if (y4 <= 8.5d-193) then
        tmp = i * ((y1 * t_10) - ((c * ((x * y) - (z * t))) + (y5 * t_4)))
    else if (y4 <= 14000000.0d0) then
        tmp = t_9
    else if (y4 <= 2d+75) then
        tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_10))
    else if (y4 <= 1.05d+181) then
        tmp = z * ((k * ((b * y0) - (i * y1))) - ((t * t_6) + (y3 * t_1)))
    else
        tmp = t_5
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (c * y0) - (a * y1);
	double t_2 = y2 * t_1;
	double t_3 = (y0 * y5) - (y1 * y4);
	double t_4 = (t * j) - (y * k);
	double t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_6 = (a * b) - (c * i);
	double t_7 = (i * y1) - (b * y0);
	double t_8 = j * t_7;
	double t_9 = x * (((y * t_6) + t_2) + t_8);
	double t_10 = (x * j) - (z * k);
	double tmp;
	if (y4 <= -3.7e+182) {
		tmp = t_5;
	} else if (y4 <= -7.1e+143) {
		tmp = x * t_2;
	} else if (y4 <= -2.15e+71) {
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_3)));
	} else if (y4 <= -1.25e-221) {
		tmp = x * (t_2 + t_8);
	} else if (y4 <= -2.6e-286) {
		tmp = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_7));
	} else if (y4 <= 7.2e-225) {
		tmp = t_9;
	} else if (y4 <= 8.5e-193) {
		tmp = i * ((y1 * t_10) - ((c * ((x * y) - (z * t))) + (y5 * t_4)));
	} else if (y4 <= 14000000.0) {
		tmp = t_9;
	} else if (y4 <= 2e+75) {
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_10));
	} else if (y4 <= 1.05e+181) {
		tmp = z * ((k * ((b * y0) - (i * y1))) - ((t * t_6) + (y3 * t_1)));
	} else {
		tmp = t_5;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (c * y0) - (a * y1)
	t_2 = y2 * t_1
	t_3 = (y0 * y5) - (y1 * y4)
	t_4 = (t * j) - (y * k)
	t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	t_6 = (a * b) - (c * i)
	t_7 = (i * y1) - (b * y0)
	t_8 = j * t_7
	t_9 = x * (((y * t_6) + t_2) + t_8)
	t_10 = (x * j) - (z * k)
	tmp = 0
	if y4 <= -3.7e+182:
		tmp = t_5
	elif y4 <= -7.1e+143:
		tmp = x * t_2
	elif y4 <= -2.15e+71:
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_3)))
	elif y4 <= -1.25e-221:
		tmp = x * (t_2 + t_8)
	elif y4 <= -2.6e-286:
		tmp = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_7))
	elif y4 <= 7.2e-225:
		tmp = t_9
	elif y4 <= 8.5e-193:
		tmp = i * ((y1 * t_10) - ((c * ((x * y) - (z * t))) + (y5 * t_4)))
	elif y4 <= 14000000.0:
		tmp = t_9
	elif y4 <= 2e+75:
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_10))
	elif y4 <= 1.05e+181:
		tmp = z * ((k * ((b * y0) - (i * y1))) - ((t * t_6) + (y3 * t_1)))
	else:
		tmp = t_5
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(c * y0) - Float64(a * y1))
	t_2 = Float64(y2 * t_1)
	t_3 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_4 = Float64(Float64(t * j) - Float64(y * k))
	t_5 = Float64(y4 * Float64(Float64(Float64(b * t_4) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))))
	t_6 = Float64(Float64(a * b) - Float64(c * i))
	t_7 = Float64(Float64(i * y1) - Float64(b * y0))
	t_8 = Float64(j * t_7)
	t_9 = Float64(x * Float64(Float64(Float64(y * t_6) + t_2) + t_8))
	t_10 = Float64(Float64(x * j) - Float64(z * k))
	tmp = 0.0
	if (y4 <= -3.7e+182)
		tmp = t_5;
	elseif (y4 <= -7.1e+143)
		tmp = Float64(x * t_2);
	elseif (y4 <= -2.15e+71)
		tmp = Float64(y3 * Float64(Float64(c * Float64(y * y4)) - Float64(Float64(c * Float64(z * y0)) - Float64(j * t_3))));
	elseif (y4 <= -1.25e-221)
		tmp = Float64(x * Float64(t_2 + t_8));
	elseif (y4 <= -2.6e-286)
		tmp = Float64(j * Float64(Float64(Float64(y3 * t_3) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * t_7)));
	elseif (y4 <= 7.2e-225)
		tmp = t_9;
	elseif (y4 <= 8.5e-193)
		tmp = Float64(i * Float64(Float64(y1 * t_10) - Float64(Float64(c * Float64(Float64(x * y) - Float64(z * t))) + Float64(y5 * t_4))));
	elseif (y4 <= 14000000.0)
		tmp = t_9;
	elseif (y4 <= 2e+75)
		tmp = Float64(y0 * Float64(Float64(Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(c * Float64(Float64(x * y2) - Float64(z * y3)))) - Float64(b * t_10)));
	elseif (y4 <= 1.05e+181)
		tmp = Float64(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(Float64(t * t_6) + Float64(y3 * t_1))));
	else
		tmp = t_5;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (c * y0) - (a * y1);
	t_2 = y2 * t_1;
	t_3 = (y0 * y5) - (y1 * y4);
	t_4 = (t * j) - (y * k);
	t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	t_6 = (a * b) - (c * i);
	t_7 = (i * y1) - (b * y0);
	t_8 = j * t_7;
	t_9 = x * (((y * t_6) + t_2) + t_8);
	t_10 = (x * j) - (z * k);
	tmp = 0.0;
	if (y4 <= -3.7e+182)
		tmp = t_5;
	elseif (y4 <= -7.1e+143)
		tmp = x * t_2;
	elseif (y4 <= -2.15e+71)
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_3)));
	elseif (y4 <= -1.25e-221)
		tmp = x * (t_2 + t_8);
	elseif (y4 <= -2.6e-286)
		tmp = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_7));
	elseif (y4 <= 7.2e-225)
		tmp = t_9;
	elseif (y4 <= 8.5e-193)
		tmp = i * ((y1 * t_10) - ((c * ((x * y) - (z * t))) + (y5 * t_4)));
	elseif (y4 <= 14000000.0)
		tmp = t_9;
	elseif (y4 <= 2e+75)
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_10));
	elseif (y4 <= 1.05e+181)
		tmp = z * ((k * ((b * y0) - (i * y1))) - ((t * t_6) + (y3 * t_1)));
	else
		tmp = t_5;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y2 * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(y4 * N[(N[(N[(b * t$95$4), $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]}, Block[{t$95$6 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(j * t$95$7), $MachinePrecision]}, Block[{t$95$9 = N[(x * N[(N[(N[(y * t$95$6), $MachinePrecision] + t$95$2), $MachinePrecision] + t$95$8), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -3.7e+182], t$95$5, If[LessEqual[y4, -7.1e+143], N[(x * t$95$2), $MachinePrecision], If[LessEqual[y4, -2.15e+71], N[(y3 * N[(N[(c * N[(y * y4), $MachinePrecision]), $MachinePrecision] - N[(N[(c * N[(z * y0), $MachinePrecision]), $MachinePrecision] - N[(j * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.25e-221], N[(x * N[(t$95$2 + t$95$8), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -2.6e-286], N[(j * N[(N[(N[(y3 * t$95$3), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 7.2e-225], t$95$9, If[LessEqual[y4, 8.5e-193], N[(i * N[(N[(y1 * t$95$10), $MachinePrecision] - N[(N[(c * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 14000000.0], t$95$9, If[LessEqual[y4, 2e+75], N[(y0 * N[(N[(N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * t$95$10), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.05e+181], N[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t * t$95$6), $MachinePrecision] + N[(y3 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$5]]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y4 < -3.69999999999999977e182 or 1.04999999999999999e181 < y4

   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. Taylor expanded in y4 around inf 72.7%

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

   if -3.69999999999999977e182 < y4 < -7.10000000000000043e143

   1. Initial program 40.0%

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

   2. Taylor expanded in x around inf 60.2%

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

   3. Taylor expanded in y2 around inf 80.2%

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

   if -7.10000000000000043e143 < y4 < -2.14999999999999992e71

   1. Initial program 22.2%

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

   2. Taylor expanded in y3 around -inf 56.4%

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

   3. Taylor expanded in a around 0 57.1%

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

   if -2.14999999999999992e71 < y4 < -1.24999999999999999e-221

   1. Initial program 26.1%

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

   2. Taylor expanded in x around inf 58.4%

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

   3. Taylor expanded in y around 0 60.6%

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

      1. *-commutative 60.6%

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

      2. *-commutative 60.6%

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

   5. Simplified 60.6%

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

   if -1.24999999999999999e-221 < y4 < -2.6e-286

   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. Taylor expanded in j around inf 48.8%

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

   if -2.6e-286 < y4 < 7.20000000000000018e-225 or 8.50000000000000004e-193 < y4 < 1.4e7

   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. Taylor expanded in x around inf 57.7%

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

   if 7.20000000000000018e-225 < y4 < 8.50000000000000004e-193

   1. Initial program 53.5%

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

   2. Taylor expanded in i around -inf 61.6%

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

   if 1.4e7 < y4 < 1.99999999999999985e75

   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. Taylor expanded in y0 around inf 83.4%

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

   if 1.99999999999999985e75 < y4 < 1.04999999999999999e181

   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. Taylor expanded in z around -inf 62.0%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 62.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -3.7 \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}\;y4 \leq -7.1 \cdot 10^{+143}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq -2.15 \cdot 10^{+71}:\\ \;\;\;\;y3 \cdot \left(c \cdot \left(y \cdot y4\right) - \left(c \cdot \left(z \cdot y0\right) - j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\right)\\ \mathbf{elif}\;y4 \leq -1.25 \cdot 10^{-221}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq -2.6 \cdot 10^{-286}:\\ \;\;\;\;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}\;y4 \leq 7.2 \cdot 10^{-225}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 8.5 \cdot 10^{-193}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;y4 \leq 14000000:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 2 \cdot 10^{+75}:\\ \;\;\;\;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(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq 1.05 \cdot 10^{+181}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;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)\\ \end{array} \]

Alternative 2: 53.5% accurate, 0.5× speedup

Math

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

FPCore

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

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * b) - (c * i);
	double t_2 = (c * y0) - (a * y1);
	double t_3 = (((((t_1 * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (t_2 * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_3 <= ((double) INFINITY)) {
		tmp = t_3;
	} else {
		tmp = x * ((y * t_1) + (y2 * 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 = (a * b) - (c * i);
	double t_2 = (c * y0) - (a * y1);
	double t_3 = (((((t_1 * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (t_2 * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (t_3 <= Double.POSITIVE_INFINITY) {
		tmp = t_3;
	} else {
		tmp = x * ((y * t_1) + (y2 * 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 = (a * b) - (c * i)
	t_2 = (c * y0) - (a * y1)
	t_3 = (((((t_1 * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (t_2 * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if t_3 <= math.inf:
		tmp = t_3
	else:
		tmp = x * ((y * t_1) + (y2 * 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(a * b) - Float64(c * i))
	t_2 = Float64(Float64(c * y0) - Float64(a * y1))
	t_3 = Float64(Float64(Float64(Float64(Float64(Float64(t_1 * Float64(Float64(x * y) - Float64(z * t))) - Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(Float64(x * j) - Float64(z * k)))) + Float64(t_2 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(a * y5) - Float64(c * y4)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (t_3 <= Inf)
		tmp = t_3;
	else
		tmp = Float64(x * Float64(Float64(y * t_1) + Float64(y2 * 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 = (a * b) - (c * i);
	t_2 = (c * y0) - (a * y1);
	t_3 = (((((t_1 * ((x * y) - (z * t))) - (((b * y0) - (i * y1)) * ((x * j) - (z * k)))) + (t_2 * ((x * y2) - (z * y3)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (t_3 <= Inf)
		tmp = t_3;
	else
		tmp = x * ((y * t_1) + (y2 * 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[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(N[(N[(N[(t$95$1 * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$3, Infinity], t$95$3, N[(x * N[(N[(y * t$95$1), $MachinePrecision] + N[(y2 * 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 95.0%

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

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

   1. Initial program 0.0%

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

   2. Taylor expanded in x around inf 39.8%

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

   3. Taylor expanded in j around 0 40.4%

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

4. Final simplification 57.0%

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

Alternative 3: 36.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := c \cdot y0 - a \cdot y1\\ t_3 := y2 \cdot \left(\left(k \cdot t_1 + x \cdot t_2\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_4 := y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot t_2\\ t_5 := x \cdot t_4\\ \mathbf{if}\;j \leq -1.4 \cdot 10^{+196}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{+69}:\\ \;\;\;\;y4 \cdot \left(b \cdot \left(t \cdot j\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \mathbf{elif}\;j \leq -3.6 \cdot 10^{-108}:\\ \;\;\;\;x \cdot \left(t_4 + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -1.2 \cdot 10^{-236}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 1.48 \cdot 10^{-300}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;j \leq 2.9 \cdot 10^{-252}:\\ \;\;\;\;k \cdot \left(y2 \cdot t_1\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{-85}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;j \leq 9.5 \cdot 10^{-49} \lor \neg \left(j \leq 3 \cdot 10^{+82}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2 (- (* c y0) (* a y1)))
        (t_3 (* y2 (+ (+ (* k t_1) (* x t_2)) (* t (- (* a y5) (* c y4))))))
        (t_4 (+ (* y (- (* a b) (* c i))) (* y2 t_2)))
        (t_5 (* x t_4)))
   (if (<= j -1.4e+196)
     (* x (* y0 (- (* c y2) (* b j))))
     (if (<= j -8.5e+69)
       (+
        (* y4 (+ (* b (* t j)) (* c (- (* y y3) (* t y2)))))
        (* (* j y3) (- (* y0 y5) (* y1 y4))))
       (if (<= j -3.6e-108)
         (* x (+ t_4 (* j (- (* i y1) (* b y0)))))
         (if (<= j -1.2e-236)
           t_3
           (if (<= j 1.48e-300)
             t_5
             (if (<= j 2.9e-252)
               (* k (* y2 t_1))
               (if (<= j 2.1e-85)
                 t_5
                 (if (or (<= j 9.5e-49) (not (<= j 3e+82)))
                   (* b (* j (- (* t y4) (* x y0))))
                   t_3))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = (c * y0) - (a * y1);
	double t_3 = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))));
	double t_4 = (y * ((a * b) - (c * i))) + (y2 * t_2);
	double t_5 = x * t_4;
	double tmp;
	if (j <= -1.4e+196) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (j <= -8.5e+69) {
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * ((y0 * y5) - (y1 * y4)));
	} else if (j <= -3.6e-108) {
		tmp = x * (t_4 + (j * ((i * y1) - (b * y0))));
	} else if (j <= -1.2e-236) {
		tmp = t_3;
	} else if (j <= 1.48e-300) {
		tmp = t_5;
	} else if (j <= 2.9e-252) {
		tmp = k * (y2 * t_1);
	} else if (j <= 2.1e-85) {
		tmp = t_5;
	} else if ((j <= 9.5e-49) || !(j <= 3e+82)) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = (c * y0) - (a * y1)
    t_3 = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))))
    t_4 = (y * ((a * b) - (c * i))) + (y2 * t_2)
    t_5 = x * t_4
    if (j <= (-1.4d+196)) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else if (j <= (-8.5d+69)) then
        tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * ((y0 * y5) - (y1 * y4)))
    else if (j <= (-3.6d-108)) then
        tmp = x * (t_4 + (j * ((i * y1) - (b * y0))))
    else if (j <= (-1.2d-236)) then
        tmp = t_3
    else if (j <= 1.48d-300) then
        tmp = t_5
    else if (j <= 2.9d-252) then
        tmp = k * (y2 * t_1)
    else if (j <= 2.1d-85) then
        tmp = t_5
    else if ((j <= 9.5d-49) .or. (.not. (j <= 3d+82))) then
        tmp = b * (j * ((t * y4) - (x * y0)))
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = (c * y0) - (a * y1);
	double t_3 = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))));
	double t_4 = (y * ((a * b) - (c * i))) + (y2 * t_2);
	double t_5 = x * t_4;
	double tmp;
	if (j <= -1.4e+196) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (j <= -8.5e+69) {
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * ((y0 * y5) - (y1 * y4)));
	} else if (j <= -3.6e-108) {
		tmp = x * (t_4 + (j * ((i * y1) - (b * y0))));
	} else if (j <= -1.2e-236) {
		tmp = t_3;
	} else if (j <= 1.48e-300) {
		tmp = t_5;
	} else if (j <= 2.9e-252) {
		tmp = k * (y2 * t_1);
	} else if (j <= 2.1e-85) {
		tmp = t_5;
	} else if ((j <= 9.5e-49) || !(j <= 3e+82)) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = (c * y0) - (a * y1)
	t_3 = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))))
	t_4 = (y * ((a * b) - (c * i))) + (y2 * t_2)
	t_5 = x * t_4
	tmp = 0
	if j <= -1.4e+196:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	elif j <= -8.5e+69:
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * ((y0 * y5) - (y1 * y4)))
	elif j <= -3.6e-108:
		tmp = x * (t_4 + (j * ((i * y1) - (b * y0))))
	elif j <= -1.2e-236:
		tmp = t_3
	elif j <= 1.48e-300:
		tmp = t_5
	elif j <= 2.9e-252:
		tmp = k * (y2 * t_1)
	elif j <= 2.1e-85:
		tmp = t_5
	elif (j <= 9.5e-49) or not (j <= 3e+82):
		tmp = b * (j * ((t * y4) - (x * y0)))
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(Float64(c * y0) - Float64(a * y1))
	t_3 = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * t_2)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))))
	t_4 = Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * t_2))
	t_5 = Float64(x * t_4)
	tmp = 0.0
	if (j <= -1.4e+196)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (j <= -8.5e+69)
		tmp = Float64(Float64(y4 * Float64(Float64(b * Float64(t * j)) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2))))) + Float64(Float64(j * y3) * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (j <= -3.6e-108)
		tmp = Float64(x * Float64(t_4 + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (j <= -1.2e-236)
		tmp = t_3;
	elseif (j <= 1.48e-300)
		tmp = t_5;
	elseif (j <= 2.9e-252)
		tmp = Float64(k * Float64(y2 * t_1));
	elseif (j <= 2.1e-85)
		tmp = t_5;
	elseif ((j <= 9.5e-49) || !(j <= 3e+82))
		tmp = Float64(b * Float64(j * Float64(Float64(t * y4) - Float64(x * y0))));
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y1 * y4) - (y0 * y5);
	t_2 = (c * y0) - (a * y1);
	t_3 = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))));
	t_4 = (y * ((a * b) - (c * i))) + (y2 * t_2);
	t_5 = x * t_4;
	tmp = 0.0;
	if (j <= -1.4e+196)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	elseif (j <= -8.5e+69)
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * ((y0 * y5) - (y1 * y4)));
	elseif (j <= -3.6e-108)
		tmp = x * (t_4 + (j * ((i * y1) - (b * y0))));
	elseif (j <= -1.2e-236)
		tmp = t_3;
	elseif (j <= 1.48e-300)
		tmp = t_5;
	elseif (j <= 2.9e-252)
		tmp = k * (y2 * t_1);
	elseif (j <= 2.1e-85)
		tmp = t_5;
	elseif ((j <= 9.5e-49) || ~((j <= 3e+82)))
		tmp = b * (j * ((t * y4) - (x * y0)));
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(x * t$95$4), $MachinePrecision]}, If[LessEqual[j, -1.4e+196], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -8.5e+69], N[(N[(y4 * N[(N[(b * N[(t * j), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * y3), $MachinePrecision] * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -3.6e-108], N[(x * N[(t$95$4 + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.2e-236], t$95$3, If[LessEqual[j, 1.48e-300], t$95$5, If[LessEqual[j, 2.9e-252], N[(k * N[(y2 * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.1e-85], t$95$5, If[Or[LessEqual[j, 9.5e-49], N[Not[LessEqual[j, 3e+82]], $MachinePrecision]], N[(b * N[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.4000000000000001e196

   1. Initial program 17.8%

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

   2. Taylor expanded in x around inf 33.0%

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

   3. Taylor expanded in y0 around inf 58.0%

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

      1. *-commutative 58.0%

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

      2. *-commutative 58.0%

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

   5. Simplified 58.0%

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

   if -1.4000000000000001e196 < j < -8.5000000000000002e69

   1. Initial program 22.7%

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

   2. Taylor expanded in y4 around inf 50.8%

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

      1. *-commutative 50.8%

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

      2. *-commutative 50.8%

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

   4. Simplified 50.8%

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

   5. Taylor expanded in k around 0 64.5%

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

      1. +-commutative 64.5%

         \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + -1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]

      2. mul-1-neg 64.5%

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

      3. unsub-neg 64.5%

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

      4. *-commutative 64.5%

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

      5. associate-*r* 64.5%

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

   7. Simplified 64.5%

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

   if -8.5000000000000002e69 < j < -3.6000000000000001e-108

   1. Initial program 37.0%

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

   2. Taylor expanded in x around inf 59.0%

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

   if -3.6000000000000001e-108 < j < -1.2000000000000001e-236 or 9.50000000000000006e-49 < j < 2.99999999999999989e82

   1. Initial program 23.1%

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

   2. Taylor expanded in y2 around inf 51.2%

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

   if -1.2000000000000001e-236 < j < 1.4799999999999999e-300 or 2.9000000000000001e-252 < j < 2.1e-85

   1. Initial program 33.4%

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

   2. Taylor expanded in x around inf 57.4%

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

   3. Taylor expanded in j around 0 61.3%

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

   if 1.4799999999999999e-300 < j < 2.9000000000000001e-252

   1. Initial program 54.5%

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

   2. Taylor expanded in y4 around inf 37.4%

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

      1. *-commutative 37.4%

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

      2. *-commutative 37.4%

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

   4. Simplified 37.4%

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

   5. Taylor expanded in k around inf 46.8%

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

      1. mul-1-neg 46.8%

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

      2. distribute-rgt-neg-in 46.8%

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

      3. associate-*r* 37.7%

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

      4. distribute-rgt-neg-in 37.7%

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

      5. *-commutative 37.7%

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

   7. Simplified 37.7%

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

   8. Taylor expanded in y2 around inf 55.6%

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

   if 2.1e-85 < j < 9.50000000000000006e-49 or 2.99999999999999989e82 < j

   1. Initial program 26.2%

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

   2. Taylor expanded in b around inf 41.8%

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

   3. Taylor expanded in j around inf 59.5%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 58.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.4 \cdot 10^{+196}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{+69}:\\ \;\;\;\;y4 \cdot \left(b \cdot \left(t \cdot j\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \mathbf{elif}\;j \leq -3.6 \cdot 10^{-108}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -1.2 \cdot 10^{-236}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.48 \cdot 10^{-300}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 2.9 \cdot 10^{-252}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{-85}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 9.5 \cdot 10^{-49} \lor \neg \left(j \leq 3 \cdot 10^{+82}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \]

Alternative 4: 36.2% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(i \cdot y1 - b \cdot y0\right)\\ t_2 := y \cdot \left(a \cdot b - c \cdot i\right)\\ t_3 := \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ t_4 := y0 \cdot y5 - y1 \cdot y4\\ t_5 := y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{if}\;y4 \leq -5 \cdot 10^{+229}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -3.85 \cdot 10^{+143}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y4 \leq -2.7 \cdot 10^{+128}:\\ \;\;\;\;y3 \cdot \left(c \cdot \left(y \cdot y4\right) - \left(c \cdot \left(z \cdot y0\right) - j \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 \leq -1.2 \cdot 10^{+79}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -1.3 \cdot 10^{-135}:\\ \;\;\;\;x \cdot \left(t_5 + t_1\right)\\ \mathbf{elif}\;y4 \leq -9.2 \cdot 10^{-215}:\\ \;\;\;\;x \cdot t_2\\ \mathbf{elif}\;y4 \leq -2.85 \cdot 10^{-291}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y4 \leq 8.5 \cdot 10^{+68}:\\ \;\;\;\;x \cdot \left(\left(t_2 + t_5\right) + t_1\right)\\ \mathbf{elif}\;y4 \leq 1.25 \cdot 10^{+240}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(b \cdot \left(t \cdot j\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(j \cdot y3\right) \cdot t_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (- (* i y1) (* b y0))))
        (t_2 (* y (- (* a b) (* c i))))
        (t_3
         (-
          (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5)))
          (* b (* (* y k) y4))))
        (t_4 (- (* y0 y5) (* y1 y4)))
        (t_5 (* y2 (- (* c y0) (* a y1)))))
   (if (<= y4 -5e+229)
     (* c (* y (* y3 y4)))
     (if (<= y4 -3.85e+143)
       t_3
       (if (<= y4 -2.7e+128)
         (* y3 (- (* c (* y y4)) (- (* c (* z y0)) (* j t_4))))
         (if (<= y4 -1.2e+79)
           (* t (* y4 (- (* b j) (* c y2))))
           (if (<= y4 -1.3e-135)
             (* x (+ t_5 t_1))
             (if (<= y4 -9.2e-215)
               (* x t_2)
               (if (<= y4 -2.85e-291)
                 (* x (* y0 (- (* c y2) (* b j))))
                 (if (<= y4 8.5e+68)
                   (* x (+ (+ t_2 t_5) t_1))
                   (if (<= y4 1.25e+240)
                     t_3
                     (+
                      (* y4 (+ (* b (* t j)) (* c (- (* y y3) (* t y2)))))
                      (* (* j y3) t_4)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * ((i * y1) - (b * y0));
	double t_2 = y * ((a * b) - (c * i));
	double t_3 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	double t_4 = (y0 * y5) - (y1 * y4);
	double t_5 = y2 * ((c * y0) - (a * y1));
	double tmp;
	if (y4 <= -5e+229) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -3.85e+143) {
		tmp = t_3;
	} else if (y4 <= -2.7e+128) {
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_4)));
	} else if (y4 <= -1.2e+79) {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	} else if (y4 <= -1.3e-135) {
		tmp = x * (t_5 + t_1);
	} else if (y4 <= -9.2e-215) {
		tmp = x * t_2;
	} else if (y4 <= -2.85e-291) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (y4 <= 8.5e+68) {
		tmp = x * ((t_2 + t_5) + t_1);
	} else if (y4 <= 1.25e+240) {
		tmp = t_3;
	} else {
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * t_4);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: tmp
    t_1 = j * ((i * y1) - (b * y0))
    t_2 = y * ((a * b) - (c * i))
    t_3 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4))
    t_4 = (y0 * y5) - (y1 * y4)
    t_5 = y2 * ((c * y0) - (a * y1))
    if (y4 <= (-5d+229)) then
        tmp = c * (y * (y3 * y4))
    else if (y4 <= (-3.85d+143)) then
        tmp = t_3
    else if (y4 <= (-2.7d+128)) then
        tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_4)))
    else if (y4 <= (-1.2d+79)) then
        tmp = t * (y4 * ((b * j) - (c * y2)))
    else if (y4 <= (-1.3d-135)) then
        tmp = x * (t_5 + t_1)
    else if (y4 <= (-9.2d-215)) then
        tmp = x * t_2
    else if (y4 <= (-2.85d-291)) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else if (y4 <= 8.5d+68) then
        tmp = x * ((t_2 + t_5) + t_1)
    else if (y4 <= 1.25d+240) then
        tmp = t_3
    else
        tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * t_4)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * ((i * y1) - (b * y0));
	double t_2 = y * ((a * b) - (c * i));
	double t_3 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	double t_4 = (y0 * y5) - (y1 * y4);
	double t_5 = y2 * ((c * y0) - (a * y1));
	double tmp;
	if (y4 <= -5e+229) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -3.85e+143) {
		tmp = t_3;
	} else if (y4 <= -2.7e+128) {
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_4)));
	} else if (y4 <= -1.2e+79) {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	} else if (y4 <= -1.3e-135) {
		tmp = x * (t_5 + t_1);
	} else if (y4 <= -9.2e-215) {
		tmp = x * t_2;
	} else if (y4 <= -2.85e-291) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (y4 <= 8.5e+68) {
		tmp = x * ((t_2 + t_5) + t_1);
	} else if (y4 <= 1.25e+240) {
		tmp = t_3;
	} else {
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * t_4);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * ((i * y1) - (b * y0))
	t_2 = y * ((a * b) - (c * i))
	t_3 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4))
	t_4 = (y0 * y5) - (y1 * y4)
	t_5 = y2 * ((c * y0) - (a * y1))
	tmp = 0
	if y4 <= -5e+229:
		tmp = c * (y * (y3 * y4))
	elif y4 <= -3.85e+143:
		tmp = t_3
	elif y4 <= -2.7e+128:
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_4)))
	elif y4 <= -1.2e+79:
		tmp = t * (y4 * ((b * j) - (c * y2)))
	elif y4 <= -1.3e-135:
		tmp = x * (t_5 + t_1)
	elif y4 <= -9.2e-215:
		tmp = x * t_2
	elif y4 <= -2.85e-291:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	elif y4 <= 8.5e+68:
		tmp = x * ((t_2 + t_5) + t_1)
	elif y4 <= 1.25e+240:
		tmp = t_3
	else:
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * t_4)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))
	t_2 = Float64(y * Float64(Float64(a * b) - Float64(c * i)))
	t_3 = Float64(Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5))) - Float64(b * Float64(Float64(y * k) * y4)))
	t_4 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_5 = Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))
	tmp = 0.0
	if (y4 <= -5e+229)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	elseif (y4 <= -3.85e+143)
		tmp = t_3;
	elseif (y4 <= -2.7e+128)
		tmp = Float64(y3 * Float64(Float64(c * Float64(y * y4)) - Float64(Float64(c * Float64(z * y0)) - Float64(j * t_4))));
	elseif (y4 <= -1.2e+79)
		tmp = Float64(t * Float64(y4 * Float64(Float64(b * j) - Float64(c * y2))));
	elseif (y4 <= -1.3e-135)
		tmp = Float64(x * Float64(t_5 + t_1));
	elseif (y4 <= -9.2e-215)
		tmp = Float64(x * t_2);
	elseif (y4 <= -2.85e-291)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (y4 <= 8.5e+68)
		tmp = Float64(x * Float64(Float64(t_2 + t_5) + t_1));
	elseif (y4 <= 1.25e+240)
		tmp = t_3;
	else
		tmp = Float64(Float64(y4 * Float64(Float64(b * Float64(t * j)) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2))))) + Float64(Float64(j * y3) * t_4));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * ((i * y1) - (b * y0));
	t_2 = y * ((a * b) - (c * i));
	t_3 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	t_4 = (y0 * y5) - (y1 * y4);
	t_5 = y2 * ((c * y0) - (a * y1));
	tmp = 0.0;
	if (y4 <= -5e+229)
		tmp = c * (y * (y3 * y4));
	elseif (y4 <= -3.85e+143)
		tmp = t_3;
	elseif (y4 <= -2.7e+128)
		tmp = y3 * ((c * (y * y4)) - ((c * (z * y0)) - (j * t_4)));
	elseif (y4 <= -1.2e+79)
		tmp = t * (y4 * ((b * j) - (c * y2)));
	elseif (y4 <= -1.3e-135)
		tmp = x * (t_5 + t_1);
	elseif (y4 <= -9.2e-215)
		tmp = x * t_2;
	elseif (y4 <= -2.85e-291)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	elseif (y4 <= 8.5e+68)
		tmp = x * ((t_2 + t_5) + t_1);
	elseif (y4 <= 1.25e+240)
		tmp = t_3;
	else
		tmp = (y4 * ((b * (t * j)) + (c * ((y * y3) - (t * y2))))) + ((j * y3) * t_4);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -5e+229], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -3.85e+143], t$95$3, If[LessEqual[y4, -2.7e+128], N[(y3 * N[(N[(c * N[(y * y4), $MachinePrecision]), $MachinePrecision] - N[(N[(c * N[(z * y0), $MachinePrecision]), $MachinePrecision] - N[(j * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.2e+79], N[(t * N[(y4 * N[(N[(b * j), $MachinePrecision] - N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.3e-135], N[(x * N[(t$95$5 + t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -9.2e-215], N[(x * t$95$2), $MachinePrecision], If[LessEqual[y4, -2.85e-291], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 8.5e+68], N[(x * N[(N[(t$95$2 + t$95$5), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.25e+240], t$95$3, N[(N[(y4 * N[(N[(b * N[(t * j), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * y3), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y4 < -5.0000000000000005e229

   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. Taylor expanded in y4 around inf 21.9%

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

      1. *-commutative 21.9%

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

      2. *-commutative 21.9%

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

   4. Simplified 21.9%

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

   5. Taylor expanded in y around inf 71.6%

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

      1. associate-*r* 51.3%

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

      2. distribute-lft-out-- 51.3%

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

   7. Simplified 51.3%

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

   8. Taylor expanded in b around 0 71.6%

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

      1. *-commutative 71.6%

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

   10. Simplified 71.6%

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

   if -5.0000000000000005e229 < y4 < -3.85000000000000013e143 or 8.49999999999999966e68 < y4 < 1.2500000000000001e240

   1. Initial program 20.9%

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

   2. Taylor expanded in y4 around inf 39.5%

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

      1. *-commutative 39.5%

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

      2. *-commutative 39.5%

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

   4. Simplified 39.5%

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

   5. Taylor expanded in k around inf 58.2%

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

      1. mul-1-neg 58.2%

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

      2. distribute-rgt-neg-in 58.2%

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

      3. associate-*r* 62.8%

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

      4. distribute-rgt-neg-in 62.8%

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

      5. *-commutative 62.8%

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

   7. Simplified 62.8%

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

   if -3.85000000000000013e143 < y4 < -2.70000000000000001e128

   1. Initial program 40.0%

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

   2. Taylor expanded in y3 around -inf 63.0%

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

   3. Taylor expanded in a around 0 81.6%

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

   if -2.70000000000000001e128 < y4 < -1.19999999999999993e79

   1. Initial program 18.2%

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

   2. Taylor expanded in y4 around inf 36.9%

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

      1. *-commutative 36.9%

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

      2. *-commutative 36.9%

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

   4. Simplified 36.9%

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

   5. Taylor expanded in t around inf 73.2%

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

   if -1.19999999999999993e79 < y4 < -1.30000000000000002e-135

   1. Initial program 28.2%

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

   2. Taylor expanded in x around inf 57.0%

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

   3. Taylor expanded in y around 0 62.2%

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

      1. *-commutative 62.2%

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

      2. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if -1.30000000000000002e-135 < y4 < -9.1999999999999996e-215

   1. Initial program 20.6%

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

   2. Taylor expanded in x around inf 60.3%

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

   3. Taylor expanded in y around inf 60.8%

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

   if -9.1999999999999996e-215 < y4 < -2.85000000000000017e-291

   1. Initial program 22.4%

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

   2. Taylor expanded in x around inf 33.6%

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

   3. Taylor expanded in y0 around inf 49.0%

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

      1. *-commutative 49.0%

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

      2. *-commutative 49.0%

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

   5. Simplified 49.0%

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

   if -2.85000000000000017e-291 < y4 < 8.49999999999999966e68

   1. Initial program 40.7%

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

   2. Taylor expanded in x around inf 50.6%

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

   if 1.2500000000000001e240 < y4

   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. Taylor expanded in y4 around inf 38.1%

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

      1. *-commutative 38.1%

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

      2. *-commutative 38.1%

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

   4. Simplified 38.1%

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

   5. Taylor expanded in k around 0 57.7%

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

      1. +-commutative 57.7%

         \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + -1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]

      2. mul-1-neg 57.7%

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

      3. unsub-neg 57.7%

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

      4. *-commutative 57.7%

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

      5. associate-*r* 57.7%

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

   7. Simplified 57.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t\right) - c \cdot \left(y2 \cdot t - y \cdot y3\right)\right) - \left(j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 57.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -5 \cdot 10^{+229}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -3.85 \cdot 10^{+143}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{elif}\;y4 \leq -2.7 \cdot 10^{+128}:\\ \;\;\;\;y3 \cdot \left(c \cdot \left(y \cdot y4\right) - \left(c \cdot \left(z \cdot y0\right) - j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\right)\\ \mathbf{elif}\;y4 \leq -1.2 \cdot 10^{+79}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -1.3 \cdot 10^{-135}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq -9.2 \cdot 10^{-215}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y4 \leq -2.85 \cdot 10^{-291}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;y4 \leq 8.5 \cdot 10^{+68}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.25 \cdot 10^{+240}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(b \cdot \left(t \cdot j\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \end{array} \]

Alternative 5: 41.8% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot y0 - a \cdot y1\\ t_2 := a \cdot b - c \cdot i\\ t_3 := j \cdot \left(i \cdot y1 - b \cdot y0\right)\\ t_4 := t \cdot j - y \cdot k\\ t_5 := y4 \cdot \left(\left(b \cdot t_4 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ t_6 := b \cdot y0 - i \cdot y1\\ t_7 := x \cdot j - z \cdot k\\ t_8 := y2 \cdot t_1\\ t_9 := x \cdot \left(\left(y \cdot t_2 + t_8\right) + t_3\right)\\ \mathbf{if}\;y4 \leq -4.6 \cdot 10^{+79}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;y4 \leq -1.58 \cdot 10^{-145}:\\ \;\;\;\;x \cdot \left(t_8 + t_3\right)\\ \mathbf{elif}\;y4 \leq -1.75 \cdot 10^{-259}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot t_6\right)\\ \mathbf{elif}\;y4 \leq 4.8 \cdot 10^{-226}:\\ \;\;\;\;t_9\\ \mathbf{elif}\;y4 \leq 1.25 \cdot 10^{-193}:\\ \;\;\;\;i \cdot \left(y1 \cdot t_7 - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 \leq 3100000000:\\ \;\;\;\;t_9\\ \mathbf{elif}\;y4 \leq 4.4 \cdot 10^{+76}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) - b \cdot t_7\right)\\ \mathbf{elif}\;y4 \leq 8 \cdot 10^{+180}:\\ \;\;\;\;z \cdot \left(k \cdot t_6 - \left(t \cdot t_2 + y3 \cdot t_1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_5\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* c y0) (* a y1)))
        (t_2 (- (* a b) (* c i)))
        (t_3 (* j (- (* i y1) (* b y0))))
        (t_4 (- (* t j) (* y k)))
        (t_5
         (*
          y4
          (+
           (+ (* b t_4) (* y1 (- (* k y2) (* j y3))))
           (* c (- (* y y3) (* t y2))))))
        (t_6 (- (* b y0) (* i y1)))
        (t_7 (- (* x j) (* z k)))
        (t_8 (* y2 t_1))
        (t_9 (* x (+ (+ (* y t_2) t_8) t_3))))
   (if (<= y4 -4.6e+79)
     t_5
     (if (<= y4 -1.58e-145)
       (* x (+ t_8 t_3))
       (if (<= y4 -1.75e-259)
         (*
          k
          (+
           (+ (* y (- (* i y5) (* b y4))) (* y2 (- (* y1 y4) (* y0 y5))))
           (* z t_6)))
         (if (<= y4 4.8e-226)
           t_9
           (if (<= y4 1.25e-193)
             (* i (- (* y1 t_7) (+ (* c (- (* x y) (* z t))) (* y5 t_4))))
             (if (<= y4 3100000000.0)
               t_9
               (if (<= y4 4.4e+76)
                 (*
                  y0
                  (-
                   (+ (* y5 (- (* j y3) (* k y2))) (* c (- (* x y2) (* z y3))))
                   (* b t_7)))
                 (if (<= y4 8e+180)
                   (* z (- (* k t_6) (+ (* t t_2) (* y3 t_1))))
                   t_5))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (c * y0) - (a * y1);
	double t_2 = (a * b) - (c * i);
	double t_3 = j * ((i * y1) - (b * y0));
	double t_4 = (t * j) - (y * k);
	double t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_6 = (b * y0) - (i * y1);
	double t_7 = (x * j) - (z * k);
	double t_8 = y2 * t_1;
	double t_9 = x * (((y * t_2) + t_8) + t_3);
	double tmp;
	if (y4 <= -4.6e+79) {
		tmp = t_5;
	} else if (y4 <= -1.58e-145) {
		tmp = x * (t_8 + t_3);
	} else if (y4 <= -1.75e-259) {
		tmp = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * t_6));
	} else if (y4 <= 4.8e-226) {
		tmp = t_9;
	} else if (y4 <= 1.25e-193) {
		tmp = i * ((y1 * t_7) - ((c * ((x * y) - (z * t))) + (y5 * t_4)));
	} else if (y4 <= 3100000000.0) {
		tmp = t_9;
	} else if (y4 <= 4.4e+76) {
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_7));
	} else if (y4 <= 8e+180) {
		tmp = z * ((k * t_6) - ((t * t_2) + (y3 * t_1)));
	} else {
		tmp = t_5;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (c * y0) - (a * y1)
    t_2 = (a * b) - (c * i)
    t_3 = j * ((i * y1) - (b * y0))
    t_4 = (t * j) - (y * k)
    t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    t_6 = (b * y0) - (i * y1)
    t_7 = (x * j) - (z * k)
    t_8 = y2 * t_1
    t_9 = x * (((y * t_2) + t_8) + t_3)
    if (y4 <= (-4.6d+79)) then
        tmp = t_5
    else if (y4 <= (-1.58d-145)) then
        tmp = x * (t_8 + t_3)
    else if (y4 <= (-1.75d-259)) then
        tmp = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * t_6))
    else if (y4 <= 4.8d-226) then
        tmp = t_9
    else if (y4 <= 1.25d-193) then
        tmp = i * ((y1 * t_7) - ((c * ((x * y) - (z * t))) + (y5 * t_4)))
    else if (y4 <= 3100000000.0d0) then
        tmp = t_9
    else if (y4 <= 4.4d+76) then
        tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_7))
    else if (y4 <= 8d+180) then
        tmp = z * ((k * t_6) - ((t * t_2) + (y3 * t_1)))
    else
        tmp = t_5
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (c * y0) - (a * y1);
	double t_2 = (a * b) - (c * i);
	double t_3 = j * ((i * y1) - (b * y0));
	double t_4 = (t * j) - (y * k);
	double t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_6 = (b * y0) - (i * y1);
	double t_7 = (x * j) - (z * k);
	double t_8 = y2 * t_1;
	double t_9 = x * (((y * t_2) + t_8) + t_3);
	double tmp;
	if (y4 <= -4.6e+79) {
		tmp = t_5;
	} else if (y4 <= -1.58e-145) {
		tmp = x * (t_8 + t_3);
	} else if (y4 <= -1.75e-259) {
		tmp = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * t_6));
	} else if (y4 <= 4.8e-226) {
		tmp = t_9;
	} else if (y4 <= 1.25e-193) {
		tmp = i * ((y1 * t_7) - ((c * ((x * y) - (z * t))) + (y5 * t_4)));
	} else if (y4 <= 3100000000.0) {
		tmp = t_9;
	} else if (y4 <= 4.4e+76) {
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_7));
	} else if (y4 <= 8e+180) {
		tmp = z * ((k * t_6) - ((t * t_2) + (y3 * t_1)));
	} else {
		tmp = t_5;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (c * y0) - (a * y1)
	t_2 = (a * b) - (c * i)
	t_3 = j * ((i * y1) - (b * y0))
	t_4 = (t * j) - (y * k)
	t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	t_6 = (b * y0) - (i * y1)
	t_7 = (x * j) - (z * k)
	t_8 = y2 * t_1
	t_9 = x * (((y * t_2) + t_8) + t_3)
	tmp = 0
	if y4 <= -4.6e+79:
		tmp = t_5
	elif y4 <= -1.58e-145:
		tmp = x * (t_8 + t_3)
	elif y4 <= -1.75e-259:
		tmp = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * t_6))
	elif y4 <= 4.8e-226:
		tmp = t_9
	elif y4 <= 1.25e-193:
		tmp = i * ((y1 * t_7) - ((c * ((x * y) - (z * t))) + (y5 * t_4)))
	elif y4 <= 3100000000.0:
		tmp = t_9
	elif y4 <= 4.4e+76:
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_7))
	elif y4 <= 8e+180:
		tmp = z * ((k * t_6) - ((t * t_2) + (y3 * t_1)))
	else:
		tmp = t_5
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(c * y0) - Float64(a * y1))
	t_2 = Float64(Float64(a * b) - Float64(c * i))
	t_3 = Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))
	t_4 = Float64(Float64(t * j) - Float64(y * k))
	t_5 = Float64(y4 * Float64(Float64(Float64(b * t_4) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))))
	t_6 = Float64(Float64(b * y0) - Float64(i * y1))
	t_7 = Float64(Float64(x * j) - Float64(z * k))
	t_8 = Float64(y2 * t_1)
	t_9 = Float64(x * Float64(Float64(Float64(y * t_2) + t_8) + t_3))
	tmp = 0.0
	if (y4 <= -4.6e+79)
		tmp = t_5;
	elseif (y4 <= -1.58e-145)
		tmp = Float64(x * Float64(t_8 + t_3));
	elseif (y4 <= -1.75e-259)
		tmp = Float64(k * Float64(Float64(Float64(y * Float64(Float64(i * y5) - Float64(b * y4))) + Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) + Float64(z * t_6)));
	elseif (y4 <= 4.8e-226)
		tmp = t_9;
	elseif (y4 <= 1.25e-193)
		tmp = Float64(i * Float64(Float64(y1 * t_7) - Float64(Float64(c * Float64(Float64(x * y) - Float64(z * t))) + Float64(y5 * t_4))));
	elseif (y4 <= 3100000000.0)
		tmp = t_9;
	elseif (y4 <= 4.4e+76)
		tmp = Float64(y0 * Float64(Float64(Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(c * Float64(Float64(x * y2) - Float64(z * y3)))) - Float64(b * t_7)));
	elseif (y4 <= 8e+180)
		tmp = Float64(z * Float64(Float64(k * t_6) - Float64(Float64(t * t_2) + Float64(y3 * t_1))));
	else
		tmp = t_5;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (c * y0) - (a * y1);
	t_2 = (a * b) - (c * i);
	t_3 = j * ((i * y1) - (b * y0));
	t_4 = (t * j) - (y * k);
	t_5 = y4 * (((b * t_4) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	t_6 = (b * y0) - (i * y1);
	t_7 = (x * j) - (z * k);
	t_8 = y2 * t_1;
	t_9 = x * (((y * t_2) + t_8) + t_3);
	tmp = 0.0;
	if (y4 <= -4.6e+79)
		tmp = t_5;
	elseif (y4 <= -1.58e-145)
		tmp = x * (t_8 + t_3);
	elseif (y4 <= -1.75e-259)
		tmp = k * (((y * ((i * y5) - (b * y4))) + (y2 * ((y1 * y4) - (y0 * y5)))) + (z * t_6));
	elseif (y4 <= 4.8e-226)
		tmp = t_9;
	elseif (y4 <= 1.25e-193)
		tmp = i * ((y1 * t_7) - ((c * ((x * y) - (z * t))) + (y5 * t_4)));
	elseif (y4 <= 3100000000.0)
		tmp = t_9;
	elseif (y4 <= 4.4e+76)
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * ((x * y2) - (z * y3)))) - (b * t_7));
	elseif (y4 <= 8e+180)
		tmp = z * ((k * t_6) - ((t * t_2) + (y3 * t_1)));
	else
		tmp = t_5;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(y4 * N[(N[(N[(b * t$95$4), $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]}, Block[{t$95$6 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(y2 * t$95$1), $MachinePrecision]}, Block[{t$95$9 = N[(x * N[(N[(N[(y * t$95$2), $MachinePrecision] + t$95$8), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -4.6e+79], t$95$5, If[LessEqual[y4, -1.58e-145], N[(x * N[(t$95$8 + t$95$3), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.75e-259], N[(k * N[(N[(N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 4.8e-226], t$95$9, If[LessEqual[y4, 1.25e-193], N[(i * N[(N[(y1 * t$95$7), $MachinePrecision] - N[(N[(c * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 3100000000.0], t$95$9, If[LessEqual[y4, 4.4e+76], N[(y0 * N[(N[(N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 8e+180], N[(z * N[(N[(k * t$95$6), $MachinePrecision] - N[(N[(t * t$95$2), $MachinePrecision] + N[(y3 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$5]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y4 < -4.6000000000000001e79 or 8.0000000000000001e180 < y4

   1. Initial program 22.5%

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

   2. Taylor expanded in y4 around inf 66.4%

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

   if -4.6000000000000001e79 < y4 < -1.58000000000000003e-145

   1. Initial program 26.2%

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

   2. Taylor expanded in x around inf 55.3%

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

   3. Taylor expanded in y around 0 60.1%

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

      1. *-commutative 60.1%

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

      2. *-commutative 60.1%

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

   5. Simplified 60.1%

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

   if -1.58000000000000003e-145 < y4 < -1.7500000000000001e-259

   1. Initial program 29.4%

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

   2. Taylor expanded in k around inf 55.9%

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

   if -1.7500000000000001e-259 < y4 < 4.7999999999999999e-226 or 1.2500000000000001e-193 < y4 < 3.1e9

   1. Initial program 32.5%

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

   2. Taylor expanded in x around inf 55.5%

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

   if 4.7999999999999999e-226 < y4 < 1.2500000000000001e-193

   1. Initial program 53.5%

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

   2. Taylor expanded in i around -inf 61.6%

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

   if 3.1e9 < y4 < 4.4000000000000001e76

   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. Taylor expanded in y0 around inf 83.4%

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

   if 4.4000000000000001e76 < y4 < 8.0000000000000001e180

   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. Taylor expanded in z around -inf 62.0%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 61.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -4.6 \cdot 10^{+79}:\\ \;\;\;\;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}\;y4 \leq -1.58 \cdot 10^{-145}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq -1.75 \cdot 10^{-259}:\\ \;\;\;\;k \cdot \left(\left(y \cdot \left(i \cdot y5 - b \cdot y4\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq 4.8 \cdot 10^{-226}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.25 \cdot 10^{-193}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;y4 \leq 3100000000:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 4.4 \cdot 10^{+76}:\\ \;\;\;\;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(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;y4 \leq 8 \cdot 10^{+180}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;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)\\ \end{array} \]

Alternative 6: 41.6% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\\ t_2 := t \cdot j - y \cdot k\\ t_3 := y4 \cdot \left(\left(b \cdot t_2 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ t_4 := x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + t_1\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{if}\;y4 \leq -2.45 \cdot 10^{+182}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y4 \leq -1.15 \cdot 10^{+144}:\\ \;\;\;\;x \cdot t_1\\ \mathbf{elif}\;y4 \leq -3.3 \cdot 10^{+80}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y4 \leq 2.4 \cdot 10^{-225}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;y4 \leq 5.9 \cdot 10^{-195}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot t_2\right)\right)\\ \mathbf{elif}\;y4 \leq 3.7 \cdot 10^{+24}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;y4 \leq 5 \cdot 10^{+181}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y2 (- (* c y0) (* a y1))))
        (t_2 (- (* t j) (* y k)))
        (t_3
         (*
          y4
          (+
           (+ (* b t_2) (* y1 (- (* k y2) (* j y3))))
           (* c (- (* y y3) (* t y2))))))
        (t_4
         (*
          x
          (+ (+ (* y (- (* a b) (* c i))) t_1) (* j (- (* i y1) (* b y0)))))))
   (if (<= y4 -2.45e+182)
     t_3
     (if (<= y4 -1.15e+144)
       (* x t_1)
       (if (<= y4 -3.3e+80)
         t_3
         (if (<= y4 2.4e-225)
           t_4
           (if (<= y4 5.9e-195)
             (*
              i
              (-
               (* y1 (- (* x j) (* z k)))
               (+ (* c (- (* x y) (* z t))) (* y5 t_2))))
             (if (<= y4 3.7e+24)
               t_4
               (if (<= y4 5e+181)
                 (- (* j (* y3 (- (* y0 y5) (* y1 y4)))) (* b (* (* y k) y4)))
                 t_3)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y2 * ((c * y0) - (a * y1));
	double t_2 = (t * j) - (y * k);
	double t_3 = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_4 = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))));
	double tmp;
	if (y4 <= -2.45e+182) {
		tmp = t_3;
	} else if (y4 <= -1.15e+144) {
		tmp = x * t_1;
	} else if (y4 <= -3.3e+80) {
		tmp = t_3;
	} else if (y4 <= 2.4e-225) {
		tmp = t_4;
	} else if (y4 <= 5.9e-195) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * ((x * y) - (z * t))) + (y5 * t_2)));
	} else if (y4 <= 3.7e+24) {
		tmp = t_4;
	} else if (y4 <= 5e+181) {
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = y2 * ((c * y0) - (a * y1))
    t_2 = (t * j) - (y * k)
    t_3 = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    t_4 = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))))
    if (y4 <= (-2.45d+182)) then
        tmp = t_3
    else if (y4 <= (-1.15d+144)) then
        tmp = x * t_1
    else if (y4 <= (-3.3d+80)) then
        tmp = t_3
    else if (y4 <= 2.4d-225) then
        tmp = t_4
    else if (y4 <= 5.9d-195) then
        tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * ((x * y) - (z * t))) + (y5 * t_2)))
    else if (y4 <= 3.7d+24) then
        tmp = t_4
    else if (y4 <= 5d+181) then
        tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4))
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y2 * ((c * y0) - (a * y1));
	double t_2 = (t * j) - (y * k);
	double t_3 = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_4 = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))));
	double tmp;
	if (y4 <= -2.45e+182) {
		tmp = t_3;
	} else if (y4 <= -1.15e+144) {
		tmp = x * t_1;
	} else if (y4 <= -3.3e+80) {
		tmp = t_3;
	} else if (y4 <= 2.4e-225) {
		tmp = t_4;
	} else if (y4 <= 5.9e-195) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * ((x * y) - (z * t))) + (y5 * t_2)));
	} else if (y4 <= 3.7e+24) {
		tmp = t_4;
	} else if (y4 <= 5e+181) {
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y2 * ((c * y0) - (a * y1))
	t_2 = (t * j) - (y * k)
	t_3 = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	t_4 = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))))
	tmp = 0
	if y4 <= -2.45e+182:
		tmp = t_3
	elif y4 <= -1.15e+144:
		tmp = x * t_1
	elif y4 <= -3.3e+80:
		tmp = t_3
	elif y4 <= 2.4e-225:
		tmp = t_4
	elif y4 <= 5.9e-195:
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * ((x * y) - (z * t))) + (y5 * t_2)))
	elif y4 <= 3.7e+24:
		tmp = t_4
	elif y4 <= 5e+181:
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4))
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))
	t_2 = Float64(Float64(t * j) - Float64(y * k))
	t_3 = Float64(y4 * Float64(Float64(Float64(b * t_2) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))))
	t_4 = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + t_1) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))))
	tmp = 0.0
	if (y4 <= -2.45e+182)
		tmp = t_3;
	elseif (y4 <= -1.15e+144)
		tmp = Float64(x * t_1);
	elseif (y4 <= -3.3e+80)
		tmp = t_3;
	elseif (y4 <= 2.4e-225)
		tmp = t_4;
	elseif (y4 <= 5.9e-195)
		tmp = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) - Float64(Float64(c * Float64(Float64(x * y) - Float64(z * t))) + Float64(y5 * t_2))));
	elseif (y4 <= 3.7e+24)
		tmp = t_4;
	elseif (y4 <= 5e+181)
		tmp = Float64(Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) - Float64(b * Float64(Float64(y * k) * y4)));
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y2 * ((c * y0) - (a * y1));
	t_2 = (t * j) - (y * k);
	t_3 = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	t_4 = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))));
	tmp = 0.0;
	if (y4 <= -2.45e+182)
		tmp = t_3;
	elseif (y4 <= -1.15e+144)
		tmp = x * t_1;
	elseif (y4 <= -3.3e+80)
		tmp = t_3;
	elseif (y4 <= 2.4e-225)
		tmp = t_4;
	elseif (y4 <= 5.9e-195)
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * ((x * y) - (z * t))) + (y5 * t_2)));
	elseif (y4 <= 3.7e+24)
		tmp = t_4;
	elseif (y4 <= 5e+181)
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4));
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y4 * N[(N[(N[(b * t$95$2), $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]}, Block[{t$95$4 = N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -2.45e+182], t$95$3, If[LessEqual[y4, -1.15e+144], N[(x * t$95$1), $MachinePrecision], If[LessEqual[y4, -3.3e+80], t$95$3, If[LessEqual[y4, 2.4e-225], t$95$4, If[LessEqual[y4, 5.9e-195], N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(c * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 3.7e+24], t$95$4, If[LessEqual[y4, 5e+181], N[(N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y4 < -2.45e182 or -1.1500000000000001e144 < y4 < -3.29999999999999991e80 or 5.0000000000000003e181 < y4

   1. Initial program 21.2%

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

   2. Taylor expanded in y4 around inf 71.5%

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

   if -2.45e182 < y4 < -1.1500000000000001e144

   1. Initial program 40.0%

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

   2. Taylor expanded in x around inf 60.2%

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

   3. Taylor expanded in y2 around inf 80.2%

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

   if -3.29999999999999991e80 < y4 < 2.39999999999999996e-225 or 5.90000000000000006e-195 < y4 < 3.69999999999999999e24

   1. Initial program 30.8%

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

   2. Taylor expanded in x around inf 53.3%

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

   if 2.39999999999999996e-225 < y4 < 5.90000000000000006e-195

   1. Initial program 53.5%

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

   2. Taylor expanded in i around -inf 61.6%

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

   if 3.69999999999999999e24 < y4 < 5.0000000000000003e181

   1. Initial program 23.3%

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

   2. Taylor expanded in y4 around inf 30.7%

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

      1. *-commutative 30.7%

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

      2. *-commutative 30.7%

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

   4. Simplified 30.7%

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

   5. Taylor expanded in k around inf 50.9%

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

      1. mul-1-neg 50.9%

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

      2. distribute-rgt-neg-in 50.9%

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

      3. associate-*r* 50.9%

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

      4. distribute-rgt-neg-in 50.9%

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

      5. *-commutative 50.9%

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

   7. Simplified 50.9%

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

   8. Taylor expanded in k around 0 53.9%

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

      1. associate-*r* 53.9%

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

      2. neg-mul-1 53.9%

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

   10. Simplified 53.9%

       \[\leadsto b \cdot \left(\left(y \cdot k\right) \cdot \left(-y4\right)\right) + \color{blue}{\left(-j\right) \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 59.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -2.45 \cdot 10^{+182}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -1.15 \cdot 10^{+144}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq -3.3 \cdot 10^{+80}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 2.4 \cdot 10^{-225}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 5.9 \cdot 10^{-195}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;y4 \leq 3.7 \cdot 10^{+24}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 5 \cdot 10^{+181}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 7: 34.3% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ t_2 := y0 \cdot y2 - y \cdot i\\ t_3 := b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ t_4 := \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{if}\;c \leq -9.5 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -1.75 \cdot 10^{-215}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 4.2 \cdot 10^{-229}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 9 \cdot 10^{-168}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 1.6 \cdot 10^{-17}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 1.9 \cdot 10^{+22}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{+44}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;c \leq 1.45 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.1 \cdot 10^{+201}:\\ \;\;\;\;\left(x \cdot c\right) \cdot t_2\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+250}:\\ \;\;\;\;t_4\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot t_2\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (- (* j (- (* i y1) (* b y0))) (* a (* y1 y2)))))
        (t_2 (- (* y0 y2) (* y i)))
        (t_3 (* b (* z (- (* k y0) (* t a)))))
        (t_4
         (-
          (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5)))
          (* b (* (* y k) y4)))))
   (if (<= c -9.5e-70)
     (* x (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1)))))
     (if (<= c -1.75e-215)
       (* y3 (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0)))))
       (if (<= c 4.2e-229)
         t_1
         (if (<= c 9e-168)
           t_3
           (if (<= c 1.6e-17)
             t_1
             (if (<= c 1.9e+22)
               t_3
               (if (<= c 2.4e+44)
                 t_4
                 (if (<= c 1.45e+116)
                   (* c (* y4 (- (* y y3) (* t y2))))
                   (if (<= c 2.1e+201)
                     (* (* x c) t_2)
                     (if (<= c 2.9e+250) t_4 (* x (* c 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 * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double t_2 = (y0 * y2) - (y * i);
	double t_3 = b * (z * ((k * y0) - (t * a)));
	double t_4 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	double tmp;
	if (c <= -9.5e-70) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -1.75e-215) {
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	} else if (c <= 4.2e-229) {
		tmp = t_1;
	} else if (c <= 9e-168) {
		tmp = t_3;
	} else if (c <= 1.6e-17) {
		tmp = t_1;
	} else if (c <= 1.9e+22) {
		tmp = t_3;
	} else if (c <= 2.4e+44) {
		tmp = t_4;
	} else if (c <= 1.45e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 2.1e+201) {
		tmp = (x * c) * t_2;
	} else if (c <= 2.9e+250) {
		tmp = t_4;
	} else {
		tmp = x * (c * 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) :: t_4
    real(8) :: tmp
    t_1 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
    t_2 = (y0 * y2) - (y * i)
    t_3 = b * (z * ((k * y0) - (t * a)))
    t_4 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4))
    if (c <= (-9.5d-70)) then
        tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
    else if (c <= (-1.75d-215)) then
        tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))))
    else if (c <= 4.2d-229) then
        tmp = t_1
    else if (c <= 9d-168) then
        tmp = t_3
    else if (c <= 1.6d-17) then
        tmp = t_1
    else if (c <= 1.9d+22) then
        tmp = t_3
    else if (c <= 2.4d+44) then
        tmp = t_4
    else if (c <= 1.45d+116) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= 2.1d+201) then
        tmp = (x * c) * t_2
    else if (c <= 2.9d+250) then
        tmp = t_4
    else
        tmp = x * (c * 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 * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double t_2 = (y0 * y2) - (y * i);
	double t_3 = b * (z * ((k * y0) - (t * a)));
	double t_4 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	double tmp;
	if (c <= -9.5e-70) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -1.75e-215) {
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	} else if (c <= 4.2e-229) {
		tmp = t_1;
	} else if (c <= 9e-168) {
		tmp = t_3;
	} else if (c <= 1.6e-17) {
		tmp = t_1;
	} else if (c <= 1.9e+22) {
		tmp = t_3;
	} else if (c <= 2.4e+44) {
		tmp = t_4;
	} else if (c <= 1.45e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 2.1e+201) {
		tmp = (x * c) * t_2;
	} else if (c <= 2.9e+250) {
		tmp = t_4;
	} else {
		tmp = x * (c * 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 * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
	t_2 = (y0 * y2) - (y * i)
	t_3 = b * (z * ((k * y0) - (t * a)))
	t_4 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4))
	tmp = 0
	if c <= -9.5e-70:
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
	elif c <= -1.75e-215:
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))))
	elif c <= 4.2e-229:
		tmp = t_1
	elif c <= 9e-168:
		tmp = t_3
	elif c <= 1.6e-17:
		tmp = t_1
	elif c <= 1.9e+22:
		tmp = t_3
	elif c <= 2.4e+44:
		tmp = t_4
	elif c <= 1.45e+116:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= 2.1e+201:
		tmp = (x * c) * t_2
	elif c <= 2.9e+250:
		tmp = t_4
	else:
		tmp = x * (c * 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(j * Float64(Float64(i * y1) - Float64(b * y0))) - Float64(a * Float64(y1 * y2))))
	t_2 = Float64(Float64(y0 * y2) - Float64(y * i))
	t_3 = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))))
	t_4 = Float64(Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5))) - Float64(b * Float64(Float64(y * k) * y4)))
	tmp = 0.0
	if (c <= -9.5e-70)
		tmp = Float64(x * Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))));
	elseif (c <= -1.75e-215)
		tmp = Float64(y3 * Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))));
	elseif (c <= 4.2e-229)
		tmp = t_1;
	elseif (c <= 9e-168)
		tmp = t_3;
	elseif (c <= 1.6e-17)
		tmp = t_1;
	elseif (c <= 1.9e+22)
		tmp = t_3;
	elseif (c <= 2.4e+44)
		tmp = t_4;
	elseif (c <= 1.45e+116)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= 2.1e+201)
		tmp = Float64(Float64(x * c) * t_2);
	elseif (c <= 2.9e+250)
		tmp = t_4;
	else
		tmp = Float64(x * Float64(c * 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 * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	t_2 = (y0 * y2) - (y * i);
	t_3 = b * (z * ((k * y0) - (t * a)));
	t_4 = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	tmp = 0.0;
	if (c <= -9.5e-70)
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	elseif (c <= -1.75e-215)
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	elseif (c <= 4.2e-229)
		tmp = t_1;
	elseif (c <= 9e-168)
		tmp = t_3;
	elseif (c <= 1.6e-17)
		tmp = t_1;
	elseif (c <= 1.9e+22)
		tmp = t_3;
	elseif (c <= 2.4e+44)
		tmp = t_4;
	elseif (c <= 1.45e+116)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= 2.1e+201)
		tmp = (x * c) * t_2;
	elseif (c <= 2.9e+250)
		tmp = t_4;
	else
		tmp = x * (c * 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[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -9.5e-70], N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.75e-215], N[(y3 * N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 4.2e-229], t$95$1, If[LessEqual[c, 9e-168], t$95$3, If[LessEqual[c, 1.6e-17], t$95$1, If[LessEqual[c, 1.9e+22], t$95$3, If[LessEqual[c, 2.4e+44], t$95$4, If[LessEqual[c, 1.45e+116], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.1e+201], N[(N[(x * c), $MachinePrecision] * t$95$2), $MachinePrecision], If[LessEqual[c, 2.9e+250], t$95$4, N[(x * N[(c * t$95$2), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if c < -9.4999999999999994e-70

   1. Initial program 19.2%

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

   2. Taylor expanded in x around inf 53.8%

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

   3. Taylor expanded in j around 0 52.2%

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

   if -9.4999999999999994e-70 < c < -1.7500000000000001e-215

   1. Initial program 44.3%

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

   2. Taylor expanded in y3 around -inf 52.7%

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

   3. Taylor expanded in y around 0 49.3%

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

   if -1.7500000000000001e-215 < c < 4.19999999999999967e-229 or 9.0000000000000002e-168 < c < 1.6000000000000001e-17

   1. Initial program 46.2%

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

   2. Taylor expanded in x around inf 43.7%

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

   3. Taylor expanded in y around 0 42.1%

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

      1. *-commutative 42.1%

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

      2. *-commutative 42.1%

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

   5. Simplified 42.1%

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

   6. Taylor expanded in c around 0 47.4%

      \[\leadsto x \cdot \left(\color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 47.4%

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

      2. distribute-rgt-neg-in 47.4%

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

      3. distribute-rgt-neg-in 47.4%

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

   8. Simplified 47.4%

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

   if 4.19999999999999967e-229 < c < 9.0000000000000002e-168 or 1.6000000000000001e-17 < c < 1.9000000000000002e22

   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. Taylor expanded in b around inf 58.2%

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

   3. Taylor expanded in z around -inf 62.1%

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

   if 1.9000000000000002e22 < c < 2.40000000000000013e44 or 2.0999999999999999e201 < c < 2.90000000000000009e250

   1. Initial program 43.8%

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

   2. Taylor expanded in y4 around inf 57.0%

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

      1. *-commutative 57.0%

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

      2. *-commutative 57.0%

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

   4. Simplified 57.0%

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

   5. Taylor expanded in k around inf 69.6%

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

      1. mul-1-neg 69.6%

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

      2. distribute-rgt-neg-in 69.6%

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

      3. associate-*r* 69.6%

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

      4. distribute-rgt-neg-in 69.6%

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

      5. *-commutative 69.6%

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

   7. Simplified 69.6%

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

   if 2.40000000000000013e44 < c < 1.4500000000000001e116

   1. Initial program 13.3%

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

   2. Taylor expanded in y4 around inf 27.2%

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

      1. *-commutative 27.2%

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

      2. *-commutative 27.2%

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

   4. Simplified 27.2%

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

   5. Taylor expanded in c around inf 67.2%

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

   if 1.4500000000000001e116 < c < 2.0999999999999999e201

   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. Taylor expanded in x around inf 50.9%

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

   3. Taylor expanded in c around inf 51.1%

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

      1. associate-*r* 57.8%

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

      2. +-commutative 57.8%

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

      3. mul-1-neg 57.8%

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

      4. unsub-neg 57.8%

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

      5. *-commutative 57.8%

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

   5. Simplified 57.8%

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

   if 2.90000000000000009e250 < c

   1. Initial program 17.9%

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

   2. Taylor expanded in x around inf 41.6%

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

   3. Taylor expanded in c around inf 82.5%

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

      1. +-commutative 82.5%

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

      2. mul-1-neg 82.5%

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

      3. unsub-neg 82.5%

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

      4. *-commutative 82.5%

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

   5. Simplified 82.5%

      \[\leadsto x \cdot \color{blue}{\left(c \cdot \left(y2 \cdot y0 - i \cdot y\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 56.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -9.5 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -1.75 \cdot 10^{-215}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 4.2 \cdot 10^{-229}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 9 \cdot 10^{-168}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 1.6 \cdot 10^{-17}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.9 \cdot 10^{+22}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{+44}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{elif}\;c \leq 1.45 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.1 \cdot 10^{+201}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+250}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 8: 33.1% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot y2 - y \cdot i\\ \mathbf{if}\;c \leq -3.2 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -5.4 \cdot 10^{-212}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 3.4 \cdot 10^{-228}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 7.6 \cdot 10^{-168}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 3.4 \cdot 10^{-70}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 5.5 \cdot 10^{+44}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;c \leq 5.7 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.95 \cdot 10^{+195}:\\ \;\;\;\;\left(x \cdot c\right) \cdot t_1\\ \mathbf{elif}\;c \leq 4.8 \cdot 10^{+250}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot t_1\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y0 y2) (* y i))))
   (if (<= c -3.2e-70)
     (* x (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1)))))
     (if (<= c -5.4e-212)
       (* y3 (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0)))))
       (if (<= c 3.4e-228)
         (* x (- (* j (- (* i y1) (* b y0))) (* a (* y1 y2))))
         (if (<= c 7.6e-168)
           (* b (* z (- (* k y0) (* t a))))
           (if (<= c 3.4e-70)
             (* c (* y4 (* y y3)))
             (if (<= c 5.5e+44)
               (*
                b
                (+
                 (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
                 (* y0 (- (* z k) (* x j)))))
               (if (<= c 5.7e+116)
                 (* c (* y4 (- (* y y3) (* t y2))))
                 (if (<= c 1.95e+195)
                   (* (* x c) t_1)
                   (if (<= c 4.8e+250)
                     (-
                      (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5)))
                      (* b (* (* y k) y4)))
                     (* x (* c 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 * y2) - (y * i);
	double tmp;
	if (c <= -3.2e-70) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -5.4e-212) {
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	} else if (c <= 3.4e-228) {
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	} else if (c <= 7.6e-168) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (c <= 3.4e-70) {
		tmp = c * (y4 * (y * y3));
	} else if (c <= 5.5e+44) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (c <= 5.7e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 1.95e+195) {
		tmp = (x * c) * t_1;
	} else if (c <= 4.8e+250) {
		tmp = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	} else {
		tmp = x * (c * 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 * y2) - (y * i)
    if (c <= (-3.2d-70)) then
        tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
    else if (c <= (-5.4d-212)) then
        tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))))
    else if (c <= 3.4d-228) then
        tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
    else if (c <= 7.6d-168) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (c <= 3.4d-70) then
        tmp = c * (y4 * (y * y3))
    else if (c <= 5.5d+44) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else if (c <= 5.7d+116) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= 1.95d+195) then
        tmp = (x * c) * t_1
    else if (c <= 4.8d+250) then
        tmp = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4))
    else
        tmp = x * (c * 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 * y2) - (y * i);
	double tmp;
	if (c <= -3.2e-70) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -5.4e-212) {
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	} else if (c <= 3.4e-228) {
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	} else if (c <= 7.6e-168) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (c <= 3.4e-70) {
		tmp = c * (y4 * (y * y3));
	} else if (c <= 5.5e+44) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (c <= 5.7e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 1.95e+195) {
		tmp = (x * c) * t_1;
	} else if (c <= 4.8e+250) {
		tmp = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	} else {
		tmp = x * (c * 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 * y2) - (y * i)
	tmp = 0
	if c <= -3.2e-70:
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
	elif c <= -5.4e-212:
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))))
	elif c <= 3.4e-228:
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
	elif c <= 7.6e-168:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif c <= 3.4e-70:
		tmp = c * (y4 * (y * y3))
	elif c <= 5.5e+44:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	elif c <= 5.7e+116:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= 1.95e+195:
		tmp = (x * c) * t_1
	elif c <= 4.8e+250:
		tmp = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4))
	else:
		tmp = x * (c * t_1)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y0 * y2) - Float64(y * i))
	tmp = 0.0
	if (c <= -3.2e-70)
		tmp = Float64(x * Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))));
	elseif (c <= -5.4e-212)
		tmp = Float64(y3 * Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))));
	elseif (c <= 3.4e-228)
		tmp = Float64(x * Float64(Float64(j * Float64(Float64(i * y1) - Float64(b * y0))) - Float64(a * Float64(y1 * y2))));
	elseif (c <= 7.6e-168)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (c <= 3.4e-70)
		tmp = Float64(c * Float64(y4 * Float64(y * y3)));
	elseif (c <= 5.5e+44)
		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 (c <= 5.7e+116)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= 1.95e+195)
		tmp = Float64(Float64(x * c) * t_1);
	elseif (c <= 4.8e+250)
		tmp = Float64(Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5))) - Float64(b * Float64(Float64(y * k) * y4)));
	else
		tmp = Float64(x * Float64(c * 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 * y2) - (y * i);
	tmp = 0.0;
	if (c <= -3.2e-70)
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	elseif (c <= -5.4e-212)
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	elseif (c <= 3.4e-228)
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	elseif (c <= 7.6e-168)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (c <= 3.4e-70)
		tmp = c * (y4 * (y * y3));
	elseif (c <= 5.5e+44)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	elseif (c <= 5.7e+116)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= 1.95e+195)
		tmp = (x * c) * t_1;
	elseif (c <= 4.8e+250)
		tmp = (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))) - (b * ((y * k) * y4));
	else
		tmp = x * (c * t_1);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -3.2e-70], N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -5.4e-212], N[(y3 * N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.4e-228], N[(x * N[(N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 7.6e-168], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.4e-70], N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5.5e+44], 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[c, 5.7e+116], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.95e+195], N[(N[(x * c), $MachinePrecision] * t$95$1), $MachinePrecision], If[LessEqual[c, 4.8e+250], N[(N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x * N[(c * t$95$1), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if c < -3.1999999999999997e-70

   1. Initial program 19.2%

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

   2. Taylor expanded in x around inf 53.8%

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

   3. Taylor expanded in j around 0 52.2%

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

   if -3.1999999999999997e-70 < c < -5.39999999999999962e-212

   1. Initial program 44.3%

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

   2. Taylor expanded in y3 around -inf 52.7%

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

   3. Taylor expanded in y around 0 49.3%

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

   if -5.39999999999999962e-212 < c < 3.39999999999999991e-228

   1. Initial program 49.9%

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

   2. Taylor expanded in x around inf 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. Taylor expanded in y around 0 47.8%

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

      1. *-commutative 47.8%

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

      2. *-commutative 47.8%

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

   5. Simplified 47.8%

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

   6. Taylor expanded in c around 0 54.3%

      \[\leadsto x \cdot \left(\color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 54.3%

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

      2. distribute-rgt-neg-in 54.3%

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

      3. distribute-rgt-neg-in 54.3%

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

   8. Simplified 54.3%

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

   if 3.39999999999999991e-228 < c < 7.6000000000000001e-168

   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. Taylor expanded in b around inf 55.2%

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

   3. Taylor expanded in z around -inf 73.3%

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

   if 7.6000000000000001e-168 < c < 3.39999999999999995e-70

   1. Initial program 42.9%

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

   2. Taylor expanded in y4 around inf 15.3%

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

      1. *-commutative 15.3%

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

      2. *-commutative 15.3%

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

   4. Simplified 15.3%

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

   5. Taylor expanded in y around inf 30.9%

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

      1. associate-*r* 17.6%

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

      2. distribute-lft-out-- 17.6%

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

   7. Simplified 17.6%

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

   8. Taylor expanded in b around 0 30.1%

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

      1. associate-*r* 43.7%

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

      2. *-commutative 43.7%

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

   10. Simplified 43.7%

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

   if 3.39999999999999995e-70 < c < 5.5000000000000001e44

   1. Initial program 33.3%

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

   2. Taylor expanded in b around inf 48.3%

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

   if 5.5000000000000001e44 < c < 5.69999999999999983e116

   1. Initial program 13.3%

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

   2. Taylor expanded in y4 around inf 27.2%

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

      1. *-commutative 27.2%

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

      2. *-commutative 27.2%

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

   4. Simplified 27.2%

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

   5. Taylor expanded in c around inf 67.2%

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

   if 5.69999999999999983e116 < c < 1.9499999999999999e195

   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. Taylor expanded in x around inf 50.9%

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

   3. Taylor expanded in c around inf 51.1%

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

      1. associate-*r* 57.8%

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

      2. +-commutative 57.8%

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

      3. mul-1-neg 57.8%

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

      4. unsub-neg 57.8%

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

      5. *-commutative 57.8%

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

   5. Simplified 57.8%

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

   if 1.9499999999999999e195 < c < 4.80000000000000026e250

   1. Initial program 30.0%

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

   2. Taylor expanded in y4 around inf 60.1%

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

      1. *-commutative 60.1%

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

      2. *-commutative 60.1%

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

   4. Simplified 60.1%

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

   5. Taylor expanded in k around inf 70.4%

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

      1. mul-1-neg 70.4%

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

      2. distribute-rgt-neg-in 70.4%

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

      3. associate-*r* 70.4%

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

      4. distribute-rgt-neg-in 70.4%

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

      5. *-commutative 70.4%

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

   7. Simplified 70.4%

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

   if 4.80000000000000026e250 < c

   1. Initial program 17.9%

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

   2. Taylor expanded in x around inf 41.6%

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

   3. Taylor expanded in c around inf 82.5%

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

      1. +-commutative 82.5%

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

      2. mul-1-neg 82.5%

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

      3. unsub-neg 82.5%

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

      4. *-commutative 82.5%

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

   5. Simplified 82.5%

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

4. Final simplification 56.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -3.2 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -5.4 \cdot 10^{-212}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 3.4 \cdot 10^{-228}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 7.6 \cdot 10^{-168}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 3.4 \cdot 10^{-70}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 5.5 \cdot 10^{+44}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;c \leq 5.7 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.95 \cdot 10^{+195}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq 4.8 \cdot 10^{+250}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 9: 41.7% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\\ t_2 := y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{if}\;y4 \leq -2.65 \cdot 10^{+182}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq -1.1 \cdot 10^{+144}:\\ \;\;\;\;x \cdot t_1\\ \mathbf{elif}\;y4 \leq -1.65 \cdot 10^{+81}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq 4.2 \cdot 10^{+24}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + t_1\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 6.2 \cdot 10^{+180}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y2 (- (* c y0) (* a y1))))
        (t_2
         (*
          y4
          (+
           (+ (* b (- (* t j) (* y k))) (* y1 (- (* k y2) (* j y3))))
           (* c (- (* y y3) (* t y2)))))))
   (if (<= y4 -2.65e+182)
     t_2
     (if (<= y4 -1.1e+144)
       (* x t_1)
       (if (<= y4 -1.65e+81)
         t_2
         (if (<= y4 4.2e+24)
           (*
            x
            (+ (+ (* y (- (* a b) (* c i))) t_1) (* j (- (* i y1) (* b y0)))))
           (if (<= y4 6.2e+180)
             (- (* j (* y3 (- (* y0 y5) (* y1 y4)))) (* b (* (* y k) y4)))
             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 = y2 * ((c * y0) - (a * y1));
	double t_2 = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double tmp;
	if (y4 <= -2.65e+182) {
		tmp = t_2;
	} else if (y4 <= -1.1e+144) {
		tmp = x * t_1;
	} else if (y4 <= -1.65e+81) {
		tmp = t_2;
	} else if (y4 <= 4.2e+24) {
		tmp = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))));
	} else if (y4 <= 6.2e+180) {
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y2 * ((c * y0) - (a * y1))
    t_2 = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    if (y4 <= (-2.65d+182)) then
        tmp = t_2
    else if (y4 <= (-1.1d+144)) then
        tmp = x * t_1
    else if (y4 <= (-1.65d+81)) then
        tmp = t_2
    else if (y4 <= 4.2d+24) then
        tmp = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))))
    else if (y4 <= 6.2d+180) then
        tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4))
    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 = y2 * ((c * y0) - (a * y1));
	double t_2 = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double tmp;
	if (y4 <= -2.65e+182) {
		tmp = t_2;
	} else if (y4 <= -1.1e+144) {
		tmp = x * t_1;
	} else if (y4 <= -1.65e+81) {
		tmp = t_2;
	} else if (y4 <= 4.2e+24) {
		tmp = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))));
	} else if (y4 <= 6.2e+180) {
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4));
	} 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 = y2 * ((c * y0) - (a * y1))
	t_2 = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	tmp = 0
	if y4 <= -2.65e+182:
		tmp = t_2
	elif y4 <= -1.1e+144:
		tmp = x * t_1
	elif y4 <= -1.65e+81:
		tmp = t_2
	elif y4 <= 4.2e+24:
		tmp = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))))
	elif y4 <= 6.2e+180:
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4))
	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(y2 * Float64(Float64(c * y0) - Float64(a * y1)))
	t_2 = Float64(y4 * Float64(Float64(Float64(b * Float64(Float64(t * j) - Float64(y * k))) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))))
	tmp = 0.0
	if (y4 <= -2.65e+182)
		tmp = t_2;
	elseif (y4 <= -1.1e+144)
		tmp = Float64(x * t_1);
	elseif (y4 <= -1.65e+81)
		tmp = t_2;
	elseif (y4 <= 4.2e+24)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + t_1) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (y4 <= 6.2e+180)
		tmp = Float64(Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) - Float64(b * Float64(Float64(y * k) * y4)));
	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 = y2 * ((c * y0) - (a * y1));
	t_2 = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	tmp = 0.0;
	if (y4 <= -2.65e+182)
		tmp = t_2;
	elseif (y4 <= -1.1e+144)
		tmp = x * t_1;
	elseif (y4 <= -1.65e+81)
		tmp = t_2;
	elseif (y4 <= 4.2e+24)
		tmp = x * (((y * ((a * b) - (c * i))) + t_1) + (j * ((i * y1) - (b * y0))));
	elseif (y4 <= 6.2e+180)
		tmp = (j * (y3 * ((y0 * y5) - (y1 * y4)))) - (b * ((y * k) * y4));
	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[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y4 * N[(N[(N[(b * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -2.65e+182], t$95$2, If[LessEqual[y4, -1.1e+144], N[(x * t$95$1), $MachinePrecision], If[LessEqual[y4, -1.65e+81], t$95$2, If[LessEqual[y4, 4.2e+24], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 6.2e+180], N[(N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]

Derivation

1. Split input into 4 regimes

2. if y4 < -2.65e182 or -1.09999999999999994e144 < y4 < -1.65e81 or 6.19999999999999997e180 < y4

   1. Initial program 21.2%

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

   2. Taylor expanded in y4 around inf 71.5%

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

   if -2.65e182 < y4 < -1.09999999999999994e144

   1. Initial program 40.0%

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

   2. Taylor expanded in x around inf 60.2%

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

   3. Taylor expanded in y2 around inf 80.2%

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

   if -1.65e81 < y4 < 4.2000000000000003e24

   1. Initial program 33.0%

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

   2. Taylor expanded in x around inf 50.2%

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

   if 4.2000000000000003e24 < y4 < 6.19999999999999997e180

   1. Initial program 23.3%

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

   2. Taylor expanded in y4 around inf 30.7%

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

      1. *-commutative 30.7%

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

      2. *-commutative 30.7%

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

   4. Simplified 30.7%

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

   5. Taylor expanded in k around inf 50.9%

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

      1. mul-1-neg 50.9%

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

      2. distribute-rgt-neg-in 50.9%

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

      3. associate-*r* 50.9%

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

      4. distribute-rgt-neg-in 50.9%

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

      5. *-commutative 50.9%

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

   7. Simplified 50.9%

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

   8. Taylor expanded in k around 0 53.9%

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

      1. associate-*r* 53.9%

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

      2. neg-mul-1 53.9%

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

   10. Simplified 53.9%

       \[\leadsto b \cdot \left(\left(y \cdot k\right) \cdot \left(-y4\right)\right) + \color{blue}{\left(-j\right) \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 56.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -2.65 \cdot 10^{+182}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -1.1 \cdot 10^{+144}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y4 \leq -1.65 \cdot 10^{+81}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 4.2 \cdot 10^{+24}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 6.2 \cdot 10^{+180}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 10: 37.1% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot b - c \cdot i\\ t_2 := x \cdot y - z \cdot t\\ t_3 := c \cdot y0 - a \cdot y1\\ t_4 := z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(t \cdot t_1 + y3 \cdot t_3\right)\right)\\ t_5 := t \cdot j - y \cdot k\\ t_6 := y \cdot t_1 + y2 \cdot t_3\\ \mathbf{if}\;a \leq -9.2 \cdot 10^{+101}:\\ \;\;\;\;b \cdot \left(\left(a \cdot t_2 + y4 \cdot t_5\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq -1.35 \cdot 10^{-140}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot t_2 + y5 \cdot t_5\right)\right)\\ \mathbf{elif}\;a \leq -2.05 \cdot 10^{-235}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 680000000:\\ \;\;\;\;x \cdot \left(t_6 + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq 1.6 \cdot 10^{+113}:\\ \;\;\;\;t_4\\ \mathbf{else}:\\ \;\;\;\;x \cdot t_6\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a b) (* c i)))
        (t_2 (- (* x y) (* z t)))
        (t_3 (- (* c y0) (* a y1)))
        (t_4 (* z (- (* k (- (* b y0) (* i y1))) (+ (* t t_1) (* y3 t_3)))))
        (t_5 (- (* t j) (* y k)))
        (t_6 (+ (* y t_1) (* y2 t_3))))
   (if (<= a -9.2e+101)
     (* b (+ (+ (* a t_2) (* y4 t_5)) (* y0 (- (* z k) (* x j)))))
     (if (<= a -1.35e-140)
       (* i (- (* y1 (- (* x j) (* z k))) (+ (* c t_2) (* y5 t_5))))
       (if (<= a -2.05e-235)
         t_4
         (if (<= a 680000000.0)
           (* x (+ t_6 (* j (- (* i y1) (* b y0)))))
           (if (<= a 1.6e+113) t_4 (* x t_6))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * b) - (c * i);
	double t_2 = (x * y) - (z * t);
	double t_3 = (c * y0) - (a * y1);
	double t_4 = z * ((k * ((b * y0) - (i * y1))) - ((t * t_1) + (y3 * t_3)));
	double t_5 = (t * j) - (y * k);
	double t_6 = (y * t_1) + (y2 * t_3);
	double tmp;
	if (a <= -9.2e+101) {
		tmp = b * (((a * t_2) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))));
	} else if (a <= -1.35e-140) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_2) + (y5 * t_5)));
	} else if (a <= -2.05e-235) {
		tmp = t_4;
	} else if (a <= 680000000.0) {
		tmp = x * (t_6 + (j * ((i * y1) - (b * y0))));
	} else if (a <= 1.6e+113) {
		tmp = t_4;
	} else {
		tmp = x * t_6;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = (a * b) - (c * i)
    t_2 = (x * y) - (z * t)
    t_3 = (c * y0) - (a * y1)
    t_4 = z * ((k * ((b * y0) - (i * y1))) - ((t * t_1) + (y3 * t_3)))
    t_5 = (t * j) - (y * k)
    t_6 = (y * t_1) + (y2 * t_3)
    if (a <= (-9.2d+101)) then
        tmp = b * (((a * t_2) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))))
    else if (a <= (-1.35d-140)) then
        tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_2) + (y5 * t_5)))
    else if (a <= (-2.05d-235)) then
        tmp = t_4
    else if (a <= 680000000.0d0) then
        tmp = x * (t_6 + (j * ((i * y1) - (b * y0))))
    else if (a <= 1.6d+113) then
        tmp = t_4
    else
        tmp = x * t_6
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * b) - (c * i);
	double t_2 = (x * y) - (z * t);
	double t_3 = (c * y0) - (a * y1);
	double t_4 = z * ((k * ((b * y0) - (i * y1))) - ((t * t_1) + (y3 * t_3)));
	double t_5 = (t * j) - (y * k);
	double t_6 = (y * t_1) + (y2 * t_3);
	double tmp;
	if (a <= -9.2e+101) {
		tmp = b * (((a * t_2) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))));
	} else if (a <= -1.35e-140) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_2) + (y5 * t_5)));
	} else if (a <= -2.05e-235) {
		tmp = t_4;
	} else if (a <= 680000000.0) {
		tmp = x * (t_6 + (j * ((i * y1) - (b * y0))));
	} else if (a <= 1.6e+113) {
		tmp = t_4;
	} else {
		tmp = x * t_6;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (a * b) - (c * i)
	t_2 = (x * y) - (z * t)
	t_3 = (c * y0) - (a * y1)
	t_4 = z * ((k * ((b * y0) - (i * y1))) - ((t * t_1) + (y3 * t_3)))
	t_5 = (t * j) - (y * k)
	t_6 = (y * t_1) + (y2 * t_3)
	tmp = 0
	if a <= -9.2e+101:
		tmp = b * (((a * t_2) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))))
	elif a <= -1.35e-140:
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_2) + (y5 * t_5)))
	elif a <= -2.05e-235:
		tmp = t_4
	elif a <= 680000000.0:
		tmp = x * (t_6 + (j * ((i * y1) - (b * y0))))
	elif a <= 1.6e+113:
		tmp = t_4
	else:
		tmp = x * t_6
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(a * b) - Float64(c * i))
	t_2 = Float64(Float64(x * y) - Float64(z * t))
	t_3 = Float64(Float64(c * y0) - Float64(a * y1))
	t_4 = Float64(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(Float64(t * t_1) + Float64(y3 * t_3))))
	t_5 = Float64(Float64(t * j) - Float64(y * k))
	t_6 = Float64(Float64(y * t_1) + Float64(y2 * t_3))
	tmp = 0.0
	if (a <= -9.2e+101)
		tmp = Float64(b * Float64(Float64(Float64(a * t_2) + Float64(y4 * t_5)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (a <= -1.35e-140)
		tmp = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) - Float64(Float64(c * t_2) + Float64(y5 * t_5))));
	elseif (a <= -2.05e-235)
		tmp = t_4;
	elseif (a <= 680000000.0)
		tmp = Float64(x * Float64(t_6 + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (a <= 1.6e+113)
		tmp = t_4;
	else
		tmp = Float64(x * t_6);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (a * b) - (c * i);
	t_2 = (x * y) - (z * t);
	t_3 = (c * y0) - (a * y1);
	t_4 = z * ((k * ((b * y0) - (i * y1))) - ((t * t_1) + (y3 * t_3)));
	t_5 = (t * j) - (y * k);
	t_6 = (y * t_1) + (y2 * t_3);
	tmp = 0.0;
	if (a <= -9.2e+101)
		tmp = b * (((a * t_2) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))));
	elseif (a <= -1.35e-140)
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_2) + (y5 * t_5)));
	elseif (a <= -2.05e-235)
		tmp = t_4;
	elseif (a <= 680000000.0)
		tmp = x * (t_6 + (j * ((i * y1) - (b * y0))));
	elseif (a <= 1.6e+113)
		tmp = t_4;
	else
		tmp = x * t_6;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t * t$95$1), $MachinePrecision] + N[(y3 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(y * t$95$1), $MachinePrecision] + N[(y2 * t$95$3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -9.2e+101], N[(b * N[(N[(N[(a * t$95$2), $MachinePrecision] + N[(y4 * t$95$5), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.35e-140], N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(c * t$95$2), $MachinePrecision] + N[(y5 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -2.05e-235], t$95$4, If[LessEqual[a, 680000000.0], N[(x * N[(t$95$6 + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.6e+113], t$95$4, N[(x * t$95$6), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if a < -9.2000000000000005e101

   1. Initial program 27.9%

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

   2. Taylor expanded in b around inf 54.3%

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

   if -9.2000000000000005e101 < a < -1.35e-140

   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. Taylor expanded in i around -inf 57.6%

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

   if -1.35e-140 < a < -2.04999999999999998e-235 or 6.8e8 < a < 1.5999999999999999e113

   1. Initial program 30.7%

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

   2. Taylor expanded in z around -inf 62.3%

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

   if -2.04999999999999998e-235 < a < 6.8e8

   1. Initial program 27.0%

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

   2. Taylor expanded in x around inf 49.6%

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

   if 1.5999999999999999e113 < a

   1. Initial program 23.1%

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

   2. Taylor expanded in x around inf 64.3%

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

   3. Taylor expanded in j around 0 69.4%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 57.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -9.2 \cdot 10^{+101}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq -1.35 \cdot 10^{-140}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;a \leq -2.05 \cdot 10^{-235}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)\\ \mathbf{elif}\;a \leq 680000000:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq 1.6 \cdot 10^{+113}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \end{array} \]

Alternative 11: 33.6% accurate, 2.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ t_2 := x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ t_3 := b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ t_4 := y0 \cdot y2 - y \cdot i\\ \mathbf{if}\;c \leq -7.6 \cdot 10^{-73}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -3 \cdot 10^{-140}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -3.2 \cdot 10^{-218}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;c \leq 2.26 \cdot 10^{-228}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq 1.45 \cdot 10^{-167}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{-23}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq 3.7 \cdot 10^{+27}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 1.75 \cdot 10^{+44}:\\ \;\;\;\;t_1 - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{elif}\;c \leq 1.55 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.55 \cdot 10^{+187}:\\ \;\;\;\;\left(x \cdot c\right) \cdot t_4\\ \mathbf{elif}\;c \leq 1.1 \cdot 10^{+251}:\\ \;\;\;\;\left(y \cdot y4\right) \cdot \left(c \cdot y3 - b \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot t_4\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y3 (- (* y0 y5) (* y1 y4)))))
        (t_2 (* x (- (* j (- (* i y1) (* b y0))) (* a (* y1 y2)))))
        (t_3 (* b (* z (- (* k y0) (* t a)))))
        (t_4 (- (* y0 y2) (* y i))))
   (if (<= c -7.6e-73)
     (* x (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1)))))
     (if (<= c -3e-140)
       t_1
       (if (<= c -3.2e-218)
         (* a (* b (- (* x y) (* z t))))
         (if (<= c 2.26e-228)
           t_2
           (if (<= c 1.45e-167)
             t_3
             (if (<= c 5.8e-23)
               t_2
               (if (<= c 3.7e+27)
                 t_3
                 (if (<= c 1.75e+44)
                   (- t_1 (* b (* (* y k) y4)))
                   (if (<= c 1.55e+116)
                     (* c (* y4 (- (* y y3) (* t y2))))
                     (if (<= c 2.55e+187)
                       (* (* x c) t_4)
                       (if (<= c 1.1e+251)
                         (* (* y y4) (- (* c y3) (* b k)))
                         (* x (* c t_4)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	double t_2 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double t_3 = b * (z * ((k * y0) - (t * a)));
	double t_4 = (y0 * y2) - (y * i);
	double tmp;
	if (c <= -7.6e-73) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -3e-140) {
		tmp = t_1;
	} else if (c <= -3.2e-218) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (c <= 2.26e-228) {
		tmp = t_2;
	} else if (c <= 1.45e-167) {
		tmp = t_3;
	} else if (c <= 5.8e-23) {
		tmp = t_2;
	} else if (c <= 3.7e+27) {
		tmp = t_3;
	} else if (c <= 1.75e+44) {
		tmp = t_1 - (b * ((y * k) * y4));
	} else if (c <= 1.55e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 2.55e+187) {
		tmp = (x * c) * t_4;
	} else if (c <= 1.1e+251) {
		tmp = (y * y4) * ((c * y3) - (b * k));
	} else {
		tmp = x * (c * t_4);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)))
    t_2 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
    t_3 = b * (z * ((k * y0) - (t * a)))
    t_4 = (y0 * y2) - (y * i)
    if (c <= (-7.6d-73)) then
        tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
    else if (c <= (-3d-140)) then
        tmp = t_1
    else if (c <= (-3.2d-218)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (c <= 2.26d-228) then
        tmp = t_2
    else if (c <= 1.45d-167) then
        tmp = t_3
    else if (c <= 5.8d-23) then
        tmp = t_2
    else if (c <= 3.7d+27) then
        tmp = t_3
    else if (c <= 1.75d+44) then
        tmp = t_1 - (b * ((y * k) * y4))
    else if (c <= 1.55d+116) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= 2.55d+187) then
        tmp = (x * c) * t_4
    else if (c <= 1.1d+251) then
        tmp = (y * y4) * ((c * y3) - (b * k))
    else
        tmp = x * (c * t_4)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	double t_2 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double t_3 = b * (z * ((k * y0) - (t * a)));
	double t_4 = (y0 * y2) - (y * i);
	double tmp;
	if (c <= -7.6e-73) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -3e-140) {
		tmp = t_1;
	} else if (c <= -3.2e-218) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (c <= 2.26e-228) {
		tmp = t_2;
	} else if (c <= 1.45e-167) {
		tmp = t_3;
	} else if (c <= 5.8e-23) {
		tmp = t_2;
	} else if (c <= 3.7e+27) {
		tmp = t_3;
	} else if (c <= 1.75e+44) {
		tmp = t_1 - (b * ((y * k) * y4));
	} else if (c <= 1.55e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 2.55e+187) {
		tmp = (x * c) * t_4;
	} else if (c <= 1.1e+251) {
		tmp = (y * y4) * ((c * y3) - (b * k));
	} else {
		tmp = x * (c * t_4);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)))
	t_2 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
	t_3 = b * (z * ((k * y0) - (t * a)))
	t_4 = (y0 * y2) - (y * i)
	tmp = 0
	if c <= -7.6e-73:
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
	elif c <= -3e-140:
		tmp = t_1
	elif c <= -3.2e-218:
		tmp = a * (b * ((x * y) - (z * t)))
	elif c <= 2.26e-228:
		tmp = t_2
	elif c <= 1.45e-167:
		tmp = t_3
	elif c <= 5.8e-23:
		tmp = t_2
	elif c <= 3.7e+27:
		tmp = t_3
	elif c <= 1.75e+44:
		tmp = t_1 - (b * ((y * k) * y4))
	elif c <= 1.55e+116:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= 2.55e+187:
		tmp = (x * c) * t_4
	elif c <= 1.1e+251:
		tmp = (y * y4) * ((c * y3) - (b * k))
	else:
		tmp = x * (c * t_4)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))))
	t_2 = Float64(x * Float64(Float64(j * Float64(Float64(i * y1) - Float64(b * y0))) - Float64(a * Float64(y1 * y2))))
	t_3 = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))))
	t_4 = Float64(Float64(y0 * y2) - Float64(y * i))
	tmp = 0.0
	if (c <= -7.6e-73)
		tmp = Float64(x * Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))));
	elseif (c <= -3e-140)
		tmp = t_1;
	elseif (c <= -3.2e-218)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (c <= 2.26e-228)
		tmp = t_2;
	elseif (c <= 1.45e-167)
		tmp = t_3;
	elseif (c <= 5.8e-23)
		tmp = t_2;
	elseif (c <= 3.7e+27)
		tmp = t_3;
	elseif (c <= 1.75e+44)
		tmp = Float64(t_1 - Float64(b * Float64(Float64(y * k) * y4)));
	elseif (c <= 1.55e+116)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= 2.55e+187)
		tmp = Float64(Float64(x * c) * t_4);
	elseif (c <= 1.1e+251)
		tmp = Float64(Float64(y * y4) * Float64(Float64(c * y3) - Float64(b * k)));
	else
		tmp = Float64(x * Float64(c * t_4));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	t_2 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	t_3 = b * (z * ((k * y0) - (t * a)));
	t_4 = (y0 * y2) - (y * i);
	tmp = 0.0;
	if (c <= -7.6e-73)
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	elseif (c <= -3e-140)
		tmp = t_1;
	elseif (c <= -3.2e-218)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (c <= 2.26e-228)
		tmp = t_2;
	elseif (c <= 1.45e-167)
		tmp = t_3;
	elseif (c <= 5.8e-23)
		tmp = t_2;
	elseif (c <= 3.7e+27)
		tmp = t_3;
	elseif (c <= 1.75e+44)
		tmp = t_1 - (b * ((y * k) * y4));
	elseif (c <= 1.55e+116)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= 2.55e+187)
		tmp = (x * c) * t_4;
	elseif (c <= 1.1e+251)
		tmp = (y * y4) * ((c * y3) - (b * k));
	else
		tmp = x * (c * t_4);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -7.6e-73], N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -3e-140], t$95$1, If[LessEqual[c, -3.2e-218], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.26e-228], t$95$2, If[LessEqual[c, 1.45e-167], t$95$3, If[LessEqual[c, 5.8e-23], t$95$2, If[LessEqual[c, 3.7e+27], t$95$3, If[LessEqual[c, 1.75e+44], N[(t$95$1 - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.55e+116], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.55e+187], N[(N[(x * c), $MachinePrecision] * t$95$4), $MachinePrecision], If[LessEqual[c, 1.1e+251], N[(N[(y * y4), $MachinePrecision] * N[(N[(c * y3), $MachinePrecision] - N[(b * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x * N[(c * t$95$4), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if c < -7.6000000000000005e-73

   1. Initial program 19.2%

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

   2. Taylor expanded in x around inf 53.8%

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

   3. Taylor expanded in j around 0 52.2%

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

   if -7.6000000000000005e-73 < c < -3.00000000000000018e-140

   1. Initial program 45.3%

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

   2. Taylor expanded in y3 around -inf 72.6%

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

   3. Taylor expanded in j around inf 56.6%

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

   if -3.00000000000000018e-140 < c < -3.2000000000000001e-218

   1. Initial program 43.4%

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

   2. Taylor expanded in b around inf 43.6%

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

   3. Taylor expanded in a around inf 50.7%

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

   if -3.2000000000000001e-218 < c < 2.26000000000000001e-228 or 1.45000000000000001e-167 < c < 5.8000000000000003e-23

   1. Initial program 46.2%

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

   2. Taylor expanded in x around inf 43.7%

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

   3. Taylor expanded in y around 0 42.1%

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

      1. *-commutative 42.1%

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

      2. *-commutative 42.1%

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

   5. Simplified 42.1%

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

   6. Taylor expanded in c around 0 47.4%

      \[\leadsto x \cdot \left(\color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 47.4%

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

      2. distribute-rgt-neg-in 47.4%

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

      3. distribute-rgt-neg-in 47.4%

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

   8. Simplified 47.4%

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

   if 2.26000000000000001e-228 < c < 1.45000000000000001e-167 or 5.8000000000000003e-23 < c < 3.70000000000000002e27

   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. Taylor expanded in b around inf 58.2%

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

   3. Taylor expanded in z around -inf 62.1%

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

   if 3.70000000000000002e27 < c < 1.75e44

   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. Taylor expanded in y4 around inf 51.7%

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

      1. *-commutative 51.7%

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

      2. *-commutative 51.7%

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

   4. Simplified 51.7%

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

   5. Taylor expanded in k around inf 68.4%

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

      1. mul-1-neg 68.4%

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

      2. distribute-rgt-neg-in 68.4%

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

      3. associate-*r* 68.4%

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

      4. distribute-rgt-neg-in 68.4%

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

      5. *-commutative 68.4%

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

   7. Simplified 68.4%

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

   8. Taylor expanded in k around 0 67.8%

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

      1. associate-*r* 67.8%

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

      2. neg-mul-1 67.8%

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

   10. Simplified 67.8%

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

   if 1.75e44 < c < 1.54999999999999998e116

   1. Initial program 13.3%

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

   2. Taylor expanded in y4 around inf 27.2%

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

      1. *-commutative 27.2%

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

      2. *-commutative 27.2%

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

   4. Simplified 27.2%

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

   5. Taylor expanded in c around inf 67.2%

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

   if 1.54999999999999998e116 < c < 2.55e187

   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. Taylor expanded in x around inf 51.1%

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

   3. Taylor expanded in c around inf 47.1%

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

      1. associate-*r* 54.9%

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

      2. +-commutative 54.9%

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

      3. mul-1-neg 54.9%

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

      4. unsub-neg 54.9%

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

      5. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if 2.55e187 < c < 1.1e251

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 50.1%

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

      1. *-commutative 50.1%

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

      2. *-commutative 50.1%

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

   4. Simplified 50.1%

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

   5. Taylor expanded in y around inf 71.5%

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

      1. associate-*r* 71.6%

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

      2. distribute-lft-out-- 71.6%

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

   7. Simplified 71.6%

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

   if 1.1e251 < c

   1. Initial program 17.9%

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

   2. Taylor expanded in x around inf 41.6%

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

   3. Taylor expanded in c around inf 82.5%

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

      1. +-commutative 82.5%

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

      2. mul-1-neg 82.5%

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

      3. unsub-neg 82.5%

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

      4. *-commutative 82.5%

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

   5. Simplified 82.5%

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

4. Final simplification 57.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -7.6 \cdot 10^{-73}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -3 \cdot 10^{-140}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -3.2 \cdot 10^{-218}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;c \leq 2.26 \cdot 10^{-228}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.45 \cdot 10^{-167}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{-23}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 3.7 \cdot 10^{+27}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 1.75 \cdot 10^{+44}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{elif}\;c \leq 1.55 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.55 \cdot 10^{+187}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq 1.1 \cdot 10^{+251}:\\ \;\;\;\;\left(y \cdot y4\right) \cdot \left(c \cdot y3 - b \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 12: 33.5% accurate, 2.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ t_2 := y0 \cdot y2 - y \cdot i\\ t_3 := x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{if}\;c \leq -2.35 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -2.4 \cdot 10^{-137}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -3.8 \cdot 10^{-216}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;c \leq 2.55 \cdot 10^{-228}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 5.9 \cdot 10^{-167}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 1.75 \cdot 10^{-17}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 6.8 \cdot 10^{+20}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 1.02 \cdot 10^{+44}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 4.7 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 5.7 \cdot 10^{+187}:\\ \;\;\;\;\left(x \cdot c\right) \cdot t_2\\ \mathbf{elif}\;c \leq 3.3 \cdot 10^{+251}:\\ \;\;\;\;\left(y \cdot y4\right) \cdot \left(c \cdot y3 - b \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot t_2\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* z (- (* k y0) (* t a)))))
        (t_2 (- (* y0 y2) (* y i)))
        (t_3 (* x (- (* j (- (* i y1) (* b y0))) (* a (* y1 y2))))))
   (if (<= c -2.35e-70)
     (* x (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1)))))
     (if (<= c -2.4e-137)
       (* j (* y3 (- (* y0 y5) (* y1 y4))))
       (if (<= c -3.8e-216)
         (* a (* b (- (* x y) (* z t))))
         (if (<= c 2.55e-228)
           t_3
           (if (<= c 5.9e-167)
             t_1
             (if (<= c 1.75e-17)
               t_3
               (if (<= c 6.8e+20)
                 t_1
                 (if (<= c 1.02e+44)
                   (* y1 (* y4 (- (* k y2) (* j y3))))
                   (if (<= c 4.7e+116)
                     (* c (* y4 (- (* y y3) (* t y2))))
                     (if (<= c 5.7e+187)
                       (* (* x c) t_2)
                       (if (<= c 3.3e+251)
                         (* (* y y4) (- (* c y3) (* b k)))
                         (* x (* c 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 = b * (z * ((k * y0) - (t * a)));
	double t_2 = (y0 * y2) - (y * i);
	double t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double tmp;
	if (c <= -2.35e-70) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -2.4e-137) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (c <= -3.8e-216) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (c <= 2.55e-228) {
		tmp = t_3;
	} else if (c <= 5.9e-167) {
		tmp = t_1;
	} else if (c <= 1.75e-17) {
		tmp = t_3;
	} else if (c <= 6.8e+20) {
		tmp = t_1;
	} else if (c <= 1.02e+44) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (c <= 4.7e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 5.7e+187) {
		tmp = (x * c) * t_2;
	} else if (c <= 3.3e+251) {
		tmp = (y * y4) * ((c * y3) - (b * k));
	} else {
		tmp = x * (c * 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 = b * (z * ((k * y0) - (t * a)))
    t_2 = (y0 * y2) - (y * i)
    t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
    if (c <= (-2.35d-70)) then
        tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
    else if (c <= (-2.4d-137)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (c <= (-3.8d-216)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (c <= 2.55d-228) then
        tmp = t_3
    else if (c <= 5.9d-167) then
        tmp = t_1
    else if (c <= 1.75d-17) then
        tmp = t_3
    else if (c <= 6.8d+20) then
        tmp = t_1
    else if (c <= 1.02d+44) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (c <= 4.7d+116) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= 5.7d+187) then
        tmp = (x * c) * t_2
    else if (c <= 3.3d+251) then
        tmp = (y * y4) * ((c * y3) - (b * k))
    else
        tmp = x * (c * 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 = b * (z * ((k * y0) - (t * a)));
	double t_2 = (y0 * y2) - (y * i);
	double t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double tmp;
	if (c <= -2.35e-70) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -2.4e-137) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (c <= -3.8e-216) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (c <= 2.55e-228) {
		tmp = t_3;
	} else if (c <= 5.9e-167) {
		tmp = t_1;
	} else if (c <= 1.75e-17) {
		tmp = t_3;
	} else if (c <= 6.8e+20) {
		tmp = t_1;
	} else if (c <= 1.02e+44) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (c <= 4.7e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 5.7e+187) {
		tmp = (x * c) * t_2;
	} else if (c <= 3.3e+251) {
		tmp = (y * y4) * ((c * y3) - (b * k));
	} else {
		tmp = x * (c * 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 = b * (z * ((k * y0) - (t * a)))
	t_2 = (y0 * y2) - (y * i)
	t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
	tmp = 0
	if c <= -2.35e-70:
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
	elif c <= -2.4e-137:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif c <= -3.8e-216:
		tmp = a * (b * ((x * y) - (z * t)))
	elif c <= 2.55e-228:
		tmp = t_3
	elif c <= 5.9e-167:
		tmp = t_1
	elif c <= 1.75e-17:
		tmp = t_3
	elif c <= 6.8e+20:
		tmp = t_1
	elif c <= 1.02e+44:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif c <= 4.7e+116:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= 5.7e+187:
		tmp = (x * c) * t_2
	elif c <= 3.3e+251:
		tmp = (y * y4) * ((c * y3) - (b * k))
	else:
		tmp = x * (c * 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(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))))
	t_2 = Float64(Float64(y0 * y2) - Float64(y * i))
	t_3 = Float64(x * Float64(Float64(j * Float64(Float64(i * y1) - Float64(b * y0))) - Float64(a * Float64(y1 * y2))))
	tmp = 0.0
	if (c <= -2.35e-70)
		tmp = Float64(x * Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))));
	elseif (c <= -2.4e-137)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (c <= -3.8e-216)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (c <= 2.55e-228)
		tmp = t_3;
	elseif (c <= 5.9e-167)
		tmp = t_1;
	elseif (c <= 1.75e-17)
		tmp = t_3;
	elseif (c <= 6.8e+20)
		tmp = t_1;
	elseif (c <= 1.02e+44)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (c <= 4.7e+116)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= 5.7e+187)
		tmp = Float64(Float64(x * c) * t_2);
	elseif (c <= 3.3e+251)
		tmp = Float64(Float64(y * y4) * Float64(Float64(c * y3) - Float64(b * k)));
	else
		tmp = Float64(x * Float64(c * 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 = b * (z * ((k * y0) - (t * a)));
	t_2 = (y0 * y2) - (y * i);
	t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	tmp = 0.0;
	if (c <= -2.35e-70)
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	elseif (c <= -2.4e-137)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (c <= -3.8e-216)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (c <= 2.55e-228)
		tmp = t_3;
	elseif (c <= 5.9e-167)
		tmp = t_1;
	elseif (c <= 1.75e-17)
		tmp = t_3;
	elseif (c <= 6.8e+20)
		tmp = t_1;
	elseif (c <= 1.02e+44)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (c <= 4.7e+116)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= 5.7e+187)
		tmp = (x * c) * t_2;
	elseif (c <= 3.3e+251)
		tmp = (y * y4) * ((c * y3) - (b * k));
	else
		tmp = x * (c * 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[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -2.35e-70], N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2.4e-137], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -3.8e-216], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.55e-228], t$95$3, If[LessEqual[c, 5.9e-167], t$95$1, If[LessEqual[c, 1.75e-17], t$95$3, If[LessEqual[c, 6.8e+20], t$95$1, If[LessEqual[c, 1.02e+44], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 4.7e+116], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5.7e+187], N[(N[(x * c), $MachinePrecision] * t$95$2), $MachinePrecision], If[LessEqual[c, 3.3e+251], N[(N[(y * y4), $MachinePrecision] * N[(N[(c * y3), $MachinePrecision] - N[(b * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x * N[(c * t$95$2), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if c < -2.3499999999999999e-70

   1. Initial program 19.2%

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

   2. Taylor expanded in x around inf 53.8%

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

   3. Taylor expanded in j around 0 52.2%

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

   if -2.3499999999999999e-70 < c < -2.4e-137

   1. Initial program 45.3%

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

   2. Taylor expanded in y3 around -inf 72.6%

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

   3. Taylor expanded in j around inf 56.6%

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

   if -2.4e-137 < c < -3.8e-216

   1. Initial program 43.4%

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

   2. Taylor expanded in b around inf 43.6%

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

   3. Taylor expanded in a around inf 50.7%

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

   if -3.8e-216 < c < 2.5500000000000001e-228 or 5.90000000000000022e-167 < c < 1.7500000000000001e-17

   1. Initial program 46.2%

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

   2. Taylor expanded in x around inf 43.7%

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

   3. Taylor expanded in y around 0 42.1%

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

      1. *-commutative 42.1%

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

      2. *-commutative 42.1%

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

   5. Simplified 42.1%

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

   6. Taylor expanded in c around 0 47.4%

      \[\leadsto x \cdot \left(\color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 47.4%

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

      2. distribute-rgt-neg-in 47.4%

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

      3. distribute-rgt-neg-in 47.4%

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

   8. Simplified 47.4%

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

   if 2.5500000000000001e-228 < c < 5.90000000000000022e-167 or 1.7500000000000001e-17 < c < 6.8e20

   1. Initial program 14.8%

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

   2. Taylor expanded in b around inf 60.2%

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

   3. Taylor expanded in z around -inf 64.3%

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

   if 6.8e20 < c < 1.01999999999999999e44

   1. Initial program 50.0%

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

   2. Taylor expanded in y4 around inf 35.0%

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

      1. *-commutative 35.0%

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

      2. *-commutative 35.0%

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

   4. Simplified 35.0%

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

   5. Taylor expanded in y1 around inf 52.2%

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

   if 1.01999999999999999e44 < c < 4.7000000000000003e116

   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. Taylor expanded in y4 around inf 31.8%

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

      1. *-commutative 31.8%

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

      2. *-commutative 31.8%

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

   4. Simplified 31.8%

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

   5. Taylor expanded in c around inf 63.4%

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

   if 4.7000000000000003e116 < c < 5.7000000000000004e187

   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. Taylor expanded in x around inf 51.1%

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

   3. Taylor expanded in c around inf 47.1%

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

      1. associate-*r* 54.9%

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

      2. +-commutative 54.9%

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

      3. mul-1-neg 54.9%

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

      4. unsub-neg 54.9%

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

      5. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if 5.7000000000000004e187 < c < 3.30000000000000018e251

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 50.1%

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

      1. *-commutative 50.1%

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

      2. *-commutative 50.1%

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

   4. Simplified 50.1%

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

   5. Taylor expanded in y around inf 71.5%

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

      1. associate-*r* 71.6%

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

      2. distribute-lft-out-- 71.6%

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

   7. Simplified 71.6%

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

   if 3.30000000000000018e251 < c

   1. Initial program 17.9%

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

   2. Taylor expanded in x around inf 41.6%

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

   3. Taylor expanded in c around inf 82.5%

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

      1. +-commutative 82.5%

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

      2. mul-1-neg 82.5%

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

      3. unsub-neg 82.5%

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

      4. *-commutative 82.5%

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

   5. Simplified 82.5%

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

4. Final simplification 56.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -2.35 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -2.4 \cdot 10^{-137}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -3.8 \cdot 10^{-216}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;c \leq 2.55 \cdot 10^{-228}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 5.9 \cdot 10^{-167}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 1.75 \cdot 10^{-17}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 6.8 \cdot 10^{+20}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 1.02 \cdot 10^{+44}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;c \leq 4.7 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 5.7 \cdot 10^{+187}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq 3.3 \cdot 10^{+251}:\\ \;\;\;\;\left(y \cdot y4\right) \cdot \left(c \cdot y3 - b \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 13: 34.1% accurate, 2.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ t_2 := y0 \cdot y2 - y \cdot i\\ t_3 := x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ t_4 := y0 \cdot y5 - y1 \cdot y4\\ \mathbf{if}\;c \leq -1 \cdot 10^{-68}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -4.8 \cdot 10^{-212}:\\ \;\;\;\;y3 \cdot \left(j \cdot t_4 + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 1.3 \cdot 10^{-230}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 1.15 \cdot 10^{-167}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 1.26 \cdot 10^{-20}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{+23}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{+44}:\\ \;\;\;\;j \cdot \left(y3 \cdot t_4\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{elif}\;c \leq 2.15 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{+186}:\\ \;\;\;\;\left(x \cdot c\right) \cdot t_2\\ \mathbf{elif}\;c \leq 2.8 \cdot 10^{+250}:\\ \;\;\;\;\left(y \cdot y4\right) \cdot \left(c \cdot y3 - b \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot t_2\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* z (- (* k y0) (* t a)))))
        (t_2 (- (* y0 y2) (* y i)))
        (t_3 (* x (- (* j (- (* i y1) (* b y0))) (* a (* y1 y2)))))
        (t_4 (- (* y0 y5) (* y1 y4))))
   (if (<= c -1e-68)
     (* x (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1)))))
     (if (<= c -4.8e-212)
       (* y3 (+ (* j t_4) (* z (- (* a y1) (* c y0)))))
       (if (<= c 1.3e-230)
         t_3
         (if (<= c 1.15e-167)
           t_1
           (if (<= c 1.26e-20)
             t_3
             (if (<= c 2.4e+23)
               t_1
               (if (<= c 5.8e+44)
                 (- (* j (* y3 t_4)) (* b (* (* y k) y4)))
                 (if (<= c 2.15e+116)
                   (* c (* y4 (- (* y y3) (* t y2))))
                   (if (<= c 5.8e+186)
                     (* (* x c) t_2)
                     (if (<= c 2.8e+250)
                       (* (* y y4) (- (* c y3) (* b k)))
                       (* x (* c 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 = b * (z * ((k * y0) - (t * a)));
	double t_2 = (y0 * y2) - (y * i);
	double t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double t_4 = (y0 * y5) - (y1 * y4);
	double tmp;
	if (c <= -1e-68) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -4.8e-212) {
		tmp = y3 * ((j * t_4) + (z * ((a * y1) - (c * y0))));
	} else if (c <= 1.3e-230) {
		tmp = t_3;
	} else if (c <= 1.15e-167) {
		tmp = t_1;
	} else if (c <= 1.26e-20) {
		tmp = t_3;
	} else if (c <= 2.4e+23) {
		tmp = t_1;
	} else if (c <= 5.8e+44) {
		tmp = (j * (y3 * t_4)) - (b * ((y * k) * y4));
	} else if (c <= 2.15e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 5.8e+186) {
		tmp = (x * c) * t_2;
	} else if (c <= 2.8e+250) {
		tmp = (y * y4) * ((c * y3) - (b * k));
	} else {
		tmp = x * (c * 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) :: t_4
    real(8) :: tmp
    t_1 = b * (z * ((k * y0) - (t * a)))
    t_2 = (y0 * y2) - (y * i)
    t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
    t_4 = (y0 * y5) - (y1 * y4)
    if (c <= (-1d-68)) then
        tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
    else if (c <= (-4.8d-212)) then
        tmp = y3 * ((j * t_4) + (z * ((a * y1) - (c * y0))))
    else if (c <= 1.3d-230) then
        tmp = t_3
    else if (c <= 1.15d-167) then
        tmp = t_1
    else if (c <= 1.26d-20) then
        tmp = t_3
    else if (c <= 2.4d+23) then
        tmp = t_1
    else if (c <= 5.8d+44) then
        tmp = (j * (y3 * t_4)) - (b * ((y * k) * y4))
    else if (c <= 2.15d+116) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (c <= 5.8d+186) then
        tmp = (x * c) * t_2
    else if (c <= 2.8d+250) then
        tmp = (y * y4) * ((c * y3) - (b * k))
    else
        tmp = x * (c * 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 = b * (z * ((k * y0) - (t * a)));
	double t_2 = (y0 * y2) - (y * i);
	double t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	double t_4 = (y0 * y5) - (y1 * y4);
	double tmp;
	if (c <= -1e-68) {
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	} else if (c <= -4.8e-212) {
		tmp = y3 * ((j * t_4) + (z * ((a * y1) - (c * y0))));
	} else if (c <= 1.3e-230) {
		tmp = t_3;
	} else if (c <= 1.15e-167) {
		tmp = t_1;
	} else if (c <= 1.26e-20) {
		tmp = t_3;
	} else if (c <= 2.4e+23) {
		tmp = t_1;
	} else if (c <= 5.8e+44) {
		tmp = (j * (y3 * t_4)) - (b * ((y * k) * y4));
	} else if (c <= 2.15e+116) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (c <= 5.8e+186) {
		tmp = (x * c) * t_2;
	} else if (c <= 2.8e+250) {
		tmp = (y * y4) * ((c * y3) - (b * k));
	} else {
		tmp = x * (c * 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 = b * (z * ((k * y0) - (t * a)))
	t_2 = (y0 * y2) - (y * i)
	t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
	t_4 = (y0 * y5) - (y1 * y4)
	tmp = 0
	if c <= -1e-68:
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))))
	elif c <= -4.8e-212:
		tmp = y3 * ((j * t_4) + (z * ((a * y1) - (c * y0))))
	elif c <= 1.3e-230:
		tmp = t_3
	elif c <= 1.15e-167:
		tmp = t_1
	elif c <= 1.26e-20:
		tmp = t_3
	elif c <= 2.4e+23:
		tmp = t_1
	elif c <= 5.8e+44:
		tmp = (j * (y3 * t_4)) - (b * ((y * k) * y4))
	elif c <= 2.15e+116:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif c <= 5.8e+186:
		tmp = (x * c) * t_2
	elif c <= 2.8e+250:
		tmp = (y * y4) * ((c * y3) - (b * k))
	else:
		tmp = x * (c * 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(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))))
	t_2 = Float64(Float64(y0 * y2) - Float64(y * i))
	t_3 = Float64(x * Float64(Float64(j * Float64(Float64(i * y1) - Float64(b * y0))) - Float64(a * Float64(y1 * y2))))
	t_4 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	tmp = 0.0
	if (c <= -1e-68)
		tmp = Float64(x * Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))));
	elseif (c <= -4.8e-212)
		tmp = Float64(y3 * Float64(Float64(j * t_4) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))));
	elseif (c <= 1.3e-230)
		tmp = t_3;
	elseif (c <= 1.15e-167)
		tmp = t_1;
	elseif (c <= 1.26e-20)
		tmp = t_3;
	elseif (c <= 2.4e+23)
		tmp = t_1;
	elseif (c <= 5.8e+44)
		tmp = Float64(Float64(j * Float64(y3 * t_4)) - Float64(b * Float64(Float64(y * k) * y4)));
	elseif (c <= 2.15e+116)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= 5.8e+186)
		tmp = Float64(Float64(x * c) * t_2);
	elseif (c <= 2.8e+250)
		tmp = Float64(Float64(y * y4) * Float64(Float64(c * y3) - Float64(b * k)));
	else
		tmp = Float64(x * Float64(c * 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 = b * (z * ((k * y0) - (t * a)));
	t_2 = (y0 * y2) - (y * i);
	t_3 = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	t_4 = (y0 * y5) - (y1 * y4);
	tmp = 0.0;
	if (c <= -1e-68)
		tmp = x * ((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1))));
	elseif (c <= -4.8e-212)
		tmp = y3 * ((j * t_4) + (z * ((a * y1) - (c * y0))));
	elseif (c <= 1.3e-230)
		tmp = t_3;
	elseif (c <= 1.15e-167)
		tmp = t_1;
	elseif (c <= 1.26e-20)
		tmp = t_3;
	elseif (c <= 2.4e+23)
		tmp = t_1;
	elseif (c <= 5.8e+44)
		tmp = (j * (y3 * t_4)) - (b * ((y * k) * y4));
	elseif (c <= 2.15e+116)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (c <= 5.8e+186)
		tmp = (x * c) * t_2;
	elseif (c <= 2.8e+250)
		tmp = (y * y4) * ((c * y3) - (b * k));
	else
		tmp = x * (c * 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[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1e-68], N[(x * N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -4.8e-212], N[(y3 * N[(N[(j * t$95$4), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.3e-230], t$95$3, If[LessEqual[c, 1.15e-167], t$95$1, If[LessEqual[c, 1.26e-20], t$95$3, If[LessEqual[c, 2.4e+23], t$95$1, If[LessEqual[c, 5.8e+44], N[(N[(j * N[(y3 * t$95$4), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(y * k), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.15e+116], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5.8e+186], N[(N[(x * c), $MachinePrecision] * t$95$2), $MachinePrecision], If[LessEqual[c, 2.8e+250], N[(N[(y * y4), $MachinePrecision] * N[(N[(c * y3), $MachinePrecision] - N[(b * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x * N[(c * t$95$2), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if c < -1.00000000000000007e-68

   1. Initial program 19.2%

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

   2. Taylor expanded in x around inf 53.8%

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

   3. Taylor expanded in j around 0 52.2%

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

   if -1.00000000000000007e-68 < c < -4.79999999999999978e-212

   1. Initial program 44.3%

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

   2. Taylor expanded in y3 around -inf 52.7%

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

   3. Taylor expanded in y around 0 49.3%

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

   if -4.79999999999999978e-212 < c < 1.3000000000000001e-230 or 1.1500000000000001e-167 < c < 1.26e-20

   1. Initial program 46.2%

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

   2. Taylor expanded in x around inf 43.7%

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

   3. Taylor expanded in y around 0 42.1%

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

      1. *-commutative 42.1%

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

      2. *-commutative 42.1%

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

   5. Simplified 42.1%

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

   6. Taylor expanded in c around 0 47.4%

      \[\leadsto x \cdot \left(\color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 47.4%

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

      2. distribute-rgt-neg-in 47.4%

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

      3. distribute-rgt-neg-in 47.4%

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

   8. Simplified 47.4%

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

   if 1.3000000000000001e-230 < c < 1.1500000000000001e-167 or 1.26e-20 < c < 2.4e23

   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. Taylor expanded in b around inf 58.2%

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

   3. Taylor expanded in z around -inf 62.1%

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

   if 2.4e23 < c < 5.8000000000000004e44

   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. Taylor expanded in y4 around inf 51.7%

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

      1. *-commutative 51.7%

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

      2. *-commutative 51.7%

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

   4. Simplified 51.7%

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

   5. Taylor expanded in k around inf 68.4%

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

      1. mul-1-neg 68.4%

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

      2. distribute-rgt-neg-in 68.4%

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

      3. associate-*r* 68.4%

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

      4. distribute-rgt-neg-in 68.4%

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

      5. *-commutative 68.4%

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

   7. Simplified 68.4%

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

   8. Taylor expanded in k around 0 67.8%

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

      1. associate-*r* 67.8%

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

      2. neg-mul-1 67.8%

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

   10. Simplified 67.8%

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

   if 5.8000000000000004e44 < c < 2.15e116

   1. Initial program 13.3%

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

   2. Taylor expanded in y4 around inf 27.2%

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

      1. *-commutative 27.2%

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

      2. *-commutative 27.2%

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

   4. Simplified 27.2%

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

   5. Taylor expanded in c around inf 67.2%

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

   if 2.15e116 < c < 5.8e186

   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. Taylor expanded in x around inf 51.1%

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

   3. Taylor expanded in c around inf 47.1%

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

      1. associate-*r* 54.9%

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

      2. +-commutative 54.9%

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

      3. mul-1-neg 54.9%

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

      4. unsub-neg 54.9%

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

      5. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if 5.8e186 < c < 2.8000000000000001e250

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 50.1%

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

      1. *-commutative 50.1%

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

      2. *-commutative 50.1%

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

   4. Simplified 50.1%

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

   5. Taylor expanded in y around inf 71.5%

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

      1. associate-*r* 71.6%

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

      2. distribute-lft-out-- 71.6%

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

   7. Simplified 71.6%

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

   if 2.8000000000000001e250 < c

   1. Initial program 17.9%

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

   2. Taylor expanded in x around inf 41.6%

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

   3. Taylor expanded in c around inf 82.5%

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

      1. +-commutative 82.5%

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

      2. mul-1-neg 82.5%

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

      3. unsub-neg 82.5%

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

      4. *-commutative 82.5%

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

   5. Simplified 82.5%

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

4. Final simplification 56.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1 \cdot 10^{-68}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq -4.8 \cdot 10^{-212}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 1.3 \cdot 10^{-230}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.15 \cdot 10^{-167}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 1.26 \cdot 10^{-20}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{+23}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{+44}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - b \cdot \left(\left(y \cdot k\right) \cdot y4\right)\\ \mathbf{elif}\;c \leq 2.15 \cdot 10^{+116}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{+186}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq 2.8 \cdot 10^{+250}:\\ \;\;\;\;\left(y \cdot y4\right) \cdot \left(c \cdot y3 - b \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \end{array} \]

Alternative 14: 31.4% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ t_2 := b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ t_3 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;j \leq -1.16 \cdot 10^{+78}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq -5.3 \cdot 10^{-80}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -6.4 \cdot 10^{-236}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-300}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 4.1 \cdot 10^{-225}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 6.8 \cdot 10^{-162}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-142}:\\ \;\;\;\;x \cdot \left(\left(-a\right) \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{-44} \lor \neg \left(j \leq 6.8 \cdot 10^{+67}\right):\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* c (- (* y0 y2) (* y i)))))
        (t_2 (* b (* j (- (* t y4) (* x y0)))))
        (t_3 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= j -1.16e+78)
     t_2
     (if (<= j -5.3e-80)
       t_1
       (if (<= j -6.4e-236)
         (* c (* y4 (- (* y y3) (* t y2))))
         (if (<= j 1.5e-300)
           t_1
           (if (<= j 4.1e-225)
             t_3
             (if (<= j 6.8e-162)
               (* a (* b (- (* x y) (* z t))))
               (if (<= j 5e-142)
                 (* x (* (- a) (* y1 y2)))
                 (if (or (<= j 2.1e-44) (not (<= j 6.8e+67))) t_2 t_3))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (c * ((y0 * y2) - (y * i)));
	double t_2 = b * (j * ((t * y4) - (x * y0)));
	double t_3 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (j <= -1.16e+78) {
		tmp = t_2;
	} else if (j <= -5.3e-80) {
		tmp = t_1;
	} else if (j <= -6.4e-236) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (j <= 1.5e-300) {
		tmp = t_1;
	} else if (j <= 4.1e-225) {
		tmp = t_3;
	} else if (j <= 6.8e-162) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 5e-142) {
		tmp = x * (-a * (y1 * y2));
	} else if ((j <= 2.1e-44) || !(j <= 6.8e+67)) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = x * (c * ((y0 * y2) - (y * i)))
    t_2 = b * (j * ((t * y4) - (x * y0)))
    t_3 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (j <= (-1.16d+78)) then
        tmp = t_2
    else if (j <= (-5.3d-80)) then
        tmp = t_1
    else if (j <= (-6.4d-236)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (j <= 1.5d-300) then
        tmp = t_1
    else if (j <= 4.1d-225) then
        tmp = t_3
    else if (j <= 6.8d-162) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (j <= 5d-142) then
        tmp = x * (-a * (y1 * y2))
    else if ((j <= 2.1d-44) .or. (.not. (j <= 6.8d+67))) then
        tmp = t_2
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (c * ((y0 * y2) - (y * i)));
	double t_2 = b * (j * ((t * y4) - (x * y0)));
	double t_3 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (j <= -1.16e+78) {
		tmp = t_2;
	} else if (j <= -5.3e-80) {
		tmp = t_1;
	} else if (j <= -6.4e-236) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (j <= 1.5e-300) {
		tmp = t_1;
	} else if (j <= 4.1e-225) {
		tmp = t_3;
	} else if (j <= 6.8e-162) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 5e-142) {
		tmp = x * (-a * (y1 * y2));
	} else if ((j <= 2.1e-44) || !(j <= 6.8e+67)) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = x * (c * ((y0 * y2) - (y * i)))
	t_2 = b * (j * ((t * y4) - (x * y0)))
	t_3 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if j <= -1.16e+78:
		tmp = t_2
	elif j <= -5.3e-80:
		tmp = t_1
	elif j <= -6.4e-236:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif j <= 1.5e-300:
		tmp = t_1
	elif j <= 4.1e-225:
		tmp = t_3
	elif j <= 6.8e-162:
		tmp = a * (b * ((x * y) - (z * t)))
	elif j <= 5e-142:
		tmp = x * (-a * (y1 * y2))
	elif (j <= 2.1e-44) or not (j <= 6.8e+67):
		tmp = t_2
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(x * Float64(c * Float64(Float64(y0 * y2) - Float64(y * i))))
	t_2 = Float64(b * Float64(j * Float64(Float64(t * y4) - Float64(x * y0))))
	t_3 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (j <= -1.16e+78)
		tmp = t_2;
	elseif (j <= -5.3e-80)
		tmp = t_1;
	elseif (j <= -6.4e-236)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (j <= 1.5e-300)
		tmp = t_1;
	elseif (j <= 4.1e-225)
		tmp = t_3;
	elseif (j <= 6.8e-162)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (j <= 5e-142)
		tmp = Float64(x * Float64(Float64(-a) * Float64(y1 * y2)));
	elseif ((j <= 2.1e-44) || !(j <= 6.8e+67))
		tmp = t_2;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = x * (c * ((y0 * y2) - (y * i)));
	t_2 = b * (j * ((t * y4) - (x * y0)));
	t_3 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (j <= -1.16e+78)
		tmp = t_2;
	elseif (j <= -5.3e-80)
		tmp = t_1;
	elseif (j <= -6.4e-236)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (j <= 1.5e-300)
		tmp = t_1;
	elseif (j <= 4.1e-225)
		tmp = t_3;
	elseif (j <= 6.8e-162)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (j <= 5e-142)
		tmp = x * (-a * (y1 * y2));
	elseif ((j <= 2.1e-44) || ~((j <= 6.8e+67)))
		tmp = t_2;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(x * N[(c * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.16e+78], t$95$2, If[LessEqual[j, -5.3e-80], t$95$1, If[LessEqual[j, -6.4e-236], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.5e-300], t$95$1, If[LessEqual[j, 4.1e-225], t$95$3, If[LessEqual[j, 6.8e-162], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5e-142], N[(x * N[((-a) * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[j, 2.1e-44], N[Not[LessEqual[j, 6.8e+67]], $MachinePrecision]], t$95$2, t$95$3]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -1.1600000000000001e78 or 5.0000000000000002e-142 < j < 2.10000000000000001e-44 or 6.8000000000000003e67 < j

   1. Initial program 23.8%

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

   2. Taylor expanded in b around inf 37.7%

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

   3. Taylor expanded in j around inf 51.2%

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

   if -1.1600000000000001e78 < j < -5.30000000000000026e-80 or -6.3999999999999999e-236 < j < 1.50000000000000012e-300

   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. Taylor expanded in x around inf 61.3%

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

   3. Taylor expanded in c around inf 47.0%

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

      1. +-commutative 47.0%

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

      2. mul-1-neg 47.0%

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

      3. unsub-neg 47.0%

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

      4. *-commutative 47.0%

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

   5. Simplified 47.0%

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

   if -5.30000000000000026e-80 < j < -6.3999999999999999e-236

   1. Initial program 25.7%

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

   2. Taylor expanded in y4 around inf 26.7%

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

      1. *-commutative 26.7%

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

      2. *-commutative 26.7%

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

   4. Simplified 26.7%

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

   5. Taylor expanded in c around inf 43.2%

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

   if 1.50000000000000012e-300 < j < 4.10000000000000022e-225 or 2.10000000000000001e-44 < j < 6.8000000000000003e67

   1. Initial program 29.6%

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

   2. Taylor expanded in y4 around inf 33.1%

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

      1. *-commutative 33.1%

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

      2. *-commutative 33.1%

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

   4. Simplified 33.1%

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

   5. Taylor expanded in k around inf 36.9%

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

      1. mul-1-neg 36.9%

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

      2. distribute-rgt-neg-in 36.9%

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

      3. associate-*r* 34.0%

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

      4. distribute-rgt-neg-in 34.0%

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

      5. *-commutative 34.0%

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

   7. Simplified 34.0%

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

   8. Taylor expanded in y2 around inf 45.3%

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

   if 4.10000000000000022e-225 < j < 6.8e-162

   1. Initial program 39.3%

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

   2. Taylor expanded in b around inf 40.1%

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

   3. Taylor expanded in a around inf 44.2%

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

   if 6.8e-162 < j < 5.0000000000000002e-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. Taylor expanded in x around inf 50.0%

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

   3. Taylor expanded in j around 0 50.0%

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

   4. Taylor expanded in y1 around inf 100.0%

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

      1. mul-1-neg 100.0%

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

      2. distribute-rgt-neg-in 100.0%

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

      3. *-commutative 100.0%

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

      4. distribute-rgt-neg-in 100.0%

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

   6. Simplified 100.0%

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

4. Final simplification 48.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.16 \cdot 10^{+78}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -5.3 \cdot 10^{-80}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -6.4 \cdot 10^{-236}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-300}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;j \leq 4.1 \cdot 10^{-225}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 6.8 \cdot 10^{-162}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-142}:\\ \;\;\;\;x \cdot \left(\left(-a\right) \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{-44} \lor \neg \left(j \leq 6.8 \cdot 10^{+67}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \end{array} \]

Alternative 15: 31.0% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ t_2 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{if}\;j \leq -6.1 \cdot 10^{-25}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -4.3 \cdot 10^{-80}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -4.4 \cdot 10^{-236}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-300}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 8.5 \cdot 10^{-225}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 1.05 \cdot 10^{-163}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 4.8 \cdot 10^{-130}:\\ \;\;\;\;x \cdot \left(\left(-a\right) \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{-44} \lor \neg \left(j \leq 1.4 \cdot 10^{+68}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* c (- (* y0 y2) (* y i)))))
        (t_2 (* k (* y2 (- (* y1 y4) (* y0 y5))))))
   (if (<= j -6.1e-25)
     (* x (* j (- (* i y1) (* b y0))))
     (if (<= j -4.3e-80)
       t_1
       (if (<= j -4.4e-236)
         (* c (* y4 (- (* y y3) (* t y2))))
         (if (<= j 1.5e-300)
           t_1
           (if (<= j 8.5e-225)
             t_2
             (if (<= j 1.05e-163)
               (* a (* b (- (* x y) (* z t))))
               (if (<= j 4.8e-130)
                 (* x (* (- a) (* y1 y2)))
                 (if (or (<= j 1.7e-44) (not (<= j 1.4e+68)))
                   (* b (* j (- (* t y4) (* x y0))))
                   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 * (c * ((y0 * y2) - (y * i)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (j <= -6.1e-25) {
		tmp = x * (j * ((i * y1) - (b * y0)));
	} else if (j <= -4.3e-80) {
		tmp = t_1;
	} else if (j <= -4.4e-236) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (j <= 1.5e-300) {
		tmp = t_1;
	} else if (j <= 8.5e-225) {
		tmp = t_2;
	} else if (j <= 1.05e-163) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 4.8e-130) {
		tmp = x * (-a * (y1 * y2));
	} else if ((j <= 1.7e-44) || !(j <= 1.4e+68)) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * (c * ((y0 * y2) - (y * i)))
    t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    if (j <= (-6.1d-25)) then
        tmp = x * (j * ((i * y1) - (b * y0)))
    else if (j <= (-4.3d-80)) then
        tmp = t_1
    else if (j <= (-4.4d-236)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (j <= 1.5d-300) then
        tmp = t_1
    else if (j <= 8.5d-225) then
        tmp = t_2
    else if (j <= 1.05d-163) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (j <= 4.8d-130) then
        tmp = x * (-a * (y1 * y2))
    else if ((j <= 1.7d-44) .or. (.not. (j <= 1.4d+68))) then
        tmp = b * (j * ((t * y4) - (x * y0)))
    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 * (c * ((y0 * y2) - (y * i)));
	double t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double tmp;
	if (j <= -6.1e-25) {
		tmp = x * (j * ((i * y1) - (b * y0)));
	} else if (j <= -4.3e-80) {
		tmp = t_1;
	} else if (j <= -4.4e-236) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (j <= 1.5e-300) {
		tmp = t_1;
	} else if (j <= 8.5e-225) {
		tmp = t_2;
	} else if (j <= 1.05e-163) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 4.8e-130) {
		tmp = x * (-a * (y1 * y2));
	} else if ((j <= 1.7e-44) || !(j <= 1.4e+68)) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} 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 * (c * ((y0 * y2) - (y * i)))
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if j <= -6.1e-25:
		tmp = x * (j * ((i * y1) - (b * y0)))
	elif j <= -4.3e-80:
		tmp = t_1
	elif j <= -4.4e-236:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif j <= 1.5e-300:
		tmp = t_1
	elif j <= 8.5e-225:
		tmp = t_2
	elif j <= 1.05e-163:
		tmp = a * (b * ((x * y) - (z * t)))
	elif j <= 4.8e-130:
		tmp = x * (-a * (y1 * y2))
	elif (j <= 1.7e-44) or not (j <= 1.4e+68):
		tmp = b * (j * ((t * y4) - (x * y0)))
	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(c * Float64(Float64(y0 * y2) - Float64(y * i))))
	t_2 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (j <= -6.1e-25)
		tmp = Float64(x * Float64(j * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (j <= -4.3e-80)
		tmp = t_1;
	elseif (j <= -4.4e-236)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (j <= 1.5e-300)
		tmp = t_1;
	elseif (j <= 8.5e-225)
		tmp = t_2;
	elseif (j <= 1.05e-163)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (j <= 4.8e-130)
		tmp = Float64(x * Float64(Float64(-a) * Float64(y1 * y2)));
	elseif ((j <= 1.7e-44) || !(j <= 1.4e+68))
		tmp = Float64(b * Float64(j * Float64(Float64(t * y4) - Float64(x * y0))));
	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 * (c * ((y0 * y2) - (y * i)));
	t_2 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (j <= -6.1e-25)
		tmp = x * (j * ((i * y1) - (b * y0)));
	elseif (j <= -4.3e-80)
		tmp = t_1;
	elseif (j <= -4.4e-236)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (j <= 1.5e-300)
		tmp = t_1;
	elseif (j <= 8.5e-225)
		tmp = t_2;
	elseif (j <= 1.05e-163)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (j <= 4.8e-130)
		tmp = x * (-a * (y1 * y2));
	elseif ((j <= 1.7e-44) || ~((j <= 1.4e+68)))
		tmp = b * (j * ((t * y4) - (x * y0)));
	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[(c * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $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[j, -6.1e-25], N[(x * N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -4.3e-80], t$95$1, If[LessEqual[j, -4.4e-236], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.5e-300], t$95$1, If[LessEqual[j, 8.5e-225], t$95$2, If[LessEqual[j, 1.05e-163], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.8e-130], N[(x * N[((-a) * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[j, 1.7e-44], N[Not[LessEqual[j, 1.4e+68]], $MachinePrecision]], N[(b * N[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -6.10000000000000018e-25

   1. Initial program 23.2%

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

   2. Taylor expanded in x around inf 44.6%

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

   3. Taylor expanded in j around inf 44.0%

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

      1. *-commutative 44.0%

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

      2. *-commutative 44.0%

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

   5. Simplified 44.0%

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

   if -6.10000000000000018e-25 < j < -4.3000000000000001e-80 or -4.39999999999999985e-236 < j < 1.50000000000000012e-300

   1. Initial program 43.0%

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

   2. Taylor expanded in x around inf 60.5%

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

   3. Taylor expanded in c around inf 58.3%

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

      1. +-commutative 58.3%

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

      2. mul-1-neg 58.3%

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

      3. unsub-neg 58.3%

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

      4. *-commutative 58.3%

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

   5. Simplified 58.3%

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

   if -4.3000000000000001e-80 < j < -4.39999999999999985e-236

   1. Initial program 25.7%

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

   2. Taylor expanded in y4 around inf 26.7%

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

      1. *-commutative 26.7%

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

      2. *-commutative 26.7%

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

   4. Simplified 26.7%

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

   5. Taylor expanded in c around inf 43.2%

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

   if 1.50000000000000012e-300 < j < 8.4999999999999998e-225 or 1.70000000000000008e-44 < j < 1.4e68

   1. Initial program 29.6%

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

   2. Taylor expanded in y4 around inf 33.1%

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

      1. *-commutative 33.1%

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

      2. *-commutative 33.1%

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

   4. Simplified 33.1%

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

   5. Taylor expanded in k around inf 36.9%

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

      1. mul-1-neg 36.9%

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

      2. distribute-rgt-neg-in 36.9%

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

      3. associate-*r* 34.0%

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

      4. distribute-rgt-neg-in 34.0%

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

      5. *-commutative 34.0%

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

   7. Simplified 34.0%

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

   8. Taylor expanded in y2 around inf 45.3%

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

   if 8.4999999999999998e-225 < j < 1.04999999999999999e-163

   1. Initial program 39.3%

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

   2. Taylor expanded in b around inf 40.1%

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

   3. Taylor expanded in a around inf 44.2%

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

   if 1.04999999999999999e-163 < j < 4.79999999999999993e-130

   1. Initial program 0.0%

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

   2. Taylor expanded in x around inf 50.0%

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

   3. Taylor expanded in j around 0 50.0%

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

   4. Taylor expanded in y1 around inf 100.0%

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

      1. mul-1-neg 100.0%

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

      2. distribute-rgt-neg-in 100.0%

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

      3. *-commutative 100.0%

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

      4. distribute-rgt-neg-in 100.0%

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

   6. Simplified 100.0%

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

   if 4.79999999999999993e-130 < j < 1.70000000000000008e-44 or 1.4e68 < j

   1. Initial program 26.9%

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

   2. Taylor expanded in b around inf 39.8%

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

   3. Taylor expanded in j around inf 52.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -6.1 \cdot 10^{-25}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -4.3 \cdot 10^{-80}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -4.4 \cdot 10^{-236}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-300}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;j \leq 8.5 \cdot 10^{-225}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 1.05 \cdot 10^{-163}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 4.8 \cdot 10^{-130}:\\ \;\;\;\;x \cdot \left(\left(-a\right) \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{-44} \lor \neg \left(j \leq 1.4 \cdot 10^{+68}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \end{array} \]

Alternative 16: 29.8% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{if}\;j \leq -2.7 \cdot 10^{+156}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;j \leq -14500000000000:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -5.2 \cdot 10^{-25}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -4.8 \cdot 10^{-80}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -1.3 \cdot 10^{-236}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-300}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 4.2 \cdot 10^{-222}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{-160}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 7.6 \cdot 10^{-137}:\\ \;\;\;\;x \cdot \left(\left(-a\right) \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* c (- (* y0 y2) (* y i))))))
   (if (<= j -2.7e+156)
     (* j (* y0 (- (* y3 y5) (* x b))))
     (if (<= j -14500000000000.0)
       (* x (* y (- (* a b) (* c i))))
       (if (<= j -5.2e-25)
         (* x (* j (- (* i y1) (* b y0))))
         (if (<= j -4.8e-80)
           t_1
           (if (<= j -1.3e-236)
             (* c (* y4 (- (* y y3) (* t y2))))
             (if (<= j 1.15e-300)
               t_1
               (if (<= j 4.2e-222)
                 (* k (* y2 (- (* y1 y4) (* y0 y5))))
                 (if (<= j 2.1e-160)
                   (* a (* b (- (* x y) (* z t))))
                   (if (<= j 7.6e-137)
                     (* x (* (- a) (* y1 y2)))
                     (* b (* j (- (* t y4) (* x y0)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (c * ((y0 * y2) - (y * i)));
	double tmp;
	if (j <= -2.7e+156) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (j <= -14500000000000.0) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -5.2e-25) {
		tmp = x * (j * ((i * y1) - (b * y0)));
	} else if (j <= -4.8e-80) {
		tmp = t_1;
	} else if (j <= -1.3e-236) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (j <= 1.15e-300) {
		tmp = t_1;
	} else if (j <= 4.2e-222) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (j <= 2.1e-160) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 7.6e-137) {
		tmp = x * (-a * (y1 * y2));
	} else {
		tmp = b * (j * ((t * y4) - (x * y0)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = x * (c * ((y0 * y2) - (y * i)))
    if (j <= (-2.7d+156)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (j <= (-14500000000000.0d0)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (j <= (-5.2d-25)) then
        tmp = x * (j * ((i * y1) - (b * y0)))
    else if (j <= (-4.8d-80)) then
        tmp = t_1
    else if (j <= (-1.3d-236)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (j <= 1.15d-300) then
        tmp = t_1
    else if (j <= 4.2d-222) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (j <= 2.1d-160) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (j <= 7.6d-137) then
        tmp = x * (-a * (y1 * y2))
    else
        tmp = b * (j * ((t * y4) - (x * y0)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (c * ((y0 * y2) - (y * i)));
	double tmp;
	if (j <= -2.7e+156) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (j <= -14500000000000.0) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -5.2e-25) {
		tmp = x * (j * ((i * y1) - (b * y0)));
	} else if (j <= -4.8e-80) {
		tmp = t_1;
	} else if (j <= -1.3e-236) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (j <= 1.15e-300) {
		tmp = t_1;
	} else if (j <= 4.2e-222) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (j <= 2.1e-160) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 7.6e-137) {
		tmp = x * (-a * (y1 * y2));
	} else {
		tmp = b * (j * ((t * y4) - (x * y0)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = x * (c * ((y0 * y2) - (y * i)))
	tmp = 0
	if j <= -2.7e+156:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif j <= -14500000000000.0:
		tmp = x * (y * ((a * b) - (c * i)))
	elif j <= -5.2e-25:
		tmp = x * (j * ((i * y1) - (b * y0)))
	elif j <= -4.8e-80:
		tmp = t_1
	elif j <= -1.3e-236:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif j <= 1.15e-300:
		tmp = t_1
	elif j <= 4.2e-222:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif j <= 2.1e-160:
		tmp = a * (b * ((x * y) - (z * t)))
	elif j <= 7.6e-137:
		tmp = x * (-a * (y1 * y2))
	else:
		tmp = b * (j * ((t * y4) - (x * 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(x * Float64(c * Float64(Float64(y0 * y2) - Float64(y * i))))
	tmp = 0.0
	if (j <= -2.7e+156)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (j <= -14500000000000.0)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (j <= -5.2e-25)
		tmp = Float64(x * Float64(j * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (j <= -4.8e-80)
		tmp = t_1;
	elseif (j <= -1.3e-236)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (j <= 1.15e-300)
		tmp = t_1;
	elseif (j <= 4.2e-222)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (j <= 2.1e-160)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (j <= 7.6e-137)
		tmp = Float64(x * Float64(Float64(-a) * Float64(y1 * y2)));
	else
		tmp = Float64(b * Float64(j * Float64(Float64(t * y4) - Float64(x * 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 = x * (c * ((y0 * y2) - (y * i)));
	tmp = 0.0;
	if (j <= -2.7e+156)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (j <= -14500000000000.0)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (j <= -5.2e-25)
		tmp = x * (j * ((i * y1) - (b * y0)));
	elseif (j <= -4.8e-80)
		tmp = t_1;
	elseif (j <= -1.3e-236)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (j <= 1.15e-300)
		tmp = t_1;
	elseif (j <= 4.2e-222)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (j <= 2.1e-160)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (j <= 7.6e-137)
		tmp = x * (-a * (y1 * y2));
	else
		tmp = b * (j * ((t * y4) - (x * y0)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(x * N[(c * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.7e+156], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -14500000000000.0], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5.2e-25], N[(x * N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -4.8e-80], t$95$1, If[LessEqual[j, -1.3e-236], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.15e-300], t$95$1, If[LessEqual[j, 4.2e-222], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.1e-160], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.6e-137], N[(x * N[((-a) * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if j < -2.7e156

   1. Initial program 22.8%

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

   2. Taylor expanded in y0 around inf 37.6%

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

   3. Taylor expanded in j around inf 49.6%

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

   if -2.7e156 < j < -1.45e13

   1. Initial program 19.3%

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

   2. Taylor expanded in x around inf 55.6%

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

   3. Taylor expanded in y around inf 46.2%

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

   if -1.45e13 < j < -5.2e-25

   1. Initial program 42.6%

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

   2. Taylor expanded in x around inf 57.0%

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

   3. Taylor expanded in j around inf 71.5%

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

      1. *-commutative 71.5%

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

      2. *-commutative 71.5%

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

   5. Simplified 71.5%

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

   if -5.2e-25 < j < -4.7999999999999998e-80 or -1.3e-236 < j < 1.15e-300

   1. Initial program 43.0%

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

   2. Taylor expanded in x around inf 60.5%

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

   3. Taylor expanded in c around inf 58.3%

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

      1. +-commutative 58.3%

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

      2. mul-1-neg 58.3%

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

      3. unsub-neg 58.3%

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

      4. *-commutative 58.3%

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

   5. Simplified 58.3%

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

   if -4.7999999999999998e-80 < j < -1.3e-236

   1. Initial program 25.7%

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

   2. Taylor expanded in y4 around inf 26.7%

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

      1. *-commutative 26.7%

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

      2. *-commutative 26.7%

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

   4. Simplified 26.7%

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

   5. Taylor expanded in c around inf 43.2%

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

   if 1.15e-300 < j < 4.1999999999999998e-222

   1. Initial program 42.9%

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

   2. Taylor expanded in y4 around inf 36.7%

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

      1. *-commutative 36.7%

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

      2. *-commutative 36.7%

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

   4. Simplified 36.7%

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

   5. Taylor expanded in k around inf 37.0%

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

      1. mul-1-neg 37.0%

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

      2. distribute-rgt-neg-in 37.0%

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

      3. associate-*r* 29.9%

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

      4. distribute-rgt-neg-in 29.9%

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

      5. *-commutative 29.9%

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

   7. Simplified 29.9%

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

   8. Taylor expanded in y2 around inf 51.0%

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

   if 4.1999999999999998e-222 < j < 2.1e-160

   1. Initial program 39.3%

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

   2. Taylor expanded in b around inf 40.1%

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

   3. Taylor expanded in a around inf 44.2%

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

   if 2.1e-160 < j < 7.59999999999999997e-137

   1. Initial program 0.0%

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

   2. Taylor expanded in x around inf 50.0%

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

   3. Taylor expanded in j around 0 50.0%

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

   4. Taylor expanded in y1 around inf 100.0%

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

      1. mul-1-neg 100.0%

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

      2. distribute-rgt-neg-in 100.0%

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

      3. *-commutative 100.0%

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

      4. distribute-rgt-neg-in 100.0%

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

   6. Simplified 100.0%

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

   if 7.59999999999999997e-137 < j

   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. Taylor expanded in b around inf 37.6%

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

   3. Taylor expanded in j around inf 44.4%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 49.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -2.7 \cdot 10^{+156}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;j \leq -14500000000000:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -5.2 \cdot 10^{-25}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -4.8 \cdot 10^{-80}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.3 \cdot 10^{-236}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-300}:\\ \;\;\;\;x \cdot \left(c \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;j \leq 4.2 \cdot 10^{-222}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 2.1 \cdot 10^{-160}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 7.6 \cdot 10^{-137}:\\ \;\;\;\;x \cdot \left(\left(-a\right) \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \end{array} \]

Alternative 17: 28.6% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ t_2 := x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{if}\;i \leq -1.95 \cdot 10^{+105}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;i \leq -4.2 \cdot 10^{+57}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;i \leq -3.2 \cdot 10^{-50}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;i \leq -3.1 \cdot 10^{-165}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq -4 \cdot 10^{-275}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 9.5 \cdot 10^{-235}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 7 \cdot 10^{-152}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 2.75 \cdot 10^{+31}:\\ \;\;\;\;\left(t \cdot b\right) \cdot \left(j \cdot y4 - z \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y2 (- (* c y0) (* a y1)))))
        (t_2 (* x (* y (- (* a b) (* c i))))))
   (if (<= i -1.95e+105)
     t_2
     (if (<= i -4.2e+57)
       (* j (* y0 (- (* y3 y5) (* x b))))
       (if (<= i -3.2e-50)
         t_2
         (if (<= i -3.1e-165)
           t_1
           (if (<= i -4e-275)
             (* y1 (* y4 (- (* k y2) (* j y3))))
             (if (<= i 9.5e-235)
               t_1
               (if (<= i 7e-152)
                 (* k (* y2 (- (* y1 y4) (* y0 y5))))
                 (if (<= i 2.75e+31)
                   (* (* t b) (- (* j y4) (* z a)))
                   (* x (* 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 = x * (y2 * ((c * y0) - (a * y1)));
	double t_2 = x * (y * ((a * b) - (c * i)));
	double tmp;
	if (i <= -1.95e+105) {
		tmp = t_2;
	} else if (i <= -4.2e+57) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (i <= -3.2e-50) {
		tmp = t_2;
	} else if (i <= -3.1e-165) {
		tmp = t_1;
	} else if (i <= -4e-275) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 9.5e-235) {
		tmp = t_1;
	} else if (i <= 7e-152) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 2.75e+31) {
		tmp = (t * b) * ((j * y4) - (z * a));
	} else {
		tmp = x * (j * ((i * y1) - (b * 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) :: t_2
    real(8) :: tmp
    t_1 = x * (y2 * ((c * y0) - (a * y1)))
    t_2 = x * (y * ((a * b) - (c * i)))
    if (i <= (-1.95d+105)) then
        tmp = t_2
    else if (i <= (-4.2d+57)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (i <= (-3.2d-50)) then
        tmp = t_2
    else if (i <= (-3.1d-165)) then
        tmp = t_1
    else if (i <= (-4d-275)) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (i <= 9.5d-235) then
        tmp = t_1
    else if (i <= 7d-152) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (i <= 2.75d+31) then
        tmp = (t * b) * ((j * y4) - (z * a))
    else
        tmp = x * (j * ((i * y1) - (b * 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 = x * (y2 * ((c * y0) - (a * y1)));
	double t_2 = x * (y * ((a * b) - (c * i)));
	double tmp;
	if (i <= -1.95e+105) {
		tmp = t_2;
	} else if (i <= -4.2e+57) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (i <= -3.2e-50) {
		tmp = t_2;
	} else if (i <= -3.1e-165) {
		tmp = t_1;
	} else if (i <= -4e-275) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 9.5e-235) {
		tmp = t_1;
	} else if (i <= 7e-152) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 2.75e+31) {
		tmp = (t * b) * ((j * y4) - (z * a));
	} else {
		tmp = x * (j * ((i * y1) - (b * y0)));
	}
	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)))
	t_2 = x * (y * ((a * b) - (c * i)))
	tmp = 0
	if i <= -1.95e+105:
		tmp = t_2
	elif i <= -4.2e+57:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif i <= -3.2e-50:
		tmp = t_2
	elif i <= -3.1e-165:
		tmp = t_1
	elif i <= -4e-275:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif i <= 9.5e-235:
		tmp = t_1
	elif i <= 7e-152:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif i <= 2.75e+31:
		tmp = (t * b) * ((j * y4) - (z * a))
	else:
		tmp = x * (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(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	t_2 = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))))
	tmp = 0.0
	if (i <= -1.95e+105)
		tmp = t_2;
	elseif (i <= -4.2e+57)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (i <= -3.2e-50)
		tmp = t_2;
	elseif (i <= -3.1e-165)
		tmp = t_1;
	elseif (i <= -4e-275)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (i <= 9.5e-235)
		tmp = t_1;
	elseif (i <= 7e-152)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (i <= 2.75e+31)
		tmp = Float64(Float64(t * b) * Float64(Float64(j * y4) - Float64(z * a)));
	else
		tmp = Float64(x * Float64(j * Float64(Float64(i * y1) - Float64(b * 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 = x * (y2 * ((c * y0) - (a * y1)));
	t_2 = x * (y * ((a * b) - (c * i)));
	tmp = 0.0;
	if (i <= -1.95e+105)
		tmp = t_2;
	elseif (i <= -4.2e+57)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (i <= -3.2e-50)
		tmp = t_2;
	elseif (i <= -3.1e-165)
		tmp = t_1;
	elseif (i <= -4e-275)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (i <= 9.5e-235)
		tmp = t_1;
	elseif (i <= 7e-152)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (i <= 2.75e+31)
		tmp = (t * b) * ((j * y4) - (z * a));
	else
		tmp = x * (j * ((i * y1) - (b * 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[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -1.95e+105], t$95$2, If[LessEqual[i, -4.2e+57], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -3.2e-50], t$95$2, If[LessEqual[i, -3.1e-165], t$95$1, If[LessEqual[i, -4e-275], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 9.5e-235], t$95$1, If[LessEqual[i, 7e-152], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2.75e+31], N[(N[(t * b), $MachinePrecision] * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x * N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if i < -1.94999999999999989e105 or -4.19999999999999982e57 < i < -3.2e-50

   1. Initial program 26.3%

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

   2. Taylor expanded in x around inf 47.5%

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

   3. Taylor expanded in y around inf 53.2%

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

   if -1.94999999999999989e105 < i < -4.19999999999999982e57

   1. Initial program 29.8%

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

   2. Taylor expanded in y0 around inf 50.0%

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

   3. Taylor expanded in j around inf 62.0%

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

   if -3.2e-50 < i < -3.09999999999999996e-165 or -3.99999999999999974e-275 < i < 9.4999999999999996e-235

   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. Taylor expanded in x around inf 60.2%

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

   3. Taylor expanded in y2 around inf 55.8%

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

   if -3.09999999999999996e-165 < i < -3.99999999999999974e-275

   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. Taylor expanded in y4 around inf 35.5%

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

      1. *-commutative 35.5%

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

      2. *-commutative 35.5%

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

   4. Simplified 35.5%

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

   5. Taylor expanded in y1 around inf 42.8%

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

   if 9.4999999999999996e-235 < i < 7.0000000000000002e-152

   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. Taylor expanded in y4 around inf 43.2%

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

      1. *-commutative 43.2%

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

      2. *-commutative 43.2%

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

   4. Simplified 43.2%

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

   5. Taylor expanded in k around inf 59.7%

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

      1. mul-1-neg 59.7%

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

      2. distribute-rgt-neg-in 59.7%

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

      3. associate-*r* 54.4%

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

      4. distribute-rgt-neg-in 54.4%

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

      5. *-commutative 54.4%

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

   7. Simplified 54.4%

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

   8. Taylor expanded in y2 around inf 53.8%

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

   if 7.0000000000000002e-152 < i < 2.75000000000000001e31

   1. Initial program 24.4%

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

   2. Taylor expanded in b around inf 44.7%

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

   3. Taylor expanded in t around inf 49.9%

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

      1. associate-*r* 47.5%

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

      2. +-commutative 47.5%

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

      3. mul-1-neg 47.5%

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

      4. unsub-neg 47.5%

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

   5. Simplified 47.5%

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

   if 2.75000000000000001e31 < i

   1. Initial program 24.1%

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

   2. Taylor expanded in x around inf 47.0%

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

   3. Taylor expanded in j around inf 41.1%

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

      1. *-commutative 41.1%

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

      2. *-commutative 41.1%

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

   5. Simplified 41.1%

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

4. Final simplification 49.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -1.95 \cdot 10^{+105}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;i \leq -4.2 \cdot 10^{+57}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;i \leq -3.2 \cdot 10^{-50}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;i \leq -3.1 \cdot 10^{-165}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -4 \cdot 10^{-275}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 9.5 \cdot 10^{-235}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 7 \cdot 10^{-152}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 2.75 \cdot 10^{+31}:\\ \;\;\;\;\left(t \cdot b\right) \cdot \left(j \cdot y4 - z \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]

Alternative 18: 28.5% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ t_2 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{if}\;z \leq -1.05 \cdot 10^{+132}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -4.5 \cdot 10^{+110}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -2020000000:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{-70}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+51}:\\ \;\;\;\;\left(y \cdot b\right) \cdot \left(x \cdot a - k \cdot y4\right)\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+100}:\\ \;\;\;\;\left(y0 \cdot y3\right) \cdot \left(j \cdot y5 - z \cdot c\right)\\ \mathbf{elif}\;z \leq 8.4 \cdot 10^{+130}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 2.3 \cdot 10^{+258}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y0 (- (* c y2) (* b j)))))
        (t_2 (* b (* t (- (* j y4) (* z a))))))
   (if (<= z -1.05e+132)
     t_2
     (if (<= z -4.5e+110)
       (* k (* y2 (- (* y1 y4) (* y0 y5))))
       (if (<= z -2020000000.0)
         t_2
         (if (<= z 1.3e-70)
           t_1
           (if (<= z 5e+51)
             (* (* y b) (- (* x a) (* k y4)))
             (if (<= z 2.8e+100)
               (* (* y0 y3) (- (* j y5) (* z c)))
               (if (<= z 8.4e+130)
                 t_2
                 (if (<= z 2.3e+258)
                   t_1
                   (* c (* y4 (- (* y y3) (* t y2))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (y0 * ((c * y2) - (b * j)));
	double t_2 = b * (t * ((j * y4) - (z * a)));
	double tmp;
	if (z <= -1.05e+132) {
		tmp = t_2;
	} else if (z <= -4.5e+110) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -2020000000.0) {
		tmp = t_2;
	} else if (z <= 1.3e-70) {
		tmp = t_1;
	} else if (z <= 5e+51) {
		tmp = (y * b) * ((x * a) - (k * y4));
	} else if (z <= 2.8e+100) {
		tmp = (y0 * y3) * ((j * y5) - (z * c));
	} else if (z <= 8.4e+130) {
		tmp = t_2;
	} else if (z <= 2.3e+258) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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 = x * (y0 * ((c * y2) - (b * j)))
    t_2 = b * (t * ((j * y4) - (z * a)))
    if (z <= (-1.05d+132)) then
        tmp = t_2
    else if (z <= (-4.5d+110)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (z <= (-2020000000.0d0)) then
        tmp = t_2
    else if (z <= 1.3d-70) then
        tmp = t_1
    else if (z <= 5d+51) then
        tmp = (y * b) * ((x * a) - (k * y4))
    else if (z <= 2.8d+100) then
        tmp = (y0 * y3) * ((j * y5) - (z * c))
    else if (z <= 8.4d+130) then
        tmp = t_2
    else if (z <= 2.3d+258) then
        tmp = t_1
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 = x * (y0 * ((c * y2) - (b * j)));
	double t_2 = b * (t * ((j * y4) - (z * a)));
	double tmp;
	if (z <= -1.05e+132) {
		tmp = t_2;
	} else if (z <= -4.5e+110) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -2020000000.0) {
		tmp = t_2;
	} else if (z <= 1.3e-70) {
		tmp = t_1;
	} else if (z <= 5e+51) {
		tmp = (y * b) * ((x * a) - (k * y4));
	} else if (z <= 2.8e+100) {
		tmp = (y0 * y3) * ((j * y5) - (z * c));
	} else if (z <= 8.4e+130) {
		tmp = t_2;
	} else if (z <= 2.3e+258) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = x * (y0 * ((c * y2) - (b * j)))
	t_2 = b * (t * ((j * y4) - (z * a)))
	tmp = 0
	if z <= -1.05e+132:
		tmp = t_2
	elif z <= -4.5e+110:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif z <= -2020000000.0:
		tmp = t_2
	elif z <= 1.3e-70:
		tmp = t_1
	elif z <= 5e+51:
		tmp = (y * b) * ((x * a) - (k * y4))
	elif z <= 2.8e+100:
		tmp = (y0 * y3) * ((j * y5) - (z * c))
	elif z <= 8.4e+130:
		tmp = t_2
	elif z <= 2.3e+258:
		tmp = t_1
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))))
	t_2 = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	tmp = 0.0
	if (z <= -1.05e+132)
		tmp = t_2;
	elseif (z <= -4.5e+110)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (z <= -2020000000.0)
		tmp = t_2;
	elseif (z <= 1.3e-70)
		tmp = t_1;
	elseif (z <= 5e+51)
		tmp = Float64(Float64(y * b) * Float64(Float64(x * a) - Float64(k * y4)));
	elseif (z <= 2.8e+100)
		tmp = Float64(Float64(y0 * y3) * Float64(Float64(j * y5) - Float64(z * c)));
	elseif (z <= 8.4e+130)
		tmp = t_2;
	elseif (z <= 2.3e+258)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = x * (y0 * ((c * y2) - (b * j)));
	t_2 = b * (t * ((j * y4) - (z * a)));
	tmp = 0.0;
	if (z <= -1.05e+132)
		tmp = t_2;
	elseif (z <= -4.5e+110)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (z <= -2020000000.0)
		tmp = t_2;
	elseif (z <= 1.3e-70)
		tmp = t_1;
	elseif (z <= 5e+51)
		tmp = (y * b) * ((x * a) - (k * y4));
	elseif (z <= 2.8e+100)
		tmp = (y0 * y3) * ((j * y5) - (z * c));
	elseif (z <= 8.4e+130)
		tmp = t_2;
	elseif (z <= 2.3e+258)
		tmp = t_1;
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.05e+132], t$95$2, If[LessEqual[z, -4.5e+110], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2020000000.0], t$95$2, If[LessEqual[z, 1.3e-70], t$95$1, If[LessEqual[z, 5e+51], N[(N[(y * b), $MachinePrecision] * N[(N[(x * a), $MachinePrecision] - N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.8e+100], N[(N[(y0 * y3), $MachinePrecision] * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8.4e+130], t$95$2, If[LessEqual[z, 2.3e+258], t$95$1, N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if z < -1.04999999999999997e132 or -4.5000000000000003e110 < z < -2.02e9 or 2.7999999999999998e100 < z < 8.39999999999999962e130

   1. Initial program 25.6%

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

   2. Taylor expanded in b around inf 46.3%

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

   3. Taylor expanded in t around -inf 54.9%

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

      1. mul-1-neg 54.9%

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

      2. distribute-rgt-neg-in 54.9%

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

      3. +-commutative 54.9%

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

      4. mul-1-neg 54.9%

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

      5. unsub-neg 54.9%

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

   5. Simplified 54.9%

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

   if -1.04999999999999997e132 < z < -4.5000000000000003e110

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 29.6%

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

      1. *-commutative 29.6%

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

      2. *-commutative 29.6%

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

   4. Simplified 29.6%

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

   5. Taylor expanded in k around inf 46.1%

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

      1. mul-1-neg 46.1%

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

      2. distribute-rgt-neg-in 46.1%

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

      3. associate-*r* 46.1%

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

      4. distribute-rgt-neg-in 46.1%

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

      5. *-commutative 46.1%

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

   7. Simplified 46.1%

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

   8. Taylor expanded in y2 around inf 72.2%

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

   if -2.02e9 < z < 1.30000000000000001e-70 or 8.39999999999999962e130 < z < 2.3000000000000001e258

   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. Taylor expanded in x around inf 49.1%

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

   3. Taylor expanded in y0 around inf 43.4%

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

      1. *-commutative 43.4%

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

      2. *-commutative 43.4%

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

   5. Simplified 43.4%

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

   if 1.30000000000000001e-70 < z < 5e51

   1. Initial program 18.0%

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

   2. Taylor expanded in b around inf 39.8%

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

   3. Taylor expanded in y around inf 64.6%

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

      1. associate-*r* 61.3%

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

      2. +-commutative 61.3%

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

      3. mul-1-neg 61.3%

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

      4. unsub-neg 61.3%

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

      5. *-commutative 61.3%

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

   5. Simplified 61.3%

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

   if 5e51 < z < 2.7999999999999998e100

   1. Initial program 50.0%

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

   2. Taylor expanded in y0 around inf 68.9%

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

   3. Taylor expanded in y3 around inf 52.0%

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

      1. associate-*r* 59.4%

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

      2. +-commutative 59.4%

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

      3. mul-1-neg 59.4%

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

      4. unsub-neg 59.4%

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

   5. Simplified 59.4%

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

   if 2.3000000000000001e258 < z

   1. Initial program 16.7%

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

   2. Taylor expanded in y4 around inf 50.4%

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

      1. *-commutative 50.4%

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

      2. *-commutative 50.4%

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

   4. Simplified 50.4%

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

   5. Taylor expanded in c around inf 58.7%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 50.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.05 \cdot 10^{+132}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -4.5 \cdot 10^{+110}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -2020000000:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+51}:\\ \;\;\;\;\left(y \cdot b\right) \cdot \left(x \cdot a - k \cdot y4\right)\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+100}:\\ \;\;\;\;\left(y0 \cdot y3\right) \cdot \left(j \cdot y5 - z \cdot c\right)\\ \mathbf{elif}\;z \leq 8.4 \cdot 10^{+130}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 2.3 \cdot 10^{+258}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 19: 20.6% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{if}\;c \leq -1.05 \cdot 10^{+131}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -18000:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;c \leq 3.3 \cdot 10^{-238}:\\ \;\;\;\;x \cdot \left(b \cdot \left(j \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;c \leq 3.6 \cdot 10^{-179}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;c \leq 5 \cdot 10^{-20}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 1.2 \cdot 10^{+30}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+101}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;c \leq 3 \cdot 10^{+131}:\\ \;\;\;\;\left(a \cdot b\right) \cdot \left(z \cdot \left(-t\right)\right)\\ \mathbf{elif}\;c \leq 4.4 \cdot 10^{+250}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y0 (* c y2)))))
   (if (<= c -1.05e+131)
     t_1
     (if (<= c -18000.0)
       (* (* x y) (* a b))
       (if (<= c 3.3e-238)
         (* x (* b (* j (- y0))))
         (if (<= c 3.6e-179)
           (* a (* (* z t) (- b)))
           (if (<= c 5e-20)
             (* i (* j (* x y1)))
             (if (<= c 1.2e+30)
               (* b (* t (* z (- a))))
               (if (<= c 2.9e+101)
                 (* b (* k (* y (- y4))))
                 (if (<= c 3e+131)
                   (* (* a b) (* z (- t)))
                   (if (<= c 4.4e+250) (* c (* y (* y3 y4))) t_1)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (y0 * (c * y2));
	double tmp;
	if (c <= -1.05e+131) {
		tmp = t_1;
	} else if (c <= -18000.0) {
		tmp = (x * y) * (a * b);
	} else if (c <= 3.3e-238) {
		tmp = x * (b * (j * -y0));
	} else if (c <= 3.6e-179) {
		tmp = a * ((z * t) * -b);
	} else if (c <= 5e-20) {
		tmp = i * (j * (x * y1));
	} else if (c <= 1.2e+30) {
		tmp = b * (t * (z * -a));
	} else if (c <= 2.9e+101) {
		tmp = b * (k * (y * -y4));
	} else if (c <= 3e+131) {
		tmp = (a * b) * (z * -t);
	} else if (c <= 4.4e+250) {
		tmp = c * (y * (y3 * y4));
	} 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 = x * (y0 * (c * y2))
    if (c <= (-1.05d+131)) then
        tmp = t_1
    else if (c <= (-18000.0d0)) then
        tmp = (x * y) * (a * b)
    else if (c <= 3.3d-238) then
        tmp = x * (b * (j * -y0))
    else if (c <= 3.6d-179) then
        tmp = a * ((z * t) * -b)
    else if (c <= 5d-20) then
        tmp = i * (j * (x * y1))
    else if (c <= 1.2d+30) then
        tmp = b * (t * (z * -a))
    else if (c <= 2.9d+101) then
        tmp = b * (k * (y * -y4))
    else if (c <= 3d+131) then
        tmp = (a * b) * (z * -t)
    else if (c <= 4.4d+250) then
        tmp = c * (y * (y3 * y4))
    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 * (y0 * (c * y2));
	double tmp;
	if (c <= -1.05e+131) {
		tmp = t_1;
	} else if (c <= -18000.0) {
		tmp = (x * y) * (a * b);
	} else if (c <= 3.3e-238) {
		tmp = x * (b * (j * -y0));
	} else if (c <= 3.6e-179) {
		tmp = a * ((z * t) * -b);
	} else if (c <= 5e-20) {
		tmp = i * (j * (x * y1));
	} else if (c <= 1.2e+30) {
		tmp = b * (t * (z * -a));
	} else if (c <= 2.9e+101) {
		tmp = b * (k * (y * -y4));
	} else if (c <= 3e+131) {
		tmp = (a * b) * (z * -t);
	} else if (c <= 4.4e+250) {
		tmp = c * (y * (y3 * y4));
	} 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 * (y0 * (c * y2))
	tmp = 0
	if c <= -1.05e+131:
		tmp = t_1
	elif c <= -18000.0:
		tmp = (x * y) * (a * b)
	elif c <= 3.3e-238:
		tmp = x * (b * (j * -y0))
	elif c <= 3.6e-179:
		tmp = a * ((z * t) * -b)
	elif c <= 5e-20:
		tmp = i * (j * (x * y1))
	elif c <= 1.2e+30:
		tmp = b * (t * (z * -a))
	elif c <= 2.9e+101:
		tmp = b * (k * (y * -y4))
	elif c <= 3e+131:
		tmp = (a * b) * (z * -t)
	elif c <= 4.4e+250:
		tmp = c * (y * (y3 * y4))
	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(y0 * Float64(c * y2)))
	tmp = 0.0
	if (c <= -1.05e+131)
		tmp = t_1;
	elseif (c <= -18000.0)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (c <= 3.3e-238)
		tmp = Float64(x * Float64(b * Float64(j * Float64(-y0))));
	elseif (c <= 3.6e-179)
		tmp = Float64(a * Float64(Float64(z * t) * Float64(-b)));
	elseif (c <= 5e-20)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (c <= 1.2e+30)
		tmp = Float64(b * Float64(t * Float64(z * Float64(-a))));
	elseif (c <= 2.9e+101)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (c <= 3e+131)
		tmp = Float64(Float64(a * b) * Float64(z * Float64(-t)));
	elseif (c <= 4.4e+250)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	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 * (y0 * (c * y2));
	tmp = 0.0;
	if (c <= -1.05e+131)
		tmp = t_1;
	elseif (c <= -18000.0)
		tmp = (x * y) * (a * b);
	elseif (c <= 3.3e-238)
		tmp = x * (b * (j * -y0));
	elseif (c <= 3.6e-179)
		tmp = a * ((z * t) * -b);
	elseif (c <= 5e-20)
		tmp = i * (j * (x * y1));
	elseif (c <= 1.2e+30)
		tmp = b * (t * (z * -a));
	elseif (c <= 2.9e+101)
		tmp = b * (k * (y * -y4));
	elseif (c <= 3e+131)
		tmp = (a * b) * (z * -t);
	elseif (c <= 4.4e+250)
		tmp = c * (y * (y3 * y4));
	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[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.05e+131], t$95$1, If[LessEqual[c, -18000.0], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.3e-238], N[(x * N[(b * N[(j * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.6e-179], N[(a * N[(N[(z * t), $MachinePrecision] * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5e-20], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.2e+30], N[(b * N[(t * N[(z * (-a)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.9e+101], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3e+131], N[(N[(a * b), $MachinePrecision] * N[(z * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 4.4e+250], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if c < -1.04999999999999993e131 or 4.40000000000000029e250 < c

   1. Initial program 13.3%

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

   2. Taylor expanded in x around inf 45.4%

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

   3. Taylor expanded in y0 around inf 55.6%

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

      1. *-commutative 55.6%

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

      2. *-commutative 55.6%

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

   5. Simplified 55.6%

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

   6. Taylor expanded in y2 around inf 52.0%

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

      1. *-commutative 52.0%

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

   8. Simplified 52.0%

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

   if -1.04999999999999993e131 < c < -18000

   1. Initial program 12.1%

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

   2. Taylor expanded in b around inf 48.5%

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

   3. Taylor expanded in y around inf 56.6%

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

      1. associate-*r* 52.6%

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

      2. +-commutative 52.6%

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

      3. mul-1-neg 52.6%

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

      4. unsub-neg 52.6%

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

      5. *-commutative 52.6%

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

   5. Simplified 52.6%

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

   6. Taylor expanded in a around inf 41.3%

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

      1. associate-*r* 45.1%

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

      2. *-commutative 45.1%

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

   8. Simplified 45.1%

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

   if -18000 < c < 3.2999999999999997e-238

   1. Initial program 50.0%

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

   2. Taylor expanded in x around inf 43.2%

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

   3. Taylor expanded in y0 around inf 32.0%

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

      1. *-commutative 32.0%

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

      2. *-commutative 32.0%

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

   5. Simplified 32.0%

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

   6. Taylor expanded in y2 around 0 30.3%

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

      1. mul-1-neg 30.3%

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

      2. *-commutative 30.3%

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

   8. Simplified 30.3%

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

   if 3.2999999999999997e-238 < c < 3.60000000000000007e-179

   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. Taylor expanded in b around inf 71.5%

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

   3. Taylor expanded in a around inf 71.5%

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

   4. Taylor expanded in x around 0 71.8%

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

      1. associate-*r* 71.8%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(t \cdot z\right)\right)} \]

      2. neg-mul-1 71.8%

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

   6. Simplified 71.8%

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

   if 3.60000000000000007e-179 < c < 4.9999999999999999e-20

   1. Initial program 33.3%

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

   2. Taylor expanded in x around inf 34.3%

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

   3. Taylor expanded in y around 0 34.7%

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

      1. *-commutative 34.7%

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

      2. *-commutative 34.7%

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

   5. Simplified 34.7%

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

   6. Taylor expanded in i around inf 24.8%

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

   if 4.9999999999999999e-20 < c < 1.2e30

   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. Taylor expanded in b around inf 63.7%

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

   3. Taylor expanded in t around -inf 51.3%

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

      1. mul-1-neg 51.3%

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

      2. distribute-rgt-neg-in 51.3%

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

      3. +-commutative 51.3%

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

      4. mul-1-neg 51.3%

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

      5. unsub-neg 51.3%

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

   5. Simplified 51.3%

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

   6. Taylor expanded in a around inf 51.2%

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

   if 1.2e30 < c < 2.89999999999999987e101

   1. Initial program 26.3%

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

   2. Taylor expanded in b around inf 27.4%

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

   3. Taylor expanded in y around inf 48.9%

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

      1. associate-*r* 33.5%

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

      2. +-commutative 33.5%

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

      3. mul-1-neg 33.5%

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

      4. unsub-neg 33.5%

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

      5. *-commutative 33.5%

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

   5. Simplified 33.5%

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

   6. Taylor expanded in a around 0 43.2%

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

      1. mul-1-neg 43.2%

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

   8. Simplified 43.2%

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

   if 2.89999999999999987e101 < c < 3.0000000000000001e131

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 60.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 51.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(b \cdot \left(t \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 51.3%

         \[\leadsto \color{blue}{-a \cdot \left(b \cdot \left(t \cdot z\right)\right)} \]

      2. associate-*r* 60.6%

         \[\leadsto -\color{blue}{\left(a \cdot b\right) \cdot \left(t \cdot z\right)} \]

      3. distribute-rgt-neg-in 60.6%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(-t \cdot z\right)} \]

      4. distribute-rgt-neg-in 60.6%

         \[\leadsto \left(a \cdot b\right) \cdot \color{blue}{\left(t \cdot \left(-z\right)\right)} \]

   6. Simplified 60.6%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(t \cdot \left(-z\right)\right)} \]

   if 3.0000000000000001e131 < c < 4.40000000000000029e250

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 43.9%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 43.9%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.9%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 43.9%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 63.7%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 57.0%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 57.0%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 57.0%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 47.8%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. *-commutative 47.8%

         \[\leadsto c \cdot \left(y \cdot \color{blue}{\left(y4 \cdot y3\right)}\right) \]

   10. Simplified 47.8%

       \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y4 \cdot y3\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 42.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1.05 \cdot 10^{+131}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq -18000:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;c \leq 3.3 \cdot 10^{-238}:\\ \;\;\;\;x \cdot \left(b \cdot \left(j \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;c \leq 3.6 \cdot 10^{-179}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;c \leq 5 \cdot 10^{-20}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 1.2 \cdot 10^{+30}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+101}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;c \leq 3 \cdot 10^{+131}:\\ \;\;\;\;\left(a \cdot b\right) \cdot \left(z \cdot \left(-t\right)\right)\\ \mathbf{elif}\;c \leq 4.4 \cdot 10^{+250}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \end{array} \]

Alternative 20: 23.9% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;y4 \leq -1.35 \cdot 10^{+221}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -5.5 \cdot 10^{-19}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -2.45 \cdot 10^{-39}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq -5.4 \cdot 10^{-72}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;y4 \leq -2.5 \cdot 10^{-234}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(c \cdot \left(-i\right)\right)\\ \mathbf{elif}\;y4 \leq 5 \cdot 10^{-302}:\\ \;\;\;\;x \cdot \left(b \cdot \left(j \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;y4 \leq 2.1 \cdot 10^{+113}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* b (- (* x y) (* z t))))))
   (if (<= y4 -1.35e+221)
     (* c (* y (* y3 y4)))
     (if (<= y4 -5.5e-19)
       (* x (* y0 (* c y2)))
       (if (<= y4 -2.45e-39)
         t_1
         (if (<= y4 -5.4e-72)
           (* b (* t (* z (- a))))
           (if (<= y4 -2.5e-234)
             (* (* x y) (* c (- i)))
             (if (<= y4 5e-302)
               (* x (* b (* j (- y0))))
               (if (<= y4 2.1e+113) t_1 (* b (* t (* j y4))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y4 <= -1.35e+221) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -5.5e-19) {
		tmp = x * (y0 * (c * y2));
	} else if (y4 <= -2.45e-39) {
		tmp = t_1;
	} else if (y4 <= -5.4e-72) {
		tmp = b * (t * (z * -a));
	} else if (y4 <= -2.5e-234) {
		tmp = (x * y) * (c * -i);
	} else if (y4 <= 5e-302) {
		tmp = x * (b * (j * -y0));
	} else if (y4 <= 2.1e+113) {
		tmp = t_1;
	} else {
		tmp = b * (t * (j * y4));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (b * ((x * y) - (z * t)))
    if (y4 <= (-1.35d+221)) then
        tmp = c * (y * (y3 * y4))
    else if (y4 <= (-5.5d-19)) then
        tmp = x * (y0 * (c * y2))
    else if (y4 <= (-2.45d-39)) then
        tmp = t_1
    else if (y4 <= (-5.4d-72)) then
        tmp = b * (t * (z * -a))
    else if (y4 <= (-2.5d-234)) then
        tmp = (x * y) * (c * -i)
    else if (y4 <= 5d-302) then
        tmp = x * (b * (j * -y0))
    else if (y4 <= 2.1d+113) then
        tmp = t_1
    else
        tmp = b * (t * (j * y4))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y4 <= -1.35e+221) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -5.5e-19) {
		tmp = x * (y0 * (c * y2));
	} else if (y4 <= -2.45e-39) {
		tmp = t_1;
	} else if (y4 <= -5.4e-72) {
		tmp = b * (t * (z * -a));
	} else if (y4 <= -2.5e-234) {
		tmp = (x * y) * (c * -i);
	} else if (y4 <= 5e-302) {
		tmp = x * (b * (j * -y0));
	} else if (y4 <= 2.1e+113) {
		tmp = t_1;
	} else {
		tmp = b * (t * (j * y4));
	}
	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 y4 <= -1.35e+221:
		tmp = c * (y * (y3 * y4))
	elif y4 <= -5.5e-19:
		tmp = x * (y0 * (c * y2))
	elif y4 <= -2.45e-39:
		tmp = t_1
	elif y4 <= -5.4e-72:
		tmp = b * (t * (z * -a))
	elif y4 <= -2.5e-234:
		tmp = (x * y) * (c * -i)
	elif y4 <= 5e-302:
		tmp = x * (b * (j * -y0))
	elif y4 <= 2.1e+113:
		tmp = t_1
	else:
		tmp = b * (t * (j * y4))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (y4 <= -1.35e+221)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	elseif (y4 <= -5.5e-19)
		tmp = Float64(x * Float64(y0 * Float64(c * y2)));
	elseif (y4 <= -2.45e-39)
		tmp = t_1;
	elseif (y4 <= -5.4e-72)
		tmp = Float64(b * Float64(t * Float64(z * Float64(-a))));
	elseif (y4 <= -2.5e-234)
		tmp = Float64(Float64(x * y) * Float64(c * Float64(-i)));
	elseif (y4 <= 5e-302)
		tmp = Float64(x * Float64(b * Float64(j * Float64(-y0))));
	elseif (y4 <= 2.1e+113)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(t * Float64(j * y4)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (b * ((x * y) - (z * t)));
	tmp = 0.0;
	if (y4 <= -1.35e+221)
		tmp = c * (y * (y3 * y4));
	elseif (y4 <= -5.5e-19)
		tmp = x * (y0 * (c * y2));
	elseif (y4 <= -2.45e-39)
		tmp = t_1;
	elseif (y4 <= -5.4e-72)
		tmp = b * (t * (z * -a));
	elseif (y4 <= -2.5e-234)
		tmp = (x * y) * (c * -i);
	elseif (y4 <= 5e-302)
		tmp = x * (b * (j * -y0));
	elseif (y4 <= 2.1e+113)
		tmp = t_1;
	else
		tmp = b * (t * (j * y4));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.35e+221], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -5.5e-19], N[(x * N[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -2.45e-39], t$95$1, If[LessEqual[y4, -5.4e-72], N[(b * N[(t * N[(z * (-a)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -2.5e-234], N[(N[(x * y), $MachinePrecision] * N[(c * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 5e-302], N[(x * N[(b * N[(j * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 2.1e+113], t$95$1, N[(b * N[(t * N[(j * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y4 < -1.35e221

   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. Taylor expanded in y4 around inf 27.1%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 27.1%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 27.1%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 27.1%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 73.5%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 54.6%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 54.6%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 54.6%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 67.1%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. *-commutative 67.1%

         \[\leadsto c \cdot \left(y \cdot \color{blue}{\left(y4 \cdot y3\right)}\right) \]

   10. Simplified 67.1%

       \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y4 \cdot y3\right)\right)} \]

   if -1.35e221 < y4 < -5.4999999999999996e-19

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 46.1%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 41.9%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.9%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 41.9%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 41.9%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 43.9%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 43.9%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 43.9%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   if -5.4999999999999996e-19 < y4 < -2.44999999999999987e-39 or 5.00000000000000033e-302 < y4 < 2.0999999999999999e113

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 42.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 41.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -2.44999999999999987e-39 < y4 < -5.4e-72

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 50.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 50.6%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 50.6%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 50.6%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 50.6%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 50.6%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 50.6%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 50.6%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 50.6%

      \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z\right)}\right) \]

   if -5.4e-72 < y4 < -2.49999999999999989e-234

   1. Initial program 29.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 56.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 48.7%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in i around inf 40.5%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 40.5%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. associate-*r* 41.8%

         \[\leadsto -\color{blue}{\left(c \cdot i\right) \cdot \left(x \cdot y\right)} \]

      3. distribute-rgt-neg-in 41.8%

         \[\leadsto \color{blue}{\left(c \cdot i\right) \cdot \left(-x \cdot y\right)} \]

   6. Simplified 41.8%

      \[\leadsto \color{blue}{\left(c \cdot i\right) \cdot \left(-x \cdot y\right)} \]

   if -2.49999999999999989e-234 < y4 < 5.00000000000000033e-302

   1. Initial program 22.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 41.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 49.0%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 49.0%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 49.0%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 49.0%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around 0 34.2%

      \[\leadsto x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(j \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 34.2%

         \[\leadsto x \cdot \color{blue}{\left(-b \cdot \left(j \cdot y0\right)\right)} \]

      2. *-commutative 34.2%

         \[\leadsto x \cdot \left(-b \cdot \color{blue}{\left(y0 \cdot j\right)}\right) \]

   8. Simplified 34.2%

      \[\leadsto x \cdot \color{blue}{\left(-b \cdot \left(y0 \cdot j\right)\right)} \]

   if 2.0999999999999999e113 < y4

   1. Initial program 14.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 34.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 43.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 43.8%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 43.8%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 43.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 43.8%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 43.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 44.1%

      \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(-1 \cdot \left(j \cdot y4\right)\right)}\right) \]
   7. Step-by-step derivation

      1. neg-mul-1 44.1%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(-j \cdot y4\right)}\right) \]

      2. distribute-lft-neg-in 44.1%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(\left(-j\right) \cdot y4\right)}\right) \]

      3. *-commutative 44.1%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(y4 \cdot \left(-j\right)\right)}\right) \]

   8. Simplified 44.1%

      \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(y4 \cdot \left(-j\right)\right)}\right) \]
3. Recombined 7 regimes into one program.

4. Final simplification 43.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.35 \cdot 10^{+221}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -5.5 \cdot 10^{-19}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -2.45 \cdot 10^{-39}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y4 \leq -5.4 \cdot 10^{-72}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;y4 \leq -2.5 \cdot 10^{-234}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(c \cdot \left(-i\right)\right)\\ \mathbf{elif}\;y4 \leq 5 \cdot 10^{-302}:\\ \;\;\;\;x \cdot \left(b \cdot \left(j \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;y4 \leq 2.1 \cdot 10^{+113}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4\right)\right)\\ \end{array} \]

Alternative 21: 27.9% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{if}\;z \leq -6.4 \cdot 10^{+131}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{+93}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -1.35 \cdot 10^{+37}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-77}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 4 \cdot 10^{+73}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 9.5 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+224}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* t (* z (- a))))))
   (if (<= z -6.4e+131)
     t_1
     (if (<= z -1.4e+93)
       (* k (* y2 (- (* y1 y4) (* y0 y5))))
       (if (<= z -1.35e+37)
         t_1
         (if (<= z 1.35e-77)
           (* x (* y0 (- (* c y2) (* b j))))
           (if (<= z 4e+73)
             (* x (* y (- (* a b) (* c i))))
             (if (<= z 9.5e+141)
               (* b (* y0 (- (* z k) (* x j))))
               (if (<= z 1.1e+224)
                 (* a (* b (- (* x y) (* z t))))
                 (* c (* y4 (- (* y y3) (* t y2)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (t * (z * -a));
	double tmp;
	if (z <= -6.4e+131) {
		tmp = t_1;
	} else if (z <= -1.4e+93) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -1.35e+37) {
		tmp = t_1;
	} else if (z <= 1.35e-77) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (z <= 4e+73) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 9.5e+141) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (z <= 1.1e+224) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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) :: tmp
    t_1 = b * (t * (z * -a))
    if (z <= (-6.4d+131)) then
        tmp = t_1
    else if (z <= (-1.4d+93)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (z <= (-1.35d+37)) then
        tmp = t_1
    else if (z <= 1.35d-77) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else if (z <= 4d+73) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (z <= 9.5d+141) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (z <= 1.1d+224) then
        tmp = a * (b * ((x * y) - (z * t)))
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 = b * (t * (z * -a));
	double tmp;
	if (z <= -6.4e+131) {
		tmp = t_1;
	} else if (z <= -1.4e+93) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -1.35e+37) {
		tmp = t_1;
	} else if (z <= 1.35e-77) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else if (z <= 4e+73) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 9.5e+141) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (z <= 1.1e+224) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (t * (z * -a))
	tmp = 0
	if z <= -6.4e+131:
		tmp = t_1
	elif z <= -1.4e+93:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif z <= -1.35e+37:
		tmp = t_1
	elif z <= 1.35e-77:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	elif z <= 4e+73:
		tmp = x * (y * ((a * b) - (c * i)))
	elif z <= 9.5e+141:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif z <= 1.1e+224:
		tmp = a * (b * ((x * y) - (z * t)))
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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(b * Float64(t * Float64(z * Float64(-a))))
	tmp = 0.0
	if (z <= -6.4e+131)
		tmp = t_1;
	elseif (z <= -1.4e+93)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (z <= -1.35e+37)
		tmp = t_1;
	elseif (z <= 1.35e-77)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (z <= 4e+73)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (z <= 9.5e+141)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (z <= 1.1e+224)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = b * (t * (z * -a));
	tmp = 0.0;
	if (z <= -6.4e+131)
		tmp = t_1;
	elseif (z <= -1.4e+93)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (z <= -1.35e+37)
		tmp = t_1;
	elseif (z <= 1.35e-77)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	elseif (z <= 4e+73)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (z <= 9.5e+141)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (z <= 1.1e+224)
		tmp = a * (b * ((x * y) - (z * t)));
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[(b * N[(t * N[(z * (-a)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -6.4e+131], t$95$1, If[LessEqual[z, -1.4e+93], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.35e+37], t$95$1, If[LessEqual[z, 1.35e-77], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4e+73], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.5e+141], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.1e+224], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if z < -6.4000000000000004e131 or -1.39999999999999994e93 < z < -1.34999999999999993e37

   1. Initial program 28.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 46.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 56.9%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 56.9%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 56.9%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 56.9%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 56.9%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 56.9%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 56.9%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 46.3%

      \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z\right)}\right) \]

   if -6.4000000000000004e131 < z < -1.39999999999999994e93

   1. Initial program 20.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 30.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 30.7%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 30.7%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 30.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in k around inf 32.3%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   6. Step-by-step derivation

      1. mul-1-neg 32.3%

         \[\leadsto \color{blue}{\left(-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. distribute-rgt-neg-in 32.3%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      3. associate-*r* 32.3%

         \[\leadsto b \cdot \left(-\color{blue}{\left(k \cdot y\right) \cdot y4}\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      4. distribute-rgt-neg-in 32.3%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot \left(-y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      5. *-commutative 32.3%

         \[\leadsto b \cdot \left(\color{blue}{\left(y \cdot k\right)} \cdot \left(-y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Simplified 32.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot k\right) \cdot \left(-y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   8. Taylor expanded in y2 around inf 60.8%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if -1.34999999999999993e37 < z < 1.35e-77

   1. Initial program 34.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 48.8%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 39.8%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 39.8%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 39.8%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 39.8%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   if 1.35e-77 < z < 3.99999999999999993e73

   1. Initial program 21.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 49.1%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around inf 57.4%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 3.99999999999999993e73 < z < 9.49999999999999974e141

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 27.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 54.6%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if 9.49999999999999974e141 < z < 1.1e224

   1. Initial program 19.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 60.9%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if 1.1e224 < z

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 56.0%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 56.0%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 56.0%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 56.0%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in c around inf 50.5%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 46.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -6.4 \cdot 10^{+131}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{+93}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -1.35 \cdot 10^{+37}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-77}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 4 \cdot 10^{+73}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 9.5 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+224}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 22: 29.9% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{if}\;z \leq -3.4 \cdot 10^{+132}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -2.45 \cdot 10^{+104}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -2400000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{-120}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+70}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+128}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 3.9 \cdot 10^{+178}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* t (- (* j y4) (* z a))))))
   (if (<= z -3.4e+132)
     t_1
     (if (<= z -2.45e+104)
       (* k (* y2 (- (* y1 y4) (* y0 y5))))
       (if (<= z -2400000000.0)
         t_1
         (if (<= z 9.2e-120)
           (* x (- (* j (- (* i y1) (* b y0))) (* a (* y1 y2))))
           (if (<= z 1.8e+70)
             (* (* x c) (- (* y0 y2) (* y i)))
             (if (<= z 3.1e+128)
               (* b (* y0 (- (* z k) (* x j))))
               (if (<= z 3.9e+178)
                 (* x (* y0 (- (* c y2) (* b j))))
                 (* c (* y4 (- (* y y3) (* t y2)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (t * ((j * y4) - (z * a)));
	double tmp;
	if (z <= -3.4e+132) {
		tmp = t_1;
	} else if (z <= -2.45e+104) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -2400000000.0) {
		tmp = t_1;
	} else if (z <= 9.2e-120) {
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	} else if (z <= 1.8e+70) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (z <= 3.1e+128) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (z <= 3.9e+178) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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) :: tmp
    t_1 = b * (t * ((j * y4) - (z * a)))
    if (z <= (-3.4d+132)) then
        tmp = t_1
    else if (z <= (-2.45d+104)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (z <= (-2400000000.0d0)) then
        tmp = t_1
    else if (z <= 9.2d-120) then
        tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
    else if (z <= 1.8d+70) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (z <= 3.1d+128) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (z <= 3.9d+178) then
        tmp = x * (y0 * ((c * y2) - (b * j)))
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 = b * (t * ((j * y4) - (z * a)));
	double tmp;
	if (z <= -3.4e+132) {
		tmp = t_1;
	} else if (z <= -2.45e+104) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (z <= -2400000000.0) {
		tmp = t_1;
	} else if (z <= 9.2e-120) {
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	} else if (z <= 1.8e+70) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (z <= 3.1e+128) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (z <= 3.9e+178) {
		tmp = x * (y0 * ((c * y2) - (b * j)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (t * ((j * y4) - (z * a)))
	tmp = 0
	if z <= -3.4e+132:
		tmp = t_1
	elif z <= -2.45e+104:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif z <= -2400000000.0:
		tmp = t_1
	elif z <= 9.2e-120:
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)))
	elif z <= 1.8e+70:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif z <= 3.1e+128:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif z <= 3.9e+178:
		tmp = x * (y0 * ((c * y2) - (b * j)))
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	tmp = 0.0
	if (z <= -3.4e+132)
		tmp = t_1;
	elseif (z <= -2.45e+104)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (z <= -2400000000.0)
		tmp = t_1;
	elseif (z <= 9.2e-120)
		tmp = Float64(x * Float64(Float64(j * Float64(Float64(i * y1) - Float64(b * y0))) - Float64(a * Float64(y1 * y2))));
	elseif (z <= 1.8e+70)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (z <= 3.1e+128)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (z <= 3.9e+178)
		tmp = Float64(x * Float64(y0 * Float64(Float64(c * y2) - Float64(b * j))));
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = b * (t * ((j * y4) - (z * a)));
	tmp = 0.0;
	if (z <= -3.4e+132)
		tmp = t_1;
	elseif (z <= -2.45e+104)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (z <= -2400000000.0)
		tmp = t_1;
	elseif (z <= 9.2e-120)
		tmp = x * ((j * ((i * y1) - (b * y0))) - (a * (y1 * y2)));
	elseif (z <= 1.8e+70)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (z <= 3.1e+128)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (z <= 3.9e+178)
		tmp = x * (y0 * ((c * y2) - (b * j)));
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3.4e+132], t$95$1, If[LessEqual[z, -2.45e+104], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2400000000.0], t$95$1, If[LessEqual[z, 9.2e-120], N[(x * N[(N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e+70], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.1e+128], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.9e+178], N[(x * N[(y0 * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if z < -3.40000000000000025e132 or -2.44999999999999993e104 < z < -2.4e9

   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. Taylor expanded in b around inf 45.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 53.5%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 53.5%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 53.5%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 53.5%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 53.5%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 53.5%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 53.5%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   if -3.40000000000000025e132 < z < -2.44999999999999993e104

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 29.6%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 29.6%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 29.6%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 29.6%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in k around inf 46.1%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   6. Step-by-step derivation

      1. mul-1-neg 46.1%

         \[\leadsto \color{blue}{\left(-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. distribute-rgt-neg-in 46.1%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      3. associate-*r* 46.1%

         \[\leadsto b \cdot \left(-\color{blue}{\left(k \cdot y\right) \cdot y4}\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      4. distribute-rgt-neg-in 46.1%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot \left(-y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      5. *-commutative 46.1%

         \[\leadsto b \cdot \left(\color{blue}{\left(y \cdot k\right)} \cdot \left(-y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Simplified 46.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot k\right) \cdot \left(-y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   8. Taylor expanded in y2 around inf 72.2%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if -2.4e9 < z < 9.19999999999999946e-120

   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. Taylor expanded in x around inf 50.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 49.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 49.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 49.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 49.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in c around 0 43.4%

      \[\leadsto x \cdot \left(\color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 43.4%

         \[\leadsto x \cdot \left(\color{blue}{\left(-a \cdot \left(y1 \cdot y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]

      2. distribute-rgt-neg-in 43.4%

         \[\leadsto x \cdot \left(\color{blue}{a \cdot \left(-y1 \cdot y2\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]

      3. distribute-rgt-neg-in 43.4%

         \[\leadsto x \cdot \left(a \cdot \color{blue}{\left(y1 \cdot \left(-y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]

   8. Simplified 43.4%

      \[\leadsto x \cdot \left(\color{blue}{a \cdot \left(y1 \cdot \left(-y2\right)\right)} - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) \]

   if 9.19999999999999946e-120 < z < 1.8e70

   1. Initial program 22.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 47.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in c around inf 48.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 52.1%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 52.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 52.1%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 52.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

      5. *-commutative 52.1%

         \[\leadsto \left(c \cdot x\right) \cdot \left(\color{blue}{y2 \cdot y0} - i \cdot y\right) \]

   5. Simplified 52.1%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y2 \cdot y0 - i \cdot y\right)} \]

   if 1.8e70 < z < 3.10000000000000004e128

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 41.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 60.8%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if 3.10000000000000004e128 < z < 3.8999999999999997e178

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 44.9%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 78.0%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 78.0%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 78.0%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 78.0%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   if 3.8999999999999997e178 < z

   1. Initial program 16.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 50.9%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 50.9%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 50.9%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 50.9%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in c around inf 50.6%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 50.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.4 \cdot 10^{+132}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -2.45 \cdot 10^{+104}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq -2400000000:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{-120}:\\ \;\;\;\;x \cdot \left(j \cdot \left(i \cdot y1 - b \cdot y0\right) - a \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+70}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+128}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 3.9 \cdot 10^{+178}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 23: 21.3% accurate, 4.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{if}\;c \leq -1 \cdot 10^{+126}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -1.42 \cdot 10^{-6}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;c \leq 3.8 \cdot 10^{-235}:\\ \;\;\;\;x \cdot \left(b \cdot \left(j \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{-179}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;c \leq 5 \cdot 10^{-19}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 4.6 \cdot 10^{+24}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;c \leq 1.75 \cdot 10^{+140}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y0 (* c y2)))))
   (if (<= c -1e+126)
     t_1
     (if (<= c -1.42e-6)
       (* (* x y) (* a b))
       (if (<= c 3.8e-235)
         (* x (* b (* j (- y0))))
         (if (<= c 2.4e-179)
           (* a (* (* z t) (- b)))
           (if (<= c 5e-19)
             (* i (* j (* x y1)))
             (if (<= c 4.6e+24)
               (* b (* t (* z (- a))))
               (if (<= c 1.75e+140) (* b (* k (* y (- y4)))) t_1)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = x * (y0 * (c * y2));
	double tmp;
	if (c <= -1e+126) {
		tmp = t_1;
	} else if (c <= -1.42e-6) {
		tmp = (x * y) * (a * b);
	} else if (c <= 3.8e-235) {
		tmp = x * (b * (j * -y0));
	} else if (c <= 2.4e-179) {
		tmp = a * ((z * t) * -b);
	} else if (c <= 5e-19) {
		tmp = i * (j * (x * y1));
	} else if (c <= 4.6e+24) {
		tmp = b * (t * (z * -a));
	} else if (c <= 1.75e+140) {
		tmp = b * (k * (y * -y4));
	} 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 = x * (y0 * (c * y2))
    if (c <= (-1d+126)) then
        tmp = t_1
    else if (c <= (-1.42d-6)) then
        tmp = (x * y) * (a * b)
    else if (c <= 3.8d-235) then
        tmp = x * (b * (j * -y0))
    else if (c <= 2.4d-179) then
        tmp = a * ((z * t) * -b)
    else if (c <= 5d-19) then
        tmp = i * (j * (x * y1))
    else if (c <= 4.6d+24) then
        tmp = b * (t * (z * -a))
    else if (c <= 1.75d+140) then
        tmp = b * (k * (y * -y4))
    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 * (y0 * (c * y2));
	double tmp;
	if (c <= -1e+126) {
		tmp = t_1;
	} else if (c <= -1.42e-6) {
		tmp = (x * y) * (a * b);
	} else if (c <= 3.8e-235) {
		tmp = x * (b * (j * -y0));
	} else if (c <= 2.4e-179) {
		tmp = a * ((z * t) * -b);
	} else if (c <= 5e-19) {
		tmp = i * (j * (x * y1));
	} else if (c <= 4.6e+24) {
		tmp = b * (t * (z * -a));
	} else if (c <= 1.75e+140) {
		tmp = b * (k * (y * -y4));
	} 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 * (y0 * (c * y2))
	tmp = 0
	if c <= -1e+126:
		tmp = t_1
	elif c <= -1.42e-6:
		tmp = (x * y) * (a * b)
	elif c <= 3.8e-235:
		tmp = x * (b * (j * -y0))
	elif c <= 2.4e-179:
		tmp = a * ((z * t) * -b)
	elif c <= 5e-19:
		tmp = i * (j * (x * y1))
	elif c <= 4.6e+24:
		tmp = b * (t * (z * -a))
	elif c <= 1.75e+140:
		tmp = b * (k * (y * -y4))
	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(y0 * Float64(c * y2)))
	tmp = 0.0
	if (c <= -1e+126)
		tmp = t_1;
	elseif (c <= -1.42e-6)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (c <= 3.8e-235)
		tmp = Float64(x * Float64(b * Float64(j * Float64(-y0))));
	elseif (c <= 2.4e-179)
		tmp = Float64(a * Float64(Float64(z * t) * Float64(-b)));
	elseif (c <= 5e-19)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	elseif (c <= 4.6e+24)
		tmp = Float64(b * Float64(t * Float64(z * Float64(-a))));
	elseif (c <= 1.75e+140)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	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 * (y0 * (c * y2));
	tmp = 0.0;
	if (c <= -1e+126)
		tmp = t_1;
	elseif (c <= -1.42e-6)
		tmp = (x * y) * (a * b);
	elseif (c <= 3.8e-235)
		tmp = x * (b * (j * -y0));
	elseif (c <= 2.4e-179)
		tmp = a * ((z * t) * -b);
	elseif (c <= 5e-19)
		tmp = i * (j * (x * y1));
	elseif (c <= 4.6e+24)
		tmp = b * (t * (z * -a));
	elseif (c <= 1.75e+140)
		tmp = b * (k * (y * -y4));
	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[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1e+126], t$95$1, If[LessEqual[c, -1.42e-6], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.8e-235], N[(x * N[(b * N[(j * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.4e-179], N[(a * N[(N[(z * t), $MachinePrecision] * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 5e-19], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 4.6e+24], N[(b * N[(t * N[(z * (-a)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.75e+140], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if c < -9.99999999999999925e125 or 1.74999999999999995e140 < c

   1. Initial program 20.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 49.8%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 49.8%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 49.8%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 49.8%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 46.1%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 46.1%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 46.1%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   if -9.99999999999999925e125 < c < -1.42e-6

   1. Initial program 12.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 48.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 56.6%

      \[\leadsto \color{blue}{b \cdot \left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 52.6%

         \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)} \]

      2. +-commutative 52.6%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)} \]

      3. mul-1-neg 52.6%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right) \]

      4. unsub-neg 52.6%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)} \]

      5. *-commutative 52.6%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x - \color{blue}{y4 \cdot k}\right) \]

   5. Simplified 52.6%

      \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(a \cdot x - y4 \cdot k\right)} \]

   6. Taylor expanded in a around inf 41.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 45.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)} \]

      2. *-commutative 45.1%

         \[\leadsto \color{blue}{\left(x \cdot y\right) \cdot \left(a \cdot b\right)} \]

   8. Simplified 45.1%

      \[\leadsto \color{blue}{\left(x \cdot y\right) \cdot \left(a \cdot b\right)} \]

   if -1.42e-6 < c < 3.80000000000000026e-235

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 43.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 32.0%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 32.0%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 32.0%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 32.0%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around 0 30.3%

      \[\leadsto x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(j \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 30.3%

         \[\leadsto x \cdot \color{blue}{\left(-b \cdot \left(j \cdot y0\right)\right)} \]

      2. *-commutative 30.3%

         \[\leadsto x \cdot \left(-b \cdot \color{blue}{\left(y0 \cdot j\right)}\right) \]

   8. Simplified 30.3%

      \[\leadsto x \cdot \color{blue}{\left(-b \cdot \left(y0 \cdot j\right)\right)} \]

   if 3.80000000000000026e-235 < c < 2.4e-179

   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. Taylor expanded in b around inf 71.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 71.5%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 71.8%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(t \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 71.8%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(t \cdot z\right)\right)} \]

      2. neg-mul-1 71.8%

         \[\leadsto a \cdot \left(\color{blue}{\left(-b\right)} \cdot \left(t \cdot z\right)\right) \]

   6. Simplified 71.8%

      \[\leadsto a \cdot \color{blue}{\left(\left(-b\right) \cdot \left(t \cdot z\right)\right)} \]

   if 2.4e-179 < c < 5.0000000000000004e-19

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 34.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 34.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 34.7%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 34.7%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 34.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 24.8%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if 5.0000000000000004e-19 < c < 4.5999999999999998e24

   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. Taylor expanded in b around inf 63.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 51.3%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 51.3%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 51.3%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 51.3%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 51.3%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 51.3%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 51.3%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 51.2%

      \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z\right)}\right) \]

   if 4.5999999999999998e24 < c < 1.74999999999999995e140

   1. Initial program 23.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 33.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 42.6%

      \[\leadsto \color{blue}{b \cdot \left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 34.0%

         \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)} \]

      2. +-commutative 34.0%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)} \]

      3. mul-1-neg 34.0%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right) \]

      4. unsub-neg 34.0%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)} \]

      5. *-commutative 34.0%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x - \color{blue}{y4 \cdot k}\right) \]

   5. Simplified 34.0%

      \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(a \cdot x - y4 \cdot k\right)} \]

   6. Taylor expanded in a around 0 39.1%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 39.1%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

   8. Simplified 39.1%

      \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 39.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1 \cdot 10^{+126}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq -1.42 \cdot 10^{-6}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;c \leq 3.8 \cdot 10^{-235}:\\ \;\;\;\;x \cdot \left(b \cdot \left(j \cdot \left(-y0\right)\right)\right)\\ \mathbf{elif}\;c \leq 2.4 \cdot 10^{-179}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;c \leq 5 \cdot 10^{-19}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;c \leq 4.6 \cdot 10^{+24}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;c \leq 1.75 \cdot 10^{+140}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \end{array} \]

Alternative 24: 31.3% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{if}\;j \leq -4.8 \cdot 10^{+73}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{-242}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;j \leq 4.1 \cdot 10^{-172}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-45} \lor \neg \left(j \leq 9.5 \cdot 10^{+67}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \end{array} \end{array} \]

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) (* x y0))))))
   (if (<= j -4.8e+73)
     t_1
     (if (<= j 1.7e-242)
       (* c (* y0 (- (* x y2) (* z y3))))
       (if (<= j 4.1e-172)
         (* a (* b (- (* x y) (* z t))))
         (if (or (<= j 1.15e-45) (not (<= j 9.5e+67)))
           t_1
           (* k (* y2 (- (* y1 y4) (* y0 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) - (x * y0)));
	double tmp;
	if (j <= -4.8e+73) {
		tmp = t_1;
	} else if (j <= 1.7e-242) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (j <= 4.1e-172) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((j <= 1.15e-45) || !(j <= 9.5e+67)) {
		tmp = t_1;
	} else {
		tmp = k * (y2 * ((y1 * y4) - (y0 * 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) - (x * y0)))
    if (j <= (-4.8d+73)) then
        tmp = t_1
    else if (j <= 1.7d-242) then
        tmp = c * (y0 * ((x * y2) - (z * y3)))
    else if (j <= 4.1d-172) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if ((j <= 1.15d-45) .or. (.not. (j <= 9.5d+67))) then
        tmp = t_1
    else
        tmp = k * (y2 * ((y1 * y4) - (y0 * 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) - (x * y0)));
	double tmp;
	if (j <= -4.8e+73) {
		tmp = t_1;
	} else if (j <= 1.7e-242) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (j <= 4.1e-172) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if ((j <= 1.15e-45) || !(j <= 9.5e+67)) {
		tmp = t_1;
	} else {
		tmp = k * (y2 * ((y1 * y4) - (y0 * 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) - (x * y0)))
	tmp = 0
	if j <= -4.8e+73:
		tmp = t_1
	elif j <= 1.7e-242:
		tmp = c * (y0 * ((x * y2) - (z * y3)))
	elif j <= 4.1e-172:
		tmp = a * (b * ((x * y) - (z * t)))
	elif (j <= 1.15e-45) or not (j <= 9.5e+67):
		tmp = t_1
	else:
		tmp = k * (y2 * ((y1 * y4) - (y0 * 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(Float64(t * y4) - Float64(x * y0))))
	tmp = 0.0
	if (j <= -4.8e+73)
		tmp = t_1;
	elseif (j <= 1.7e-242)
		tmp = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))));
	elseif (j <= 4.1e-172)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif ((j <= 1.15e-45) || !(j <= 9.5e+67))
		tmp = t_1;
	else
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * 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) - (x * y0)));
	tmp = 0.0;
	if (j <= -4.8e+73)
		tmp = t_1;
	elseif (j <= 1.7e-242)
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	elseif (j <= 4.1e-172)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif ((j <= 1.15e-45) || ~((j <= 9.5e+67)))
		tmp = t_1;
	else
		tmp = k * (y2 * ((y1 * y4) - (y0 * 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[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -4.8e+73], t$95$1, If[LessEqual[j, 1.7e-242], N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.1e-172], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[j, 1.15e-45], N[Not[LessEqual[j, 9.5e+67]], $MachinePrecision]], t$95$1, N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 4 regimes

2. if j < -4.80000000000000004e73 or 4.1e-172 < j < 1.14999999999999996e-45 or 9.5000000000000002e67 < 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. Taylor expanded in b around inf 38.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in j around inf 50.4%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]

   if -4.80000000000000004e73 < j < 1.7e-242

   1. Initial program 35.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y0 around inf 37.0%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in c around inf 32.4%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 1.7e-242 < j < 4.1e-172

   1. Initial program 35.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 40.5%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if 1.14999999999999996e-45 < j < 9.5000000000000002e67

   1. Initial program 20.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 30.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 30.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 30.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 30.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in k around inf 36.9%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   6. Step-by-step derivation

      1. mul-1-neg 36.9%

         \[\leadsto \color{blue}{\left(-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. distribute-rgt-neg-in 36.9%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      3. associate-*r* 36.9%

         \[\leadsto b \cdot \left(-\color{blue}{\left(k \cdot y\right) \cdot y4}\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      4. distribute-rgt-neg-in 36.9%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot \left(-y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      5. *-commutative 36.9%

         \[\leadsto b \cdot \left(\color{blue}{\left(y \cdot k\right)} \cdot \left(-y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Simplified 36.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot k\right) \cdot \left(-y4\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   8. Taylor expanded in y2 around inf 41.4%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 41.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -4.8 \cdot 10^{+73}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{-242}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;j \leq 4.1 \cdot 10^{-172}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 1.15 \cdot 10^{-45} \lor \neg \left(j \leq 9.5 \cdot 10^{+67}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \end{array} \]

Alternative 25: 22.1% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ t_2 := c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{if}\;y1 \leq -1.6 \cdot 10^{+56}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y1 \leq -2.6 \cdot 10^{-60}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq -2.9 \cdot 10^{-242}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 10^{-294}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y1 \leq 1.25 \cdot 10^{-136}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 2.15 \cdot 10^{+95}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* j (* x y1)))) (t_2 (* c (* y4 (* y y3)))))
   (if (<= y1 -1.6e+56)
     t_1
     (if (<= y1 -2.6e-60)
       (* b (* j (* t y4)))
       (if (<= y1 -2.9e-242)
         (* x (* y2 (* c y0)))
         (if (<= y1 1e-294)
           t_2
           (if (<= y1 1.25e-136)
             (* x (* y0 (* c y2)))
             (if (<= y1 2.15e+95) 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 = i * (j * (x * y1));
	double t_2 = c * (y4 * (y * y3));
	double tmp;
	if (y1 <= -1.6e+56) {
		tmp = t_1;
	} else if (y1 <= -2.6e-60) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= -2.9e-242) {
		tmp = x * (y2 * (c * y0));
	} else if (y1 <= 1e-294) {
		tmp = t_2;
	} else if (y1 <= 1.25e-136) {
		tmp = x * (y0 * (c * y2));
	} else if (y1 <= 2.15e+95) {
		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 = i * (j * (x * y1))
    t_2 = c * (y4 * (y * y3))
    if (y1 <= (-1.6d+56)) then
        tmp = t_1
    else if (y1 <= (-2.6d-60)) then
        tmp = b * (j * (t * y4))
    else if (y1 <= (-2.9d-242)) then
        tmp = x * (y2 * (c * y0))
    else if (y1 <= 1d-294) then
        tmp = t_2
    else if (y1 <= 1.25d-136) then
        tmp = x * (y0 * (c * y2))
    else if (y1 <= 2.15d+95) 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 = i * (j * (x * y1));
	double t_2 = c * (y4 * (y * y3));
	double tmp;
	if (y1 <= -1.6e+56) {
		tmp = t_1;
	} else if (y1 <= -2.6e-60) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= -2.9e-242) {
		tmp = x * (y2 * (c * y0));
	} else if (y1 <= 1e-294) {
		tmp = t_2;
	} else if (y1 <= 1.25e-136) {
		tmp = x * (y0 * (c * y2));
	} else if (y1 <= 2.15e+95) {
		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 = i * (j * (x * y1))
	t_2 = c * (y4 * (y * y3))
	tmp = 0
	if y1 <= -1.6e+56:
		tmp = t_1
	elif y1 <= -2.6e-60:
		tmp = b * (j * (t * y4))
	elif y1 <= -2.9e-242:
		tmp = x * (y2 * (c * y0))
	elif y1 <= 1e-294:
		tmp = t_2
	elif y1 <= 1.25e-136:
		tmp = x * (y0 * (c * y2))
	elif y1 <= 2.15e+95:
		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(i * Float64(j * Float64(x * y1)))
	t_2 = Float64(c * Float64(y4 * Float64(y * y3)))
	tmp = 0.0
	if (y1 <= -1.6e+56)
		tmp = t_1;
	elseif (y1 <= -2.6e-60)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (y1 <= -2.9e-242)
		tmp = Float64(x * Float64(y2 * Float64(c * y0)));
	elseif (y1 <= 1e-294)
		tmp = t_2;
	elseif (y1 <= 1.25e-136)
		tmp = Float64(x * Float64(y0 * Float64(c * y2)));
	elseif (y1 <= 2.15e+95)
		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 = i * (j * (x * y1));
	t_2 = c * (y4 * (y * y3));
	tmp = 0.0;
	if (y1 <= -1.6e+56)
		tmp = t_1;
	elseif (y1 <= -2.6e-60)
		tmp = b * (j * (t * y4));
	elseif (y1 <= -2.9e-242)
		tmp = x * (y2 * (c * y0));
	elseif (y1 <= 1e-294)
		tmp = t_2;
	elseif (y1 <= 1.25e-136)
		tmp = x * (y0 * (c * y2));
	elseif (y1 <= 2.15e+95)
		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[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y1, -1.6e+56], t$95$1, If[LessEqual[y1, -2.6e-60], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -2.9e-242], N[(x * N[(y2 * N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1e-294], t$95$2, If[LessEqual[y1, 1.25e-136], N[(x * N[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 2.15e+95], t$95$2, t$95$1]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y1 < -1.60000000000000002e56 or 2.15e95 < y1

   1. Initial program 21.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 36.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if -1.60000000000000002e56 < y1 < -2.5999999999999998e-60

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 38.7%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 38.7%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 38.7%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 38.7%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 38.7%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 38.7%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 38.7%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 42.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -2.5999999999999998e-60 < y1 < -2.9000000000000001e-242

   1. Initial program 44.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 43.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 33.1%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 29.2%

      \[\leadsto x \cdot \color{blue}{\left(c \cdot \left(y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 31.7%

         \[\leadsto x \cdot \color{blue}{\left(\left(c \cdot y0\right) \cdot y2\right)} \]

      2. *-commutative 31.7%

         \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0\right)\right)} \]

   6. Simplified 31.7%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0\right)\right)} \]

   if -2.9000000000000001e-242 < y1 < 1.00000000000000002e-294 or 1.25e-136 < y1 < 2.15e95

   1. Initial program 28.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 37.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 37.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 37.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 40.8%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 37.9%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 37.9%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 37.9%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 29.7%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 32.3%

         \[\leadsto c \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \]

      2. *-commutative 32.3%

         \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   10. Simplified 32.3%

       \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   if 1.00000000000000002e-294 < y1 < 1.25e-136

   1. Initial program 30.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 42.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 47.3%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 47.3%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 47.3%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 47.3%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 47.2%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 47.2%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 47.2%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 36.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -1.6 \cdot 10^{+56}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;y1 \leq -2.6 \cdot 10^{-60}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq -2.9 \cdot 10^{-242}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 10^{-294}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;y1 \leq 1.25 \cdot 10^{-136}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 2.15 \cdot 10^{+95}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \]

Alternative 26: 18.9% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{if}\;y1 \leq -33000000000000:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y1 \leq -2.36 \cdot 10^{-60}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq -2.25 \cdot 10^{-249}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 5.2 \cdot 10^{-293}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y1 \leq 7.2 \cdot 10^{-135}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 1.7 \cdot 10^{+97}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* y4 (* y y3)))))
   (if (<= y1 -33000000000000.0)
     (* (* x y) (* a b))
     (if (<= y1 -2.36e-60)
       (* b (* j (* t y4)))
       (if (<= y1 -2.25e-249)
         (* x (* y2 (* c y0)))
         (if (<= y1 5.2e-293)
           t_1
           (if (<= y1 7.2e-135)
             (* x (* y0 (* c y2)))
             (if (<= y1 1.7e+97) t_1 (* i (* j (* x y1)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y4 * (y * y3));
	double tmp;
	if (y1 <= -33000000000000.0) {
		tmp = (x * y) * (a * b);
	} else if (y1 <= -2.36e-60) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= -2.25e-249) {
		tmp = x * (y2 * (c * y0));
	} else if (y1 <= 5.2e-293) {
		tmp = t_1;
	} else if (y1 <= 7.2e-135) {
		tmp = x * (y0 * (c * y2));
	} else if (y1 <= 1.7e+97) {
		tmp = t_1;
	} else {
		tmp = i * (j * (x * y1));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (y4 * (y * y3))
    if (y1 <= (-33000000000000.0d0)) then
        tmp = (x * y) * (a * b)
    else if (y1 <= (-2.36d-60)) then
        tmp = b * (j * (t * y4))
    else if (y1 <= (-2.25d-249)) then
        tmp = x * (y2 * (c * y0))
    else if (y1 <= 5.2d-293) then
        tmp = t_1
    else if (y1 <= 7.2d-135) then
        tmp = x * (y0 * (c * y2))
    else if (y1 <= 1.7d+97) then
        tmp = t_1
    else
        tmp = i * (j * (x * y1))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y4 * (y * y3));
	double tmp;
	if (y1 <= -33000000000000.0) {
		tmp = (x * y) * (a * b);
	} else if (y1 <= -2.36e-60) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= -2.25e-249) {
		tmp = x * (y2 * (c * y0));
	} else if (y1 <= 5.2e-293) {
		tmp = t_1;
	} else if (y1 <= 7.2e-135) {
		tmp = x * (y0 * (c * y2));
	} else if (y1 <= 1.7e+97) {
		tmp = t_1;
	} else {
		tmp = i * (j * (x * y1));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (y4 * (y * y3))
	tmp = 0
	if y1 <= -33000000000000.0:
		tmp = (x * y) * (a * b)
	elif y1 <= -2.36e-60:
		tmp = b * (j * (t * y4))
	elif y1 <= -2.25e-249:
		tmp = x * (y2 * (c * y0))
	elif y1 <= 5.2e-293:
		tmp = t_1
	elif y1 <= 7.2e-135:
		tmp = x * (y0 * (c * y2))
	elif y1 <= 1.7e+97:
		tmp = t_1
	else:
		tmp = i * (j * (x * y1))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(y4 * Float64(y * y3)))
	tmp = 0.0
	if (y1 <= -33000000000000.0)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (y1 <= -2.36e-60)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (y1 <= -2.25e-249)
		tmp = Float64(x * Float64(y2 * Float64(c * y0)));
	elseif (y1 <= 5.2e-293)
		tmp = t_1;
	elseif (y1 <= 7.2e-135)
		tmp = Float64(x * Float64(y0 * Float64(c * y2)));
	elseif (y1 <= 1.7e+97)
		tmp = t_1;
	else
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (y4 * (y * y3));
	tmp = 0.0;
	if (y1 <= -33000000000000.0)
		tmp = (x * y) * (a * b);
	elseif (y1 <= -2.36e-60)
		tmp = b * (j * (t * y4));
	elseif (y1 <= -2.25e-249)
		tmp = x * (y2 * (c * y0));
	elseif (y1 <= 5.2e-293)
		tmp = t_1;
	elseif (y1 <= 7.2e-135)
		tmp = x * (y0 * (c * y2));
	elseif (y1 <= 1.7e+97)
		tmp = t_1;
	else
		tmp = i * (j * (x * y1));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y1, -33000000000000.0], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -2.36e-60], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -2.25e-249], N[(x * N[(y2 * N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 5.2e-293], t$95$1, If[LessEqual[y1, 7.2e-135], N[(x * N[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.7e+97], t$95$1, N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y1 < -3.3e13

   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. Taylor expanded in b around inf 25.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 36.6%

      \[\leadsto \color{blue}{b \cdot \left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 34.6%

         \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)} \]

      2. +-commutative 34.6%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)} \]

      3. mul-1-neg 34.6%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right) \]

      4. unsub-neg 34.6%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)} \]

      5. *-commutative 34.6%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x - \color{blue}{y4 \cdot k}\right) \]

   5. Simplified 34.6%

      \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(a \cdot x - y4 \cdot k\right)} \]

   6. Taylor expanded in a around inf 30.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 34.3%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)} \]

      2. *-commutative 34.3%

         \[\leadsto \color{blue}{\left(x \cdot y\right) \cdot \left(a \cdot b\right)} \]

   8. Simplified 34.3%

      \[\leadsto \color{blue}{\left(x \cdot y\right) \cdot \left(a \cdot b\right)} \]

   if -3.3e13 < y1 < -2.35999999999999989e-60

   1. Initial program 31.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 33.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 42.5%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 42.5%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 42.5%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 42.5%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 42.5%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 42.5%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 42.5%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 46.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -2.35999999999999989e-60 < y1 < -2.2499999999999999e-249

   1. Initial program 44.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 43.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 33.1%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 29.2%

      \[\leadsto x \cdot \color{blue}{\left(c \cdot \left(y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 31.7%

         \[\leadsto x \cdot \color{blue}{\left(\left(c \cdot y0\right) \cdot y2\right)} \]

      2. *-commutative 31.7%

         \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0\right)\right)} \]

   6. Simplified 31.7%

      \[\leadsto x \cdot \color{blue}{\left(y2 \cdot \left(c \cdot y0\right)\right)} \]

   if -2.2499999999999999e-249 < y1 < 5.1999999999999996e-293 or 7.19999999999999955e-135 < y1 < 1.70000000000000005e97

   1. Initial program 28.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 37.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 37.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 37.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 40.8%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 37.9%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 37.9%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 37.9%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 29.7%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 32.3%

         \[\leadsto c \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \]

      2. *-commutative 32.3%

         \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   10. Simplified 32.3%

       \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   if 5.1999999999999996e-293 < y1 < 7.19999999999999955e-135

   1. Initial program 30.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 42.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 47.3%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 47.3%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 47.3%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 47.3%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 47.2%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 47.2%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 47.2%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   if 1.70000000000000005e97 < y1

   1. Initial program 12.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 45.5%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 45.5%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 45.5%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 45.5%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 40.1%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 36.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -33000000000000:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;y1 \leq -2.36 \cdot 10^{-60}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq -2.25 \cdot 10^{-249}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq 5.2 \cdot 10^{-293}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;y1 \leq 7.2 \cdot 10^{-135}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 1.7 \cdot 10^{+97}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \]

Alternative 27: 21.7% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ t_2 := a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ t_3 := c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{if}\;y4 \leq -6 \cdot 10^{+113}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq -1.42 \cdot 10^{-18}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y4 \leq -1.95 \cdot 10^{-196}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq 2.5 \cdot 10^{-300}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y4 \leq 1.6 \cdot 10^{+113}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4))))
        (t_2 (* a (* (* x y) b)))
        (t_3 (* c (* x (* y0 y2)))))
   (if (<= y4 -6e+113)
     t_1
     (if (<= y4 -1.42e-18)
       t_3
       (if (<= y4 -1.95e-196)
         t_2
         (if (<= y4 2.5e-300) t_3 (if (<= y4 1.6e+113) 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 * (j * (t * y4));
	double t_2 = a * ((x * y) * b);
	double t_3 = c * (x * (y0 * y2));
	double tmp;
	if (y4 <= -6e+113) {
		tmp = t_1;
	} else if (y4 <= -1.42e-18) {
		tmp = t_3;
	} else if (y4 <= -1.95e-196) {
		tmp = t_2;
	} else if (y4 <= 2.5e-300) {
		tmp = t_3;
	} else if (y4 <= 1.6e+113) {
		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) :: t_3
    real(8) :: tmp
    t_1 = b * (j * (t * y4))
    t_2 = a * ((x * y) * b)
    t_3 = c * (x * (y0 * y2))
    if (y4 <= (-6d+113)) then
        tmp = t_1
    else if (y4 <= (-1.42d-18)) then
        tmp = t_3
    else if (y4 <= (-1.95d-196)) then
        tmp = t_2
    else if (y4 <= 2.5d-300) then
        tmp = t_3
    else if (y4 <= 1.6d+113) 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 * (j * (t * y4));
	double t_2 = a * ((x * y) * b);
	double t_3 = c * (x * (y0 * y2));
	double tmp;
	if (y4 <= -6e+113) {
		tmp = t_1;
	} else if (y4 <= -1.42e-18) {
		tmp = t_3;
	} else if (y4 <= -1.95e-196) {
		tmp = t_2;
	} else if (y4 <= 2.5e-300) {
		tmp = t_3;
	} else if (y4 <= 1.6e+113) {
		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 * (j * (t * y4))
	t_2 = a * ((x * y) * b)
	t_3 = c * (x * (y0 * y2))
	tmp = 0
	if y4 <= -6e+113:
		tmp = t_1
	elif y4 <= -1.42e-18:
		tmp = t_3
	elif y4 <= -1.95e-196:
		tmp = t_2
	elif y4 <= 2.5e-300:
		tmp = t_3
	elif y4 <= 1.6e+113:
		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(j * Float64(t * y4)))
	t_2 = Float64(a * Float64(Float64(x * y) * b))
	t_3 = Float64(c * Float64(x * Float64(y0 * y2)))
	tmp = 0.0
	if (y4 <= -6e+113)
		tmp = t_1;
	elseif (y4 <= -1.42e-18)
		tmp = t_3;
	elseif (y4 <= -1.95e-196)
		tmp = t_2;
	elseif (y4 <= 2.5e-300)
		tmp = t_3;
	elseif (y4 <= 1.6e+113)
		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 * (j * (t * y4));
	t_2 = a * ((x * y) * b);
	t_3 = c * (x * (y0 * y2));
	tmp = 0.0;
	if (y4 <= -6e+113)
		tmp = t_1;
	elseif (y4 <= -1.42e-18)
		tmp = t_3;
	elseif (y4 <= -1.95e-196)
		tmp = t_2;
	elseif (y4 <= 2.5e-300)
		tmp = t_3;
	elseif (y4 <= 1.6e+113)
		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[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -6e+113], t$95$1, If[LessEqual[y4, -1.42e-18], t$95$3, If[LessEqual[y4, -1.95e-196], t$95$2, If[LessEqual[y4, 2.5e-300], t$95$3, If[LessEqual[y4, 1.6e+113], t$95$2, t$95$1]]]]]]]]

Derivation

1. Split input into 3 regimes

2. if y4 < -6e113 or 1.5999999999999999e113 < y4

   1. Initial program 21.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 33.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 42.2%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 42.2%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 42.2%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 42.2%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 42.2%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 42.2%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 42.2%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 39.4%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -6e113 < y4 < -1.41999999999999996e-18 or -1.95000000000000008e-196 < y4 < 2.49999999999999998e-300

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 47.9%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.5%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 32.4%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 32.4%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   6. Simplified 32.4%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if -1.41999999999999996e-18 < y4 < -1.95000000000000008e-196 or 2.49999999999999998e-300 < y4 < 1.5999999999999999e113

   1. Initial program 36.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.2%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in b around inf 30.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 33.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -6 \cdot 10^{+113}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -1.42 \cdot 10^{-18}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -1.95 \cdot 10^{-196}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;y4 \leq 2.5 \cdot 10^{-300}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 1.6 \cdot 10^{+113}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 28: 21.8% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ t_2 := c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{if}\;y4 \leq -1.35 \cdot 10^{+80}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -2.6 \cdot 10^{-17}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq -6.4 \cdot 10^{-199}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 1.5 \cdot 10^{-301}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y4 \leq 1.85 \cdot 10^{+113}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* (* x y) b))) (t_2 (* c (* x (* y0 y2)))))
   (if (<= y4 -1.35e+80)
     (* c (* y (* y3 y4)))
     (if (<= y4 -2.6e-17)
       t_2
       (if (<= y4 -6.4e-199)
         t_1
         (if (<= y4 1.5e-301)
           t_2
           (if (<= y4 1.85e+113) t_1 (* b (* j (* t y4))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * ((x * y) * b);
	double t_2 = c * (x * (y0 * y2));
	double tmp;
	if (y4 <= -1.35e+80) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -2.6e-17) {
		tmp = t_2;
	} else if (y4 <= -6.4e-199) {
		tmp = t_1;
	} else if (y4 <= 1.5e-301) {
		tmp = t_2;
	} else if (y4 <= 1.85e+113) {
		tmp = t_1;
	} else {
		tmp = b * (j * (t * y4));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = a * ((x * y) * b)
    t_2 = c * (x * (y0 * y2))
    if (y4 <= (-1.35d+80)) then
        tmp = c * (y * (y3 * y4))
    else if (y4 <= (-2.6d-17)) then
        tmp = t_2
    else if (y4 <= (-6.4d-199)) then
        tmp = t_1
    else if (y4 <= 1.5d-301) then
        tmp = t_2
    else if (y4 <= 1.85d+113) then
        tmp = t_1
    else
        tmp = b * (j * (t * y4))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * ((x * y) * b);
	double t_2 = c * (x * (y0 * y2));
	double tmp;
	if (y4 <= -1.35e+80) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -2.6e-17) {
		tmp = t_2;
	} else if (y4 <= -6.4e-199) {
		tmp = t_1;
	} else if (y4 <= 1.5e-301) {
		tmp = t_2;
	} else if (y4 <= 1.85e+113) {
		tmp = t_1;
	} else {
		tmp = b * (j * (t * y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * ((x * y) * b)
	t_2 = c * (x * (y0 * y2))
	tmp = 0
	if y4 <= -1.35e+80:
		tmp = c * (y * (y3 * y4))
	elif y4 <= -2.6e-17:
		tmp = t_2
	elif y4 <= -6.4e-199:
		tmp = t_1
	elif y4 <= 1.5e-301:
		tmp = t_2
	elif y4 <= 1.85e+113:
		tmp = t_1
	else:
		tmp = b * (j * (t * y4))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(Float64(x * y) * b))
	t_2 = Float64(c * Float64(x * Float64(y0 * y2)))
	tmp = 0.0
	if (y4 <= -1.35e+80)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	elseif (y4 <= -2.6e-17)
		tmp = t_2;
	elseif (y4 <= -6.4e-199)
		tmp = t_1;
	elseif (y4 <= 1.5e-301)
		tmp = t_2;
	elseif (y4 <= 1.85e+113)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * ((x * y) * b);
	t_2 = c * (x * (y0 * y2));
	tmp = 0.0;
	if (y4 <= -1.35e+80)
		tmp = c * (y * (y3 * y4));
	elseif (y4 <= -2.6e-17)
		tmp = t_2;
	elseif (y4 <= -6.4e-199)
		tmp = t_1;
	elseif (y4 <= 1.5e-301)
		tmp = t_2;
	elseif (y4 <= 1.85e+113)
		tmp = t_1;
	else
		tmp = b * (j * (t * y4));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.35e+80], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -2.6e-17], t$95$2, If[LessEqual[y4, -6.4e-199], t$95$1, If[LessEqual[y4, 1.5e-301], t$95$2, If[LessEqual[y4, 1.85e+113], t$95$1, N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if y4 < -1.34999999999999991e80

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 34.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 34.7%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 34.7%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 34.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 50.9%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 38.3%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 38.3%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 38.3%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 40.6%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. *-commutative 40.6%

         \[\leadsto c \cdot \left(y \cdot \color{blue}{\left(y4 \cdot y3\right)}\right) \]

   10. Simplified 40.6%

       \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y4 \cdot y3\right)\right)} \]

   if -1.34999999999999991e80 < y4 < -2.60000000000000003e-17 or -6.3999999999999999e-199 < y4 < 1.5e-301

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 54.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 46.3%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 35.7%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 35.7%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   6. Simplified 35.7%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if -2.60000000000000003e-17 < y4 < -6.3999999999999999e-199 or 1.5e-301 < y4 < 1.8499999999999999e113

   1. Initial program 36.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.3%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in b around inf 29.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if 1.8499999999999999e113 < y4

   1. Initial program 14.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 34.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 43.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 43.8%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 43.8%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 43.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 43.8%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 43.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 41.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 34.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.35 \cdot 10^{+80}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -2.6 \cdot 10^{-17}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -6.4 \cdot 10^{-199}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;y4 \leq 1.5 \cdot 10^{-301}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 1.85 \cdot 10^{+113}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 29: 21.8% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{if}\;y4 \leq -1.48 \cdot 10^{+81}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -6.6 \cdot 10^{-18}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -9 \cdot 10^{-197}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 4.5 \cdot 10^{-301}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.45 \cdot 10^{+113}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* (* x y) b))))
   (if (<= y4 -1.48e+81)
     (* c (* y (* y3 y4)))
     (if (<= y4 -6.6e-18)
       (* c (* x (* y0 y2)))
       (if (<= y4 -9e-197)
         t_1
         (if (<= y4 4.5e-301)
           (* c (* y2 (* x y0)))
           (if (<= y4 1.45e+113) t_1 (* b (* j (* t y4))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * ((x * y) * b);
	double tmp;
	if (y4 <= -1.48e+81) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -6.6e-18) {
		tmp = c * (x * (y0 * y2));
	} else if (y4 <= -9e-197) {
		tmp = t_1;
	} else if (y4 <= 4.5e-301) {
		tmp = c * (y2 * (x * y0));
	} else if (y4 <= 1.45e+113) {
		tmp = t_1;
	} else {
		tmp = b * (j * (t * y4));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * ((x * y) * b)
    if (y4 <= (-1.48d+81)) then
        tmp = c * (y * (y3 * y4))
    else if (y4 <= (-6.6d-18)) then
        tmp = c * (x * (y0 * y2))
    else if (y4 <= (-9d-197)) then
        tmp = t_1
    else if (y4 <= 4.5d-301) then
        tmp = c * (y2 * (x * y0))
    else if (y4 <= 1.45d+113) then
        tmp = t_1
    else
        tmp = b * (j * (t * y4))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * ((x * y) * b);
	double tmp;
	if (y4 <= -1.48e+81) {
		tmp = c * (y * (y3 * y4));
	} else if (y4 <= -6.6e-18) {
		tmp = c * (x * (y0 * y2));
	} else if (y4 <= -9e-197) {
		tmp = t_1;
	} else if (y4 <= 4.5e-301) {
		tmp = c * (y2 * (x * y0));
	} else if (y4 <= 1.45e+113) {
		tmp = t_1;
	} else {
		tmp = b * (j * (t * y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * ((x * y) * b)
	tmp = 0
	if y4 <= -1.48e+81:
		tmp = c * (y * (y3 * y4))
	elif y4 <= -6.6e-18:
		tmp = c * (x * (y0 * y2))
	elif y4 <= -9e-197:
		tmp = t_1
	elif y4 <= 4.5e-301:
		tmp = c * (y2 * (x * y0))
	elif y4 <= 1.45e+113:
		tmp = t_1
	else:
		tmp = b * (j * (t * y4))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(Float64(x * y) * b))
	tmp = 0.0
	if (y4 <= -1.48e+81)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	elseif (y4 <= -6.6e-18)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y4 <= -9e-197)
		tmp = t_1;
	elseif (y4 <= 4.5e-301)
		tmp = Float64(c * Float64(y2 * Float64(x * y0)));
	elseif (y4 <= 1.45e+113)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * ((x * y) * b);
	tmp = 0.0;
	if (y4 <= -1.48e+81)
		tmp = c * (y * (y3 * y4));
	elseif (y4 <= -6.6e-18)
		tmp = c * (x * (y0 * y2));
	elseif (y4 <= -9e-197)
		tmp = t_1;
	elseif (y4 <= 4.5e-301)
		tmp = c * (y2 * (x * y0));
	elseif (y4 <= 1.45e+113)
		tmp = t_1;
	else
		tmp = b * (j * (t * y4));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.48e+81], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -6.6e-18], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -9e-197], t$95$1, If[LessEqual[y4, 4.5e-301], N[(c * N[(y2 * N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.45e+113], t$95$1, N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y4 < -1.47999999999999998e81

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 34.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 34.7%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 34.7%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 34.7%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 50.9%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 38.3%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 38.3%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 38.3%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 40.6%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. *-commutative 40.6%

         \[\leadsto c \cdot \left(y \cdot \color{blue}{\left(y4 \cdot y3\right)}\right) \]

   10. Simplified 40.6%

       \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y4 \cdot y3\right)\right)} \]

   if -1.47999999999999998e81 < y4 < -6.6000000000000003e-18

   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. Taylor expanded in x around inf 69.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 75.5%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 63.8%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 63.8%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   6. Simplified 63.8%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if -6.6000000000000003e-18 < y4 < -9.0000000000000002e-197 or 4.5000000000000002e-301 < y4 < 1.44999999999999992e113

   1. Initial program 36.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.3%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in b around inf 29.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if -9.0000000000000002e-197 < y4 < 4.5000000000000002e-301

   1. Initial program 23.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 47.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 45.1%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 45.1%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 45.1%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 45.1%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in c around inf 22.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 22.6%

         \[\leadsto c \cdot \color{blue}{\left(\left(x \cdot y0\right) \cdot y2\right)} \]

   8. Simplified 22.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(x \cdot y0\right) \cdot y2\right)} \]

   if 1.44999999999999992e113 < y4

   1. Initial program 14.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 34.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 43.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 43.8%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 43.8%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 43.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 43.8%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 43.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 41.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 34.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.48 \cdot 10^{+81}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -6.6 \cdot 10^{-18}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq -9 \cdot 10^{-197}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;y4 \leq 4.5 \cdot 10^{-301}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.45 \cdot 10^{+113}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 30: 22.0% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ t_2 := c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{if}\;y1 \leq -9.6 \cdot 10^{+51}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y1 \leq -1.3 \cdot 10^{-254}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq 7 \cdot 10^{-235}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y1 \leq 3 \cdot 10^{-136}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 3.3 \cdot 10^{+95}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* j (* x y1)))) (t_2 (* c (* y4 (* y y3)))))
   (if (<= y1 -9.6e+51)
     t_1
     (if (<= y1 -1.3e-254)
       (* b (* j (* t y4)))
       (if (<= y1 7e-235)
         t_2
         (if (<= y1 3e-136)
           (* c (* x (* y0 y2)))
           (if (<= y1 3.3e+95) 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 = i * (j * (x * y1));
	double t_2 = c * (y4 * (y * y3));
	double tmp;
	if (y1 <= -9.6e+51) {
		tmp = t_1;
	} else if (y1 <= -1.3e-254) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= 7e-235) {
		tmp = t_2;
	} else if (y1 <= 3e-136) {
		tmp = c * (x * (y0 * y2));
	} else if (y1 <= 3.3e+95) {
		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 = i * (j * (x * y1))
    t_2 = c * (y4 * (y * y3))
    if (y1 <= (-9.6d+51)) then
        tmp = t_1
    else if (y1 <= (-1.3d-254)) then
        tmp = b * (j * (t * y4))
    else if (y1 <= 7d-235) then
        tmp = t_2
    else if (y1 <= 3d-136) then
        tmp = c * (x * (y0 * y2))
    else if (y1 <= 3.3d+95) 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 = i * (j * (x * y1));
	double t_2 = c * (y4 * (y * y3));
	double tmp;
	if (y1 <= -9.6e+51) {
		tmp = t_1;
	} else if (y1 <= -1.3e-254) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= 7e-235) {
		tmp = t_2;
	} else if (y1 <= 3e-136) {
		tmp = c * (x * (y0 * y2));
	} else if (y1 <= 3.3e+95) {
		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 = i * (j * (x * y1))
	t_2 = c * (y4 * (y * y3))
	tmp = 0
	if y1 <= -9.6e+51:
		tmp = t_1
	elif y1 <= -1.3e-254:
		tmp = b * (j * (t * y4))
	elif y1 <= 7e-235:
		tmp = t_2
	elif y1 <= 3e-136:
		tmp = c * (x * (y0 * y2))
	elif y1 <= 3.3e+95:
		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(i * Float64(j * Float64(x * y1)))
	t_2 = Float64(c * Float64(y4 * Float64(y * y3)))
	tmp = 0.0
	if (y1 <= -9.6e+51)
		tmp = t_1;
	elseif (y1 <= -1.3e-254)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (y1 <= 7e-235)
		tmp = t_2;
	elseif (y1 <= 3e-136)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y1 <= 3.3e+95)
		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 = i * (j * (x * y1));
	t_2 = c * (y4 * (y * y3));
	tmp = 0.0;
	if (y1 <= -9.6e+51)
		tmp = t_1;
	elseif (y1 <= -1.3e-254)
		tmp = b * (j * (t * y4));
	elseif (y1 <= 7e-235)
		tmp = t_2;
	elseif (y1 <= 3e-136)
		tmp = c * (x * (y0 * y2));
	elseif (y1 <= 3.3e+95)
		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[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y1, -9.6e+51], t$95$1, If[LessEqual[y1, -1.3e-254], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 7e-235], t$95$2, If[LessEqual[y1, 3e-136], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 3.3e+95], t$95$2, t$95$1]]]]]]]

Derivation

1. Split input into 4 regimes

2. if y1 < -9.5999999999999994e51 or 3.2999999999999998e95 < y1

   1. Initial program 21.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 36.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if -9.5999999999999994e51 < y1 < -1.3e-254

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 37.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 33.3%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 33.3%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 33.3%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 33.3%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 33.3%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 33.3%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 33.3%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 30.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -1.3e-254 < y1 < 6.9999999999999997e-235 or 2.9999999999999998e-136 < y1 < 3.2999999999999998e95

   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. Taylor expanded in y4 around inf 35.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 35.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 35.5%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 35.5%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 40.8%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 37.1%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 37.1%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 37.1%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 29.8%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 32.2%

         \[\leadsto c \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \]

      2. *-commutative 32.2%

         \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   10. Simplified 32.2%

       \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   if 6.9999999999999997e-235 < y1 < 2.9999999999999998e-136

   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. Taylor expanded in x around inf 44.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 63.0%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 57.2%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 57.2%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   6. Simplified 57.2%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 34.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -9.6 \cdot 10^{+51}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;y1 \leq -1.3 \cdot 10^{-254}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq 7 \cdot 10^{-235}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;y1 \leq 3 \cdot 10^{-136}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 3.3 \cdot 10^{+95}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \]

Alternative 31: 31.0% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{if}\;j \leq -2.16 \cdot 10^{+74}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 2.5 \cdot 10^{-251}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;j \leq 2.8 \cdot 10^{-172}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (- (* t y4) (* x y0))))))
   (if (<= j -2.16e+74)
     t_1
     (if (<= j 2.5e-251)
       (* c (* y0 (- (* x y2) (* z y3))))
       (if (<= j 2.8e-172) (* 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 * (j * ((t * y4) - (x * y0)));
	double tmp;
	if (j <= -2.16e+74) {
		tmp = t_1;
	} else if (j <= 2.5e-251) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (j <= 2.8e-172) {
		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 * (j * ((t * y4) - (x * y0)))
    if (j <= (-2.16d+74)) then
        tmp = t_1
    else if (j <= 2.5d-251) then
        tmp = c * (y0 * ((x * y2) - (z * y3)))
    else if (j <= 2.8d-172) 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 * (j * ((t * y4) - (x * y0)));
	double tmp;
	if (j <= -2.16e+74) {
		tmp = t_1;
	} else if (j <= 2.5e-251) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (j <= 2.8e-172) {
		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 * (j * ((t * y4) - (x * y0)))
	tmp = 0
	if j <= -2.16e+74:
		tmp = t_1
	elif j <= 2.5e-251:
		tmp = c * (y0 * ((x * y2) - (z * y3)))
	elif j <= 2.8e-172:
		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(j * Float64(Float64(t * y4) - Float64(x * y0))))
	tmp = 0.0
	if (j <= -2.16e+74)
		tmp = t_1;
	elseif (j <= 2.5e-251)
		tmp = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))));
	elseif (j <= 2.8e-172)
		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 * (j * ((t * y4) - (x * y0)));
	tmp = 0.0;
	if (j <= -2.16e+74)
		tmp = t_1;
	elseif (j <= 2.5e-251)
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	elseif (j <= 2.8e-172)
		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[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.16e+74], t$95$1, If[LessEqual[j, 2.5e-251], N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.8e-172], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if j < -2.1599999999999999e74 or 2.80000000000000011e-172 < j

   1. Initial program 23.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 37.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in j around inf 46.1%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]

   if -2.1599999999999999e74 < j < 2.5000000000000001e-251

   1. Initial program 35.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y0 around inf 37.0%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in c around inf 32.4%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 2.5000000000000001e-251 < j < 2.80000000000000011e-172

   1. Initial program 35.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 40.5%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 40.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -2.16 \cdot 10^{+74}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 2.5 \cdot 10^{-251}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;j \leq 2.8 \cdot 10^{-172}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \end{array} \]

Alternative 32: 21.8% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{if}\;y1 \leq -6 \cdot 10^{+55}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y1 \leq -2.6 \cdot 10^{-60}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq 1.7 \cdot 10^{-136}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 6 \cdot 10^{+96}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* j (* x y1)))))
   (if (<= y1 -6e+55)
     t_1
     (if (<= y1 -2.6e-60)
       (* b (* j (* t y4)))
       (if (<= y1 1.7e-136)
         (* x (* y0 (* c y2)))
         (if (<= y1 6e+96) (* c (* y4 (* y y3))) 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 = i * (j * (x * y1));
	double tmp;
	if (y1 <= -6e+55) {
		tmp = t_1;
	} else if (y1 <= -2.6e-60) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= 1.7e-136) {
		tmp = x * (y0 * (c * y2));
	} else if (y1 <= 6e+96) {
		tmp = c * (y4 * (y * y3));
	} 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 = i * (j * (x * y1))
    if (y1 <= (-6d+55)) then
        tmp = t_1
    else if (y1 <= (-2.6d-60)) then
        tmp = b * (j * (t * y4))
    else if (y1 <= 1.7d-136) then
        tmp = x * (y0 * (c * y2))
    else if (y1 <= 6d+96) then
        tmp = c * (y4 * (y * y3))
    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 = i * (j * (x * y1));
	double tmp;
	if (y1 <= -6e+55) {
		tmp = t_1;
	} else if (y1 <= -2.6e-60) {
		tmp = b * (j * (t * y4));
	} else if (y1 <= 1.7e-136) {
		tmp = x * (y0 * (c * y2));
	} else if (y1 <= 6e+96) {
		tmp = c * (y4 * (y * y3));
	} 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 = i * (j * (x * y1))
	tmp = 0
	if y1 <= -6e+55:
		tmp = t_1
	elif y1 <= -2.6e-60:
		tmp = b * (j * (t * y4))
	elif y1 <= 1.7e-136:
		tmp = x * (y0 * (c * y2))
	elif y1 <= 6e+96:
		tmp = c * (y4 * (y * y3))
	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(i * Float64(j * Float64(x * y1)))
	tmp = 0.0
	if (y1 <= -6e+55)
		tmp = t_1;
	elseif (y1 <= -2.6e-60)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (y1 <= 1.7e-136)
		tmp = Float64(x * Float64(y0 * Float64(c * y2)));
	elseif (y1 <= 6e+96)
		tmp = Float64(c * Float64(y4 * Float64(y * y3)));
	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 = i * (j * (x * y1));
	tmp = 0.0;
	if (y1 <= -6e+55)
		tmp = t_1;
	elseif (y1 <= -2.6e-60)
		tmp = b * (j * (t * y4));
	elseif (y1 <= 1.7e-136)
		tmp = x * (y0 * (c * y2));
	elseif (y1 <= 6e+96)
		tmp = c * (y4 * (y * y3));
	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[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y1, -6e+55], t$95$1, If[LessEqual[y1, -2.6e-60], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.7e-136], N[(x * N[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 6e+96], N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if y1 < -6.00000000000000033e55 or 6.0000000000000001e96 < y1

   1. Initial program 21.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 42.0%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 36.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if -6.00000000000000033e55 < y1 < -2.5999999999999998e-60

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 38.7%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 38.7%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 38.7%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 38.7%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 38.7%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 38.7%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 38.7%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 42.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -2.5999999999999998e-60 < y1 < 1.7e-136

   1. Initial program 36.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 42.8%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 44.4%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 44.4%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 44.4%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 44.4%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 32.0%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 32.0%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 32.0%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   if 1.7e-136 < y1 < 6.0000000000000001e96

   1. Initial program 28.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 35.6%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(j \cdot t - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 35.6%

         \[\leadsto y4 \cdot \left(b \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 35.6%

         \[\leadsto y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - \color{blue}{y3 \cdot y}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 35.6%

      \[\leadsto \color{blue}{y4 \cdot \left(b \cdot \left(t \cdot j - k \cdot y\right) - c \cdot \left(t \cdot y2 - y3 \cdot y\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in y around inf 46.2%

      \[\leadsto \color{blue}{y \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 41.9%

         \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k\right) - -1 \cdot \left(c \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 41.9%

         \[\leadsto \left(y \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   7. Simplified 41.9%

      \[\leadsto \color{blue}{\left(y \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot k - c \cdot y3\right)\right)} \]

   8. Taylor expanded in b around 0 26.2%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   9. Step-by-step derivation

      1. associate-*r* 30.1%

         \[\leadsto c \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \]

      2. *-commutative 30.1%

         \[\leadsto c \cdot \color{blue}{\left(y4 \cdot \left(y \cdot y3\right)\right)} \]

   10. Simplified 30.1%

       \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 34.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -6 \cdot 10^{+55}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;y1 \leq -2.6 \cdot 10^{-60}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq 1.7 \cdot 10^{-136}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;y1 \leq 6 \cdot 10^{+96}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \]

Alternative 33: 19.2% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.7 \cdot 10^{+27}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;z \leq -1.6 \cdot 10^{-129}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-219}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 5.5 \cdot 10^{-73}:\\ \;\;\;\;x \cdot \left(i \cdot \left(j \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.7e+27)
   (* a (* (* z t) (- b)))
   (if (<= z -1.6e-129)
     (* b (* k (* y (- y4))))
     (if (<= z 7e-219)
       (* x (* y0 (* c y2)))
       (if (<= z 5.5e-73) (* x (* i (* j y1))) (* a (* (* x y) b)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.7e+27) {
		tmp = a * ((z * t) * -b);
	} else if (z <= -1.6e-129) {
		tmp = b * (k * (y * -y4));
	} else if (z <= 7e-219) {
		tmp = x * (y0 * (c * y2));
	} else if (z <= 5.5e-73) {
		tmp = x * (i * (j * y1));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.7d+27)) then
        tmp = a * ((z * t) * -b)
    else if (z <= (-1.6d-129)) then
        tmp = b * (k * (y * -y4))
    else if (z <= 7d-219) then
        tmp = x * (y0 * (c * y2))
    else if (z <= 5.5d-73) then
        tmp = x * (i * (j * y1))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.7e+27) {
		tmp = a * ((z * t) * -b);
	} else if (z <= -1.6e-129) {
		tmp = b * (k * (y * -y4));
	} else if (z <= 7e-219) {
		tmp = x * (y0 * (c * y2));
	} else if (z <= 5.5e-73) {
		tmp = x * (i * (j * y1));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.7e+27:
		tmp = a * ((z * t) * -b)
	elif z <= -1.6e-129:
		tmp = b * (k * (y * -y4))
	elif z <= 7e-219:
		tmp = x * (y0 * (c * y2))
	elif z <= 5.5e-73:
		tmp = x * (i * (j * y1))
	else:
		tmp = a * ((x * y) * b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.7e+27)
		tmp = Float64(a * Float64(Float64(z * t) * Float64(-b)));
	elseif (z <= -1.6e-129)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (z <= 7e-219)
		tmp = Float64(x * Float64(y0 * Float64(c * y2)));
	elseif (z <= 5.5e-73)
		tmp = Float64(x * Float64(i * Float64(j * y1)));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.7e+27)
		tmp = a * ((z * t) * -b);
	elseif (z <= -1.6e-129)
		tmp = b * (k * (y * -y4));
	elseif (z <= 7e-219)
		tmp = x * (y0 * (c * y2));
	elseif (z <= 5.5e-73)
		tmp = x * (i * (j * y1));
	else
		tmp = a * ((x * y) * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.7e+27], N[(a * N[(N[(z * t), $MachinePrecision] * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.6e-129], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7e-219], N[(x * N[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.5e-73], N[(x * N[(i * N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -1.7e27

   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. Taylor expanded in b around inf 41.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 37.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 34.0%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(t \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 34.0%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(t \cdot z\right)\right)} \]

      2. neg-mul-1 34.0%

         \[\leadsto a \cdot \left(\color{blue}{\left(-b\right)} \cdot \left(t \cdot z\right)\right) \]

   6. Simplified 34.0%

      \[\leadsto a \cdot \color{blue}{\left(\left(-b\right) \cdot \left(t \cdot z\right)\right)} \]

   if -1.7e27 < z < -1.6000000000000001e-129

   1. Initial program 34.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 38.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 32.8%

      \[\leadsto \color{blue}{b \cdot \left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 32.8%

         \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)} \]

      2. +-commutative 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)} \]

      3. mul-1-neg 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right) \]

      4. unsub-neg 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)} \]

      5. *-commutative 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x - \color{blue}{y4 \cdot k}\right) \]

   5. Simplified 32.8%

      \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(a \cdot x - y4 \cdot k\right)} \]

   6. Taylor expanded in a around 0 32.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.8%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

   8. Simplified 32.8%

      \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

   if -1.6000000000000001e-129 < z < 7.00000000000000022e-219

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 52.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 41.4%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.4%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 41.4%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 41.4%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 31.3%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 31.3%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 31.3%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   if 7.00000000000000022e-219 < z < 5.50000000000000006e-73

   1. Initial program 35.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 59.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 62.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 62.3%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 62.3%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 62.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 39.5%

      \[\leadsto x \cdot \color{blue}{\left(i \cdot \left(j \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 39.5%

         \[\leadsto x \cdot \left(i \cdot \color{blue}{\left(y1 \cdot j\right)}\right) \]

   8. Simplified 39.5%

      \[\leadsto x \cdot \color{blue}{\left(i \cdot \left(y1 \cdot j\right)\right)} \]

   if 5.50000000000000006e-73 < z

   1. Initial program 22.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 41.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.9%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in b around inf 35.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 34.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.7 \cdot 10^{+27}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;z \leq -1.6 \cdot 10^{-129}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-219}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 5.5 \cdot 10^{-73}:\\ \;\;\;\;x \cdot \left(i \cdot \left(j \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 34: 19.1% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.25 \cdot 10^{+22}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;z \leq -3 \cdot 10^{-128}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;z \leq 5.5 \cdot 10^{-220}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 7.4 \cdot 10^{-73}:\\ \;\;\;\;x \cdot \left(i \cdot \left(j \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.25e+22)
   (* b (* t (* z (- a))))
   (if (<= z -3e-128)
     (* b (* k (* y (- y4))))
     (if (<= z 5.5e-220)
       (* x (* y0 (* c y2)))
       (if (<= z 7.4e-73) (* x (* i (* j y1))) (* a (* (* x y) b)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.25e+22) {
		tmp = b * (t * (z * -a));
	} else if (z <= -3e-128) {
		tmp = b * (k * (y * -y4));
	} else if (z <= 5.5e-220) {
		tmp = x * (y0 * (c * y2));
	} else if (z <= 7.4e-73) {
		tmp = x * (i * (j * y1));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.25d+22)) then
        tmp = b * (t * (z * -a))
    else if (z <= (-3d-128)) then
        tmp = b * (k * (y * -y4))
    else if (z <= 5.5d-220) then
        tmp = x * (y0 * (c * y2))
    else if (z <= 7.4d-73) then
        tmp = x * (i * (j * y1))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.25e+22) {
		tmp = b * (t * (z * -a));
	} else if (z <= -3e-128) {
		tmp = b * (k * (y * -y4));
	} else if (z <= 5.5e-220) {
		tmp = x * (y0 * (c * y2));
	} else if (z <= 7.4e-73) {
		tmp = x * (i * (j * y1));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.25e+22:
		tmp = b * (t * (z * -a))
	elif z <= -3e-128:
		tmp = b * (k * (y * -y4))
	elif z <= 5.5e-220:
		tmp = x * (y0 * (c * y2))
	elif z <= 7.4e-73:
		tmp = x * (i * (j * y1))
	else:
		tmp = a * ((x * y) * b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.25e+22)
		tmp = Float64(b * Float64(t * Float64(z * Float64(-a))));
	elseif (z <= -3e-128)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (z <= 5.5e-220)
		tmp = Float64(x * Float64(y0 * Float64(c * y2)));
	elseif (z <= 7.4e-73)
		tmp = Float64(x * Float64(i * Float64(j * y1)));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.25e+22)
		tmp = b * (t * (z * -a));
	elseif (z <= -3e-128)
		tmp = b * (k * (y * -y4));
	elseif (z <= 5.5e-220)
		tmp = x * (y0 * (c * y2));
	elseif (z <= 7.4e-73)
		tmp = x * (i * (j * y1));
	else
		tmp = a * ((x * y) * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.25e+22], N[(b * N[(t * N[(z * (-a)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -3e-128], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.5e-220], N[(x * N[(y0 * N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7.4e-73], N[(x * N[(i * N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -1.2499999999999999e22

   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. Taylor expanded in b around inf 41.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 48.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 48.8%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 48.8%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 48.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 48.8%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 48.8%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 48.8%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 37.2%

      \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z\right)}\right) \]

   if -1.2499999999999999e22 < z < -2.99999999999999978e-128

   1. Initial program 34.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 38.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y around inf 32.8%

      \[\leadsto \color{blue}{b \cdot \left(y \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 32.8%

         \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(-1 \cdot \left(k \cdot y4\right) + a \cdot x\right)} \]

      2. +-commutative 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x + -1 \cdot \left(k \cdot y4\right)\right)} \]

      3. mul-1-neg 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x + \color{blue}{\left(-k \cdot y4\right)}\right) \]

      4. unsub-neg 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \color{blue}{\left(a \cdot x - k \cdot y4\right)} \]

      5. *-commutative 32.8%

         \[\leadsto \left(b \cdot y\right) \cdot \left(a \cdot x - \color{blue}{y4 \cdot k}\right) \]

   5. Simplified 32.8%

      \[\leadsto \color{blue}{\left(b \cdot y\right) \cdot \left(a \cdot x - y4 \cdot k\right)} \]

   6. Taylor expanded in a around 0 32.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 32.8%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

   8. Simplified 32.8%

      \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

   if -2.99999999999999978e-128 < z < 5.4999999999999999e-220

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 52.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y0 around inf 41.4%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(c \cdot y2 - b \cdot j\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.4%

         \[\leadsto x \cdot \left(y0 \cdot \left(\color{blue}{y2 \cdot c} - b \cdot j\right)\right) \]

      2. *-commutative 41.4%

         \[\leadsto x \cdot \left(y0 \cdot \left(y2 \cdot c - \color{blue}{j \cdot b}\right)\right) \]

   5. Simplified 41.4%

      \[\leadsto x \cdot \color{blue}{\left(y0 \cdot \left(y2 \cdot c - j \cdot b\right)\right)} \]

   6. Taylor expanded in y2 around inf 31.3%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(c \cdot y2\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 31.3%

         \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   8. Simplified 31.3%

      \[\leadsto x \cdot \left(y0 \cdot \color{blue}{\left(y2 \cdot c\right)}\right) \]

   if 5.4999999999999999e-220 < z < 7.4000000000000002e-73

   1. Initial program 35.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 59.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y around 0 62.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 62.3%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(\color{blue}{y0 \cdot b} - i \cdot y1\right)\right) \]

      2. *-commutative 62.3%

         \[\leadsto x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - \color{blue}{y1 \cdot i}\right)\right) \]

   5. Simplified 62.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot b - y1 \cdot i\right)\right)} \]

   6. Taylor expanded in i around inf 39.5%

      \[\leadsto x \cdot \color{blue}{\left(i \cdot \left(j \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 39.5%

         \[\leadsto x \cdot \left(i \cdot \color{blue}{\left(y1 \cdot j\right)}\right) \]

   8. Simplified 39.5%

      \[\leadsto x \cdot \color{blue}{\left(i \cdot \left(y1 \cdot j\right)\right)} \]

   if 7.4000000000000002e-73 < z

   1. Initial program 22.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 41.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.9%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in b around inf 35.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 35.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.25 \cdot 10^{+22}:\\ \;\;\;\;b \cdot \left(t \cdot \left(z \cdot \left(-a\right)\right)\right)\\ \mathbf{elif}\;z \leq -3 \cdot 10^{-128}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;z \leq 5.5 \cdot 10^{-220}:\\ \;\;\;\;x \cdot \left(y0 \cdot \left(c \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 7.4 \cdot 10^{-73}:\\ \;\;\;\;x \cdot \left(i \cdot \left(j \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 35: 31.1% accurate, 6.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -9.2 \cdot 10^{+69} \lor \neg \left(j \leq 3 \cdot 10^{-172}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= j -9.2e+69) (not (<= j 3e-172)))
   (* b (* j (- (* t y4) (* x y0))))
   (* a (* b (- (* x y) (* z t))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((j <= -9.2e+69) || !(j <= 3e-172)) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else {
		tmp = a * (b * ((x * y) - (z * t)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if ((j <= (-9.2d+69)) .or. (.not. (j <= 3d-172))) then
        tmp = b * (j * ((t * y4) - (x * y0)))
    else
        tmp = a * (b * ((x * y) - (z * t)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((j <= -9.2e+69) || !(j <= 3e-172)) {
		tmp = b * (j * ((t * y4) - (x * y0)));
	} else {
		tmp = a * (b * ((x * y) - (z * t)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (j <= -9.2e+69) or not (j <= 3e-172):
		tmp = b * (j * ((t * y4) - (x * y0)))
	else:
		tmp = a * (b * ((x * y) - (z * t)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if ((j <= -9.2e+69) || !(j <= 3e-172))
		tmp = Float64(b * Float64(j * Float64(Float64(t * y4) - Float64(x * y0))));
	else
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if ((j <= -9.2e+69) || ~((j <= 3e-172)))
		tmp = b * (j * ((t * y4) - (x * y0)));
	else
		tmp = a * (b * ((x * y) - (z * t)));
	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[j, -9.2e+69], N[Not[LessEqual[j, 3e-172]], $MachinePrecision]], N[(b * N[(j * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if j < -9.20000000000000067e69 or 2.99999999999999984e-172 < j

   1. Initial program 23.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 37.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in j around inf 46.1%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]

   if -9.20000000000000067e69 < j < 2.99999999999999984e-172

   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. Taylor expanded in b around inf 33.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 29.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 38.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -9.2 \cdot 10^{+69} \lor \neg \left(j \leq 3 \cdot 10^{-172}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \end{array} \]

Alternative 36: 21.8% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y4 \leq -1.05 \cdot 10^{+59} \lor \neg \left(y4 \leq 1.9 \cdot 10^{+113}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= y4 -1.05e+59) (not (<= y4 1.9e+113)))
   (* b (* j (* t y4)))
   (* a (* (* x y) b))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((y4 <= -1.05e+59) || !(y4 <= 1.9e+113)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if ((y4 <= (-1.05d+59)) .or. (.not. (y4 <= 1.9d+113))) then
        tmp = b * (j * (t * y4))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((y4 <= -1.05e+59) || !(y4 <= 1.9e+113)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (y4 <= -1.05e+59) or not (y4 <= 1.9e+113):
		tmp = b * (j * (t * y4))
	else:
		tmp = a * ((x * y) * b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if ((y4 <= -1.05e+59) || !(y4 <= 1.9e+113))
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if ((y4 <= -1.05e+59) || ~((y4 <= 1.9e+113)))
		tmp = b * (j * (t * y4));
	else
		tmp = a * ((x * y) * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[Or[LessEqual[y4, -1.05e+59], N[Not[LessEqual[y4, 1.9e+113]], $MachinePrecision]], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y4 < -1.04999999999999992e59 or 1.9000000000000002e113 < y4

   1. Initial program 20.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 32.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around -inf 39.2%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 39.2%

         \[\leadsto \color{blue}{-b \cdot \left(t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 39.2%

         \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(-1 \cdot \left(j \cdot y4\right) + a \cdot z\right)\right)} \]

      3. +-commutative 39.2%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z + -1 \cdot \left(j \cdot y4\right)\right)}\right) \]

      4. mul-1-neg 39.2%

         \[\leadsto b \cdot \left(-t \cdot \left(a \cdot z + \color{blue}{\left(-j \cdot y4\right)}\right)\right) \]

      5. unsub-neg 39.2%

         \[\leadsto b \cdot \left(-t \cdot \color{blue}{\left(a \cdot z - j \cdot y4\right)}\right) \]

   5. Simplified 39.2%

      \[\leadsto \color{blue}{b \cdot \left(-t \cdot \left(a \cdot z - j \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 36.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -1.04999999999999992e59 < y4 < 1.9000000000000002e113

   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. Taylor expanded in x around inf 48.1%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in j around 0 44.7%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in b around inf 24.5%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 28.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.05 \cdot 10^{+59} \lor \neg \left(y4 \leq 1.9 \cdot 10^{+113}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 37: 16.4% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(\left(x \cdot y\right) \cdot b\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* (* x y) b)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * ((x * y) * b);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = a * ((x * y) * b)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * ((x * y) * b);
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * ((x * y) * b)

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(Float64(x * y) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * ((x * y) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 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. Taylor expanded in x around inf 42.8%

   \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

3. Taylor expanded in j around 0 40.1%

   \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

4. Taylor expanded in b around inf 21.3%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

5. Final simplification 21.3%

   \[\leadsto a \cdot \left(\left(x \cdot y\right) \cdot b\right) \]

Developer target: 27.8% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t_9\\ t_11 := t_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t_4 \cdot t_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t_3 \cdot t_1 - t_14\right)\right) + \left(t_8 - \left(t_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t_13\right)\right) + \left(t_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t_10 - \left(y \cdot x - z \cdot t\right) \cdot t_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t_8 - \left(t_11 - t_6\right)\right) - \left(\frac{t_3}{\frac{1}{t_1}} - t_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t_2 - \left(t_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t_5\right) - t_17 \cdot t_1\right) + t_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2023322 
(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
  :name "Linear.Matrix:det44 from linear-1.19.1.3"
  :precision binary64

  :herbie-target
  (if (< y4 -7.206256231996481e+60) (- (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))))) (- (/ (- (* y2 t) (* y3 y)) (/ 1.0 (- (* y4 c) (* y5 a)))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (if (< y4 -3.364603505246317e-66) (+ (- (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x))) (* (- (* b y0) (* i y1)) (- (* j x) (* k z)))) (- (* (- (* y0 c) (* a y1)) (- (* x y2) (* z y3))) (- (* (- (* t y2) (* y y3)) (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) (- (* k y2) (* j y3)))))) (if (< y4 -1.2000065055686116e-105) (+ (+ (- (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))) (* (* y3 y) (- (* y5 a) (* y4 c)))) (+ (* (* y5 a) (* t y2)) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))) (- (* (- (* b y0) (* i y1)) (- (* j x) (* k z))) (* (- (* y x) (* z t)) (- (* b a) (* i c)))))) (if (< y4 6.718963124057495e-279) (+ (- (- (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k))) (* (* y5 t) (* i j))) (- (* (- (* y2 t) (* y3 y)) (- (* y4 c) (* y5 a))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))) (if (< y4 4.77962681403792e-222) (+ (+ (- (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))) (* (* y3 y) (- (* y5 a) (* y4 c)))) (+ (* (* y5 a) (* t y2)) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))) (- (* (- (* b y0) (* i y1)) (- (* j x) (* k z))) (* (- (* y x) (* z t)) (- (* b a) (* i c)))))) (if (< y4 2.2852241541266835e-175) (+ (- (- (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k))) (* (* y5 t) (* i j))) (- (* (- (* y2 t) (* y3 y)) (- (* y4 c) (* y5 a))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))) (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (- (* k (* i (* z y1))) (+ (* j (* i (* x y1))) (* y0 (* k (* z b)))))) (- (* z (* y3 (* a y1))) (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3)))))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))))))))

  (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i)))) (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a)))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))