Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 29.4% → 38.8%

Time: 2.2min

Alternatives: 38

Speedup: 2.6×

• 89.2% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 29.4% 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: 38.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot j - y \cdot k\\ t_2 := y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ t_3 := b \cdot y4 - i \cdot y5\\ t_4 := y1 \cdot y4 - y0 \cdot y5\\ t_5 := i \cdot y1 - b \cdot y0\\ t_6 := x \cdot j - z \cdot k\\ t_7 := y1 \cdot t\_6\\ t_8 := a \cdot y5 - c \cdot y4\\ t_9 := y2 \cdot t\_8\\ t_10 := x \cdot y - z \cdot t\\ t_11 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot t\_10 + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ t_12 := c \cdot y0 - a \cdot y1\\ \mathbf{if}\;t \leq -1.45 \cdot 10^{+158}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot t\_3\right) + t\_9\right)\\ \mathbf{elif}\;t \leq -4 \cdot 10^{-61}:\\ \;\;\;\;t\_11\\ \mathbf{elif}\;t \leq -1.2 \cdot 10^{-96}:\\ \;\;\;\;i \cdot t\_7\\ \mathbf{elif}\;t \leq -4.4 \cdot 10^{-131}:\\ \;\;\;\;\left(k \cdot \left(y2 \cdot t\_4\right) + \left(x \cdot \left(y2 \cdot t\_12\right) + \left(\left(a \cdot b - c \cdot i\right) \cdot t\_10 + t\_3 \cdot t\_1\right)\right)\right) + \left(t \cdot t\_9 + t\_6 \cdot t\_5\right)\\ \mathbf{elif}\;t \leq -3.6 \cdot 10^{-258}:\\ \;\;\;\;j \cdot t\_2\\ \mathbf{elif}\;t \leq 4.1 \cdot 10^{-257}:\\ \;\;\;\;t\_11\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-48}:\\ \;\;\;\;i \cdot \left(t\_7 - \left(c \cdot t\_10 + y5 \cdot t\_1\right)\right)\\ \mathbf{elif}\;t \leq 10^{+16} \lor \neg \left(t \leq 1.95 \cdot 10^{+131}\right):\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_4 + x \cdot t\_12\right) + t \cdot t\_8\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(t \cdot t\_3 + t\_2\right) + x \cdot t\_5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t j) (* y k)))
        (t_2 (* y3 (- (* y0 y5) (* y1 y4))))
        (t_3 (- (* b y4) (* i y5)))
        (t_4 (- (* y1 y4) (* y0 y5)))
        (t_5 (- (* i y1) (* b y0)))
        (t_6 (- (* x j) (* z k)))
        (t_7 (* y1 t_6))
        (t_8 (- (* a y5) (* c y4)))
        (t_9 (* y2 t_8))
        (t_10 (- (* x y) (* z t)))
        (t_11
         (*
          a
          (+
           (* y5 (- (* t y2) (* y y3)))
           (+ (* b t_10) (* y1 (- (* z y3) (* x y2)))))))
        (t_12 (- (* c y0) (* a y1))))
   (if (<= t -1.45e+158)
     (* t (+ (+ (* z (- (* c i) (* a b))) (* j t_3)) t_9))
     (if (<= t -4e-61)
       t_11
       (if (<= t -1.2e-96)
         (* i t_7)
         (if (<= t -4.4e-131)
           (+
            (+
             (* k (* y2 t_4))
             (+
              (* x (* y2 t_12))
              (+ (* (- (* a b) (* c i)) t_10) (* t_3 t_1))))
            (+ (* t t_9) (* t_6 t_5)))
           (if (<= t -3.6e-258)
             (* j t_2)
             (if (<= t 4.1e-257)
               t_11
               (if (<= t 1.05e-48)
                 (* i (- t_7 (+ (* c t_10) (* y5 t_1))))
                 (if (or (<= t 1e+16) (not (<= t 1.95e+131)))
                   (* y2 (+ (+ (* k t_4) (* x t_12)) (* t t_8)))
                   (* j (+ (+ (* t t_3) t_2) (* x 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 = (t * j) - (y * k);
	double t_2 = y3 * ((y0 * y5) - (y1 * y4));
	double t_3 = (b * y4) - (i * y5);
	double t_4 = (y1 * y4) - (y0 * y5);
	double t_5 = (i * y1) - (b * y0);
	double t_6 = (x * j) - (z * k);
	double t_7 = y1 * t_6;
	double t_8 = (a * y5) - (c * y4);
	double t_9 = y2 * t_8;
	double t_10 = (x * y) - (z * t);
	double t_11 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_10) + (y1 * ((z * y3) - (x * y2)))));
	double t_12 = (c * y0) - (a * y1);
	double tmp;
	if (t <= -1.45e+158) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_3)) + t_9);
	} else if (t <= -4e-61) {
		tmp = t_11;
	} else if (t <= -1.2e-96) {
		tmp = i * t_7;
	} else if (t <= -4.4e-131) {
		tmp = ((k * (y2 * t_4)) + ((x * (y2 * t_12)) + ((((a * b) - (c * i)) * t_10) + (t_3 * t_1)))) + ((t * t_9) + (t_6 * t_5));
	} else if (t <= -3.6e-258) {
		tmp = j * t_2;
	} else if (t <= 4.1e-257) {
		tmp = t_11;
	} else if (t <= 1.05e-48) {
		tmp = i * (t_7 - ((c * t_10) + (y5 * t_1)));
	} else if ((t <= 1e+16) || !(t <= 1.95e+131)) {
		tmp = y2 * (((k * t_4) + (x * t_12)) + (t * t_8));
	} else {
		tmp = j * (((t * t_3) + t_2) + (x * 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_11
    real(8) :: t_12
    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 = (t * j) - (y * k)
    t_2 = y3 * ((y0 * y5) - (y1 * y4))
    t_3 = (b * y4) - (i * y5)
    t_4 = (y1 * y4) - (y0 * y5)
    t_5 = (i * y1) - (b * y0)
    t_6 = (x * j) - (z * k)
    t_7 = y1 * t_6
    t_8 = (a * y5) - (c * y4)
    t_9 = y2 * t_8
    t_10 = (x * y) - (z * t)
    t_11 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_10) + (y1 * ((z * y3) - (x * y2)))))
    t_12 = (c * y0) - (a * y1)
    if (t <= (-1.45d+158)) then
        tmp = t * (((z * ((c * i) - (a * b))) + (j * t_3)) + t_9)
    else if (t <= (-4d-61)) then
        tmp = t_11
    else if (t <= (-1.2d-96)) then
        tmp = i * t_7
    else if (t <= (-4.4d-131)) then
        tmp = ((k * (y2 * t_4)) + ((x * (y2 * t_12)) + ((((a * b) - (c * i)) * t_10) + (t_3 * t_1)))) + ((t * t_9) + (t_6 * t_5))
    else if (t <= (-3.6d-258)) then
        tmp = j * t_2
    else if (t <= 4.1d-257) then
        tmp = t_11
    else if (t <= 1.05d-48) then
        tmp = i * (t_7 - ((c * t_10) + (y5 * t_1)))
    else if ((t <= 1d+16) .or. (.not. (t <= 1.95d+131))) then
        tmp = y2 * (((k * t_4) + (x * t_12)) + (t * t_8))
    else
        tmp = j * (((t * t_3) + t_2) + (x * 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 = (t * j) - (y * k);
	double t_2 = y3 * ((y0 * y5) - (y1 * y4));
	double t_3 = (b * y4) - (i * y5);
	double t_4 = (y1 * y4) - (y0 * y5);
	double t_5 = (i * y1) - (b * y0);
	double t_6 = (x * j) - (z * k);
	double t_7 = y1 * t_6;
	double t_8 = (a * y5) - (c * y4);
	double t_9 = y2 * t_8;
	double t_10 = (x * y) - (z * t);
	double t_11 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_10) + (y1 * ((z * y3) - (x * y2)))));
	double t_12 = (c * y0) - (a * y1);
	double tmp;
	if (t <= -1.45e+158) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_3)) + t_9);
	} else if (t <= -4e-61) {
		tmp = t_11;
	} else if (t <= -1.2e-96) {
		tmp = i * t_7;
	} else if (t <= -4.4e-131) {
		tmp = ((k * (y2 * t_4)) + ((x * (y2 * t_12)) + ((((a * b) - (c * i)) * t_10) + (t_3 * t_1)))) + ((t * t_9) + (t_6 * t_5));
	} else if (t <= -3.6e-258) {
		tmp = j * t_2;
	} else if (t <= 4.1e-257) {
		tmp = t_11;
	} else if (t <= 1.05e-48) {
		tmp = i * (t_7 - ((c * t_10) + (y5 * t_1)));
	} else if ((t <= 1e+16) || !(t <= 1.95e+131)) {
		tmp = y2 * (((k * t_4) + (x * t_12)) + (t * t_8));
	} else {
		tmp = j * (((t * t_3) + t_2) + (x * 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 = (t * j) - (y * k)
	t_2 = y3 * ((y0 * y5) - (y1 * y4))
	t_3 = (b * y4) - (i * y5)
	t_4 = (y1 * y4) - (y0 * y5)
	t_5 = (i * y1) - (b * y0)
	t_6 = (x * j) - (z * k)
	t_7 = y1 * t_6
	t_8 = (a * y5) - (c * y4)
	t_9 = y2 * t_8
	t_10 = (x * y) - (z * t)
	t_11 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_10) + (y1 * ((z * y3) - (x * y2)))))
	t_12 = (c * y0) - (a * y1)
	tmp = 0
	if t <= -1.45e+158:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_3)) + t_9)
	elif t <= -4e-61:
		tmp = t_11
	elif t <= -1.2e-96:
		tmp = i * t_7
	elif t <= -4.4e-131:
		tmp = ((k * (y2 * t_4)) + ((x * (y2 * t_12)) + ((((a * b) - (c * i)) * t_10) + (t_3 * t_1)))) + ((t * t_9) + (t_6 * t_5))
	elif t <= -3.6e-258:
		tmp = j * t_2
	elif t <= 4.1e-257:
		tmp = t_11
	elif t <= 1.05e-48:
		tmp = i * (t_7 - ((c * t_10) + (y5 * t_1)))
	elif (t <= 1e+16) or not (t <= 1.95e+131):
		tmp = y2 * (((k * t_4) + (x * t_12)) + (t * t_8))
	else:
		tmp = j * (((t * t_3) + t_2) + (x * 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(t * j) - Float64(y * k))
	t_2 = Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))
	t_3 = Float64(Float64(b * y4) - Float64(i * y5))
	t_4 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_5 = Float64(Float64(i * y1) - Float64(b * y0))
	t_6 = Float64(Float64(x * j) - Float64(z * k))
	t_7 = Float64(y1 * t_6)
	t_8 = Float64(Float64(a * y5) - Float64(c * y4))
	t_9 = Float64(y2 * t_8)
	t_10 = Float64(Float64(x * y) - Float64(z * t))
	t_11 = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(b * t_10) + Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))))
	t_12 = Float64(Float64(c * y0) - Float64(a * y1))
	tmp = 0.0
	if (t <= -1.45e+158)
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * t_3)) + t_9));
	elseif (t <= -4e-61)
		tmp = t_11;
	elseif (t <= -1.2e-96)
		tmp = Float64(i * t_7);
	elseif (t <= -4.4e-131)
		tmp = Float64(Float64(Float64(k * Float64(y2 * t_4)) + Float64(Float64(x * Float64(y2 * t_12)) + Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * t_10) + Float64(t_3 * t_1)))) + Float64(Float64(t * t_9) + Float64(t_6 * t_5)));
	elseif (t <= -3.6e-258)
		tmp = Float64(j * t_2);
	elseif (t <= 4.1e-257)
		tmp = t_11;
	elseif (t <= 1.05e-48)
		tmp = Float64(i * Float64(t_7 - Float64(Float64(c * t_10) + Float64(y5 * t_1))));
	elseif ((t <= 1e+16) || !(t <= 1.95e+131))
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_4) + Float64(x * t_12)) + Float64(t * t_8)));
	else
		tmp = Float64(j * Float64(Float64(Float64(t * t_3) + t_2) + Float64(x * 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 = (t * j) - (y * k);
	t_2 = y3 * ((y0 * y5) - (y1 * y4));
	t_3 = (b * y4) - (i * y5);
	t_4 = (y1 * y4) - (y0 * y5);
	t_5 = (i * y1) - (b * y0);
	t_6 = (x * j) - (z * k);
	t_7 = y1 * t_6;
	t_8 = (a * y5) - (c * y4);
	t_9 = y2 * t_8;
	t_10 = (x * y) - (z * t);
	t_11 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_10) + (y1 * ((z * y3) - (x * y2)))));
	t_12 = (c * y0) - (a * y1);
	tmp = 0.0;
	if (t <= -1.45e+158)
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_3)) + t_9);
	elseif (t <= -4e-61)
		tmp = t_11;
	elseif (t <= -1.2e-96)
		tmp = i * t_7;
	elseif (t <= -4.4e-131)
		tmp = ((k * (y2 * t_4)) + ((x * (y2 * t_12)) + ((((a * b) - (c * i)) * t_10) + (t_3 * t_1)))) + ((t * t_9) + (t_6 * t_5));
	elseif (t <= -3.6e-258)
		tmp = j * t_2;
	elseif (t <= 4.1e-257)
		tmp = t_11;
	elseif (t <= 1.05e-48)
		tmp = i * (t_7 - ((c * t_10) + (y5 * t_1)));
	elseif ((t <= 1e+16) || ~((t <= 1.95e+131)))
		tmp = y2 * (((k * t_4) + (x * t_12)) + (t * t_8));
	else
		tmp = j * (((t * t_3) + t_2) + (x * 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[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(y1 * t$95$6), $MachinePrecision]}, Block[{t$95$8 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(y2 * t$95$8), $MachinePrecision]}, Block[{t$95$10 = N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$11 = N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(b * t$95$10), $MachinePrecision] + N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.45e+158], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$3), $MachinePrecision]), $MachinePrecision] + t$95$9), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4e-61], t$95$11, If[LessEqual[t, -1.2e-96], N[(i * t$95$7), $MachinePrecision], If[LessEqual[t, -4.4e-131], N[(N[(N[(k * N[(y2 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(N[(x * N[(y2 * t$95$12), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] * t$95$10), $MachinePrecision] + N[(t$95$3 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(t * t$95$9), $MachinePrecision] + N[(t$95$6 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.6e-258], N[(j * t$95$2), $MachinePrecision], If[LessEqual[t, 4.1e-257], t$95$11, If[LessEqual[t, 1.05e-48], N[(i * N[(t$95$7 - N[(N[(c * t$95$10), $MachinePrecision] + N[(y5 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[t, 1e+16], N[Not[LessEqual[t, 1.95e+131]], $MachinePrecision]], N[(y2 * N[(N[(N[(k * t$95$4), $MachinePrecision] + N[(x * t$95$12), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$8), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(N[(N[(t * t$95$3), $MachinePrecision] + t$95$2), $MachinePrecision] + N[(x * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -1.45000000000000012e158

   1. Initial program 19.5%

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

   3. Taylor expanded in t around inf 58.4%

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

   if -1.45000000000000012e158 < t < -4.0000000000000002e-61 or -3.59999999999999979e-258 < t < 4.0999999999999997e-257

   1. Initial program 35.0%

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

   3. Taylor expanded in a around -inf 61.1%

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

      1. mul-1-neg 61.1%

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

      2. *-commutative 61.1%

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

      3. distribute-rgt-neg-in 61.1%

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

   5. Simplified 61.1%

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

   if -4.0000000000000002e-61 < t < -1.2000000000000001e-96

   1. Initial program 12.5%

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

   3. Taylor expanded in y1 around inf 62.5%

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

   4. Taylor expanded in i around inf 75.6%

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

   if -1.2000000000000001e-96 < t < -4.3999999999999999e-131

   1. Initial program 63.5%

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

   3. Taylor expanded in y3 around 0 67.9%

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

   if -4.3999999999999999e-131 < t < -3.59999999999999979e-258

   1. Initial program 12.0%

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

   3. Taylor expanded in j around inf 36.5%

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

      1. +-commutative 36.5%

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

      2. mul-1-neg 36.5%

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

      3. unsub-neg 36.5%

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

      4. *-commutative 36.5%

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

   5. Simplified 36.5%

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

   6. Taylor expanded in y3 around inf 56.8%

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

      1. *-commutative 56.8%

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

      2. *-commutative 56.8%

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

   8. Simplified 56.8%

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

   if 4.0999999999999997e-257 < t < 1.04999999999999994e-48

   1. Initial program 34.4%

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

   3. Taylor expanded in i around -inf 64.4%

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

   if 1.04999999999999994e-48 < t < 1e16 or 1.95e131 < t

   1. Initial program 21.2%

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

   3. Taylor expanded in y2 around inf 77.2%

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

   if 1e16 < t < 1.95e131

   1. Initial program 25.8%

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

   3. Taylor expanded in j around inf 55.6%

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

      1. +-commutative 55.6%

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

      2. mul-1-neg 55.6%

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

      3. unsub-neg 55.6%

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

      4. *-commutative 55.6%

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

   5. Simplified 55.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 64.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.45 \cdot 10^{+158}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -4 \cdot 10^{-61}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -1.2 \cdot 10^{-96}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -4.4 \cdot 10^{-131}:\\ \;\;\;\;\left(k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + \left(x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\right) + \left(t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq -3.6 \cdot 10^{-258}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 4.1 \cdot 10^{-257}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-48}:\\ \;\;\;\;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}\;t \leq 10^{+16} \lor \neg \left(t \leq 1.95 \cdot 10^{+131}\right):\\ \;\;\;\;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{else}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 52.8% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot y4 - a \cdot y5\\ t_2 := y1 \cdot y4 - y0 \cdot y5\\ t_3 := c \cdot y0 - a \cdot y1\\ t_4 := \left(\left(\left(\left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(x \cdot j - z \cdot k\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\right) + t\_3 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right)\right) + t\_1 \cdot \left(y \cdot y3 - t \cdot y2\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot t\_2\\ \mathbf{if}\;t\_4 \leq \infty:\\ \;\;\;\;t\_4\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(y \cdot t\_1 - \left(j \cdot t\_2 + z \cdot t\_3\right)\right)\\ \end{array} \end{array} \]

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) (* a y5)))
        (t_2 (- (* y1 y4) (* y0 y5)))
        (t_3 (- (* c y0) (* a y1)))
        (t_4
         (+
          (+
           (+
            (+
             (+
              (* (- (* a b) (* c i)) (- (* x y) (* z t)))
              (* (- (* x j) (* z k)) (- (* i y1) (* b y0))))
             (* t_3 (- (* x y2) (* z y3))))
            (* (- (* b y4) (* i y5)) (- (* t j) (* y k))))
           (* t_1 (- (* y y3) (* t y2))))
          (* (- (* k y2) (* j y3)) t_2))))
   (if (<= t_4 INFINITY) t_4 (* y3 (- (* y t_1) (+ (* j t_2) (* z 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 = (c * y4) - (a * y5);
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = (c * y0) - (a * y1);
	double t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * t_2);
	double tmp;
	if (t_4 <= ((double) INFINITY)) {
		tmp = t_4;
	} else {
		tmp = y3 * ((y * t_1) - ((j * t_2) + (z * t_3)));
	}
	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 = (c * y4) - (a * y5);
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = (c * y0) - (a * y1);
	double t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * t_2);
	double tmp;
	if (t_4 <= Double.POSITIVE_INFINITY) {
		tmp = t_4;
	} else {
		tmp = y3 * ((y * t_1) - ((j * t_2) + (z * 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 = (c * y4) - (a * y5)
	t_2 = (y1 * y4) - (y0 * y5)
	t_3 = (c * y0) - (a * y1)
	t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * t_2)
	tmp = 0
	if t_4 <= math.inf:
		tmp = t_4
	else:
		tmp = y3 * ((y * t_1) - ((j * t_2) + (z * 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(c * y4) - Float64(a * y5))
	t_2 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_3 = Float64(Float64(c * y0) - Float64(a * y1))
	t_4 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t))) + Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(i * y1) - Float64(b * y0)))) + Float64(t_3 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(Float64(Float64(b * y4) - Float64(i * y5)) * Float64(Float64(t * j) - Float64(y * k)))) + Float64(t_1 * Float64(Float64(y * y3) - Float64(t * y2)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_2))
	tmp = 0.0
	if (t_4 <= Inf)
		tmp = t_4;
	else
		tmp = Float64(y3 * Float64(Float64(y * t_1) - Float64(Float64(j * t_2) + Float64(z * 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 = (c * y4) - (a * y5);
	t_2 = (y1 * y4) - (y0 * y5);
	t_3 = (c * y0) - (a * y1);
	t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (t_1 * ((y * y3) - (t * y2)))) + (((k * y2) - (j * y3)) * t_2);
	tmp = 0.0;
	if (t_4 <= Inf)
		tmp = t_4;
	else
		tmp = y3 * ((y * t_1) - ((j * t_2) + (z * 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[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[(N[(N[(N[(N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision] * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$4, Infinity], t$95$4, N[(y3 * N[(N[(y * t$95$1), $MachinePrecision] - N[(N[(j * t$95$2), $MachinePrecision] + N[(z * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 2 regimes

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

   1. Initial program 88.3%

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

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

   1. Initial program 0.0%

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

   3. Taylor expanded in y3 around -inf 40.0%

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

4. Final simplification 55.2%

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

Alternative 3: 35.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \left(b \cdot y4 - i \cdot y5\right)\\ t_2 := i \cdot y1 - b \cdot y0\\ t_3 := x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot t\_2\right)\\ t_4 := z \cdot k - x \cdot j\\ t_5 := y0 \cdot t\_4\\ t_6 := j \cdot \left(\left(t\_1 + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot t\_2\right)\\ \mathbf{if}\;t \leq -2.1 \cdot 10^{+191}:\\ \;\;\;\;j \cdot t\_1\\ \mathbf{elif}\;t \leq -3 \cdot 10^{+72}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -2.2 \cdot 10^{+55}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-35}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-199}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;t \leq -4.5 \cdot 10^{-289}:\\ \;\;\;\;\left(x \cdot c - k \cdot y5\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{-215}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{-98}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot t\_4\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-44}:\\ \;\;\;\;b \cdot t\_5\\ \mathbf{elif}\;t \leq 11500000:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{+25}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + t\_5\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{+154}:\\ \;\;\;\;t\_6\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* t (- (* b y4) (* i y5))))
        (t_2 (- (* i y1) (* b y0)))
        (t_3
         (*
          x
          (+
           (+ (* y2 (- (* c y0) (* a y1))) (* y (- (* a b) (* c i))))
           (* j t_2))))
        (t_4 (- (* z k) (* x j)))
        (t_5 (* y0 t_4))
        (t_6 (* j (+ (+ t_1 (* y3 (- (* y0 y5) (* y1 y4)))) (* x t_2)))))
   (if (<= t -2.1e+191)
     (* j t_1)
     (if (<= t -3e+72)
       (* y1 (* z (- (* a y3) (* i k))))
       (if (<= t -2.2e+55)
         (* y4 (* c (- (* y y3) (* t y2))))
         (if (<= t -2.8e-35)
           t_3
           (if (<= t -9e-199)
             t_6
             (if (<= t -4.5e-289)
               (* (- (* x c) (* k y5)) (* y0 y2))
               (if (<= t 1.15e-215)
                 t_3
                 (if (<= t 2.4e-98)
                   (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i t_4)))
                   (if (<= t 3.8e-44)
                     (* b t_5)
                     (if (<= t 11500000.0)
                       (* c (* y3 (- (* y y4) (* z y0))))
                       (if (<= t 3e+25)
                         (*
                          b
                          (+
                           (+
                            (* a (- (* x y) (* z t)))
                            (* y4 (- (* t j) (* y k))))
                           t_5))
                         (if (<= t 3e+154)
                           t_6
                           (* t (* y2 (- (* a y5) (* c y4))))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = t * ((b * y4) - (i * y5));
	double t_2 = (i * y1) - (b * y0);
	double t_3 = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_2));
	double t_4 = (z * k) - (x * j);
	double t_5 = y0 * t_4;
	double t_6 = j * ((t_1 + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_2));
	double tmp;
	if (t <= -2.1e+191) {
		tmp = j * t_1;
	} else if (t <= -3e+72) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (t <= -2.2e+55) {
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	} else if (t <= -2.8e-35) {
		tmp = t_3;
	} else if (t <= -9e-199) {
		tmp = t_6;
	} else if (t <= -4.5e-289) {
		tmp = ((x * c) - (k * y5)) * (y0 * y2);
	} else if (t <= 1.15e-215) {
		tmp = t_3;
	} else if (t <= 2.4e-98) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_4));
	} else if (t <= 3.8e-44) {
		tmp = b * t_5;
	} else if (t <= 11500000.0) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (t <= 3e+25) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_5);
	} else if (t <= 3e+154) {
		tmp = t_6;
	} else {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = t * ((b * y4) - (i * y5))
    t_2 = (i * y1) - (b * y0)
    t_3 = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_2))
    t_4 = (z * k) - (x * j)
    t_5 = y0 * t_4
    t_6 = j * ((t_1 + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_2))
    if (t <= (-2.1d+191)) then
        tmp = j * t_1
    else if (t <= (-3d+72)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (t <= (-2.2d+55)) then
        tmp = y4 * (c * ((y * y3) - (t * y2)))
    else if (t <= (-2.8d-35)) then
        tmp = t_3
    else if (t <= (-9d-199)) then
        tmp = t_6
    else if (t <= (-4.5d-289)) then
        tmp = ((x * c) - (k * y5)) * (y0 * y2)
    else if (t <= 1.15d-215) then
        tmp = t_3
    else if (t <= 2.4d-98) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_4))
    else if (t <= 3.8d-44) then
        tmp = b * t_5
    else if (t <= 11500000.0d0) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (t <= 3d+25) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_5)
    else if (t <= 3d+154) then
        tmp = t_6
    else
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = t * ((b * y4) - (i * y5));
	double t_2 = (i * y1) - (b * y0);
	double t_3 = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_2));
	double t_4 = (z * k) - (x * j);
	double t_5 = y0 * t_4;
	double t_6 = j * ((t_1 + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_2));
	double tmp;
	if (t <= -2.1e+191) {
		tmp = j * t_1;
	} else if (t <= -3e+72) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (t <= -2.2e+55) {
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	} else if (t <= -2.8e-35) {
		tmp = t_3;
	} else if (t <= -9e-199) {
		tmp = t_6;
	} else if (t <= -4.5e-289) {
		tmp = ((x * c) - (k * y5)) * (y0 * y2);
	} else if (t <= 1.15e-215) {
		tmp = t_3;
	} else if (t <= 2.4e-98) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_4));
	} else if (t <= 3.8e-44) {
		tmp = b * t_5;
	} else if (t <= 11500000.0) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (t <= 3e+25) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_5);
	} else if (t <= 3e+154) {
		tmp = t_6;
	} else {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = t * ((b * y4) - (i * y5))
	t_2 = (i * y1) - (b * y0)
	t_3 = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_2))
	t_4 = (z * k) - (x * j)
	t_5 = y0 * t_4
	t_6 = j * ((t_1 + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_2))
	tmp = 0
	if t <= -2.1e+191:
		tmp = j * t_1
	elif t <= -3e+72:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif t <= -2.2e+55:
		tmp = y4 * (c * ((y * y3) - (t * y2)))
	elif t <= -2.8e-35:
		tmp = t_3
	elif t <= -9e-199:
		tmp = t_6
	elif t <= -4.5e-289:
		tmp = ((x * c) - (k * y5)) * (y0 * y2)
	elif t <= 1.15e-215:
		tmp = t_3
	elif t <= 2.4e-98:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_4))
	elif t <= 3.8e-44:
		tmp = b * t_5
	elif t <= 11500000.0:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif t <= 3e+25:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_5)
	elif t <= 3e+154:
		tmp = t_6
	else:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))
	t_2 = Float64(Float64(i * y1) - Float64(b * y0))
	t_3 = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) + Float64(y * Float64(Float64(a * b) - Float64(c * i)))) + Float64(j * t_2)))
	t_4 = Float64(Float64(z * k) - Float64(x * j))
	t_5 = Float64(y0 * t_4)
	t_6 = Float64(j * Float64(Float64(t_1 + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * t_2)))
	tmp = 0.0
	if (t <= -2.1e+191)
		tmp = Float64(j * t_1);
	elseif (t <= -3e+72)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (t <= -2.2e+55)
		tmp = Float64(y4 * Float64(c * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= -2.8e-35)
		tmp = t_3;
	elseif (t <= -9e-199)
		tmp = t_6;
	elseif (t <= -4.5e-289)
		tmp = Float64(Float64(Float64(x * c) - Float64(k * y5)) * Float64(y0 * y2));
	elseif (t <= 1.15e-215)
		tmp = t_3;
	elseif (t <= 2.4e-98)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * t_4)));
	elseif (t <= 3.8e-44)
		tmp = Float64(b * t_5);
	elseif (t <= 11500000.0)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (t <= 3e+25)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + t_5));
	elseif (t <= 3e+154)
		tmp = t_6;
	else
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = t * ((b * y4) - (i * y5));
	t_2 = (i * y1) - (b * y0);
	t_3 = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_2));
	t_4 = (z * k) - (x * j);
	t_5 = y0 * t_4;
	t_6 = j * ((t_1 + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * t_2));
	tmp = 0.0;
	if (t <= -2.1e+191)
		tmp = j * t_1;
	elseif (t <= -3e+72)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (t <= -2.2e+55)
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	elseif (t <= -2.8e-35)
		tmp = t_3;
	elseif (t <= -9e-199)
		tmp = t_6;
	elseif (t <= -4.5e-289)
		tmp = ((x * c) - (k * y5)) * (y0 * y2);
	elseif (t <= 1.15e-215)
		tmp = t_3;
	elseif (t <= 2.4e-98)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_4));
	elseif (t <= 3.8e-44)
		tmp = b * t_5;
	elseif (t <= 11500000.0)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (t <= 3e+25)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + t_5);
	elseif (t <= 3e+154)
		tmp = t_6;
	else
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(y0 * t$95$4), $MachinePrecision]}, Block[{t$95$6 = N[(j * N[(N[(t$95$1 + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.1e+191], N[(j * t$95$1), $MachinePrecision], If[LessEqual[t, -3e+72], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.2e+55], N[(y4 * N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.8e-35], t$95$3, If[LessEqual[t, -9e-199], t$95$6, If[LessEqual[t, -4.5e-289], N[(N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision] * N[(y0 * y2), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.15e-215], t$95$3, If[LessEqual[t, 2.4e-98], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-44], N[(b * t$95$5), $MachinePrecision], If[LessEqual[t, 11500000.0], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3e+25], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$5), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3e+154], t$95$6, N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if t < -2.1000000000000001e191

   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. Add Preprocessing

   3. Taylor expanded in j around inf 45.4%

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

      1. +-commutative 45.4%

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

      2. mul-1-neg 45.4%

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

      3. unsub-neg 45.4%

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

      4. *-commutative 45.4%

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

   5. Simplified 45.4%

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

   6. Taylor expanded in t around inf 56.0%

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

   if -2.1000000000000001e191 < t < -3.00000000000000003e72

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 34.4%

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

   4. Taylor expanded in z around inf 56.3%

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

   if -3.00000000000000003e72 < t < -2.2000000000000001e55

   1. Initial program 19.7%

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

   3. Taylor expanded in y4 around inf 42.9%

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

   4. Taylor expanded in c around inf 62.9%

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

      1. *-commutative 62.9%

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

   6. Simplified 62.9%

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

   if -2.2000000000000001e55 < t < -2.8e-35 or -4.5000000000000002e-289 < t < 1.15e-215

   1. Initial program 42.9%

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

   3. Taylor expanded in 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 -2.8e-35 < t < -8.99999999999999995e-199 or 3.00000000000000006e25 < t < 3.00000000000000026e154

   1. Initial program 26.9%

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

   3. Taylor expanded in j around inf 51.2%

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

      1. +-commutative 51.2%

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

      2. mul-1-neg 51.2%

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

      3. unsub-neg 51.2%

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

      4. *-commutative 51.2%

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

   5. Simplified 51.2%

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

   if -8.99999999999999995e-199 < t < -4.5000000000000002e-289

   1. Initial program 21.1%

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

   3. Taylor expanded in y2 around inf 47.4%

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

   4. Taylor expanded in y0 around inf 68.6%

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

      1. associate-*r* 68.7%

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

      2. +-commutative 68.7%

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

      3. mul-1-neg 68.7%

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

      4. unsub-neg 68.7%

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

      5. *-commutative 68.7%

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

   6. Simplified 68.7%

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

   if 1.15e-215 < t < 2.40000000000000005e-98

   1. Initial program 32.4%

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

   3. Taylor expanded in y1 around inf 52.6%

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

   4. Taylor expanded in a around 0 72.6%

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

      1. associate-*r* 72.6%

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

      2. neg-mul-1 72.6%

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

      3. *-commutative 72.6%

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

   6. Simplified 72.6%

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

   if 2.40000000000000005e-98 < t < 3.8000000000000001e-44

   1. Initial program 27.3%

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

   3. Taylor expanded in b around inf 45.9%

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

   4. Taylor expanded in y0 around inf 73.2%

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

   if 3.8000000000000001e-44 < t < 1.15e7

   1. Initial program 26.7%

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

   3. Taylor expanded in y3 around -inf 67.7%

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

   4. Taylor expanded in c around inf 54.7%

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

   if 1.15e7 < t < 3.00000000000000006e25

   1. Initial program 66.7%

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

   3. Taylor expanded in b around inf 84.2%

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

   if 3.00000000000000026e154 < t

   1. Initial program 12.9%

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

   3. Taylor expanded in y2 around inf 81.0%

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

   4. Taylor expanded in t around inf 74.7%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 60.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.1 \cdot 10^{+191}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -3 \cdot 10^{+72}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -2.2 \cdot 10^{+55}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-35}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-199}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq -4.5 \cdot 10^{-289}:\\ \;\;\;\;\left(x \cdot c - k \cdot y5\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{-215}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{-98}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-44}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 11500000:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{+25}:\\ \;\;\;\;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}\;t \leq 3 \cdot 10^{+154}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 34.5% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot y - z \cdot t\right)\\ t_2 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(t\_1 + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ t_3 := i \cdot y1 - b \cdot y0\\ t_4 := x \cdot t\_3\\ t_5 := t \cdot \left(b \cdot y4 - i \cdot y5\right)\\ t_6 := j \cdot \left(\left(t\_5 + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + t\_4\right)\\ t_7 := j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -2.5 \cdot 10^{+113}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot t\_3\right)\\ \mathbf{elif}\;y \leq -6 \cdot 10^{+25}:\\ \;\;\;\;a \cdot t\_1\\ \mathbf{elif}\;y \leq -4.3 \cdot 10^{-60}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -1.6 \cdot 10^{-72}:\\ \;\;\;\;j \cdot t\_5\\ \mathbf{elif}\;y \leq -3.9 \cdot 10^{-160}:\\ \;\;\;\;j \cdot t\_4\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{-293}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-274}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 1.3 \cdot 10^{-137}:\\ \;\;\;\;t\_7\\ \mathbf{elif}\;y \leq 1.25 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 9.6:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;y \leq 1.52 \cdot 10^{+88}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{+164}:\\ \;\;\;\;t\_7\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (- (* x y) (* z t))))
        (t_2
         (*
          a
          (+
           (* y5 (- (* t y2) (* y y3)))
           (+ t_1 (* y1 (- (* z y3) (* x y2)))))))
        (t_3 (- (* i y1) (* b y0)))
        (t_4 (* x t_3))
        (t_5 (* t (- (* b y4) (* i y5))))
        (t_6 (* j (+ (+ t_5 (* y3 (- (* y0 y5) (* y1 y4)))) t_4)))
        (t_7
         (*
          j
          (-
           (- (* y1 (* x i)) (* y4 (* y1 y3)))
           (* t (- (* i y5) (* b y4)))))))
   (if (<= y -2.5e+113)
     (*
      x
      (+ (+ (* y2 (- (* c y0) (* a y1))) (* y (- (* a b) (* c i)))) (* j t_3)))
     (if (<= y -6e+25)
       (* a t_1)
       (if (<= y -4.3e-60)
         (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i (- (* z k) (* x j)))))
         (if (<= y -1.6e-72)
           (* j t_5)
           (if (<= y -3.9e-160)
             (* j t_4)
             (if (<= y -1.5e-293)
               t_6
               (if (<= y 3e-274)
                 t_2
                 (if (<= y 1.3e-137)
                   t_7
                   (if (<= y 1.25e-24)
                     (* t (* y2 (- (* a y5) (* c y4))))
                     (if (<= y 9.6)
                       t_6
                       (if (<= y 1.52e+88)
                         t_2
                         (if (<= y 1.8e+164)
                           t_7
                           (* y4 (* k (- (* y1 y2) (* 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 t_1 = b * ((x * y) - (z * t));
	double t_2 = a * ((y5 * ((t * y2) - (y * y3))) + (t_1 + (y1 * ((z * y3) - (x * y2)))));
	double t_3 = (i * y1) - (b * y0);
	double t_4 = x * t_3;
	double t_5 = t * ((b * y4) - (i * y5));
	double t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_4);
	double t_7 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double tmp;
	if (y <= -2.5e+113) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_3));
	} else if (y <= -6e+25) {
		tmp = a * t_1;
	} else if (y <= -4.3e-60) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -1.6e-72) {
		tmp = j * t_5;
	} else if (y <= -3.9e-160) {
		tmp = j * t_4;
	} else if (y <= -1.5e-293) {
		tmp = t_6;
	} else if (y <= 3e-274) {
		tmp = t_2;
	} else if (y <= 1.3e-137) {
		tmp = t_7;
	} else if (y <= 1.25e-24) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y <= 9.6) {
		tmp = t_6;
	} else if (y <= 1.52e+88) {
		tmp = t_2;
	} else if (y <= 1.8e+164) {
		tmp = t_7;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: tmp
    t_1 = b * ((x * y) - (z * t))
    t_2 = a * ((y5 * ((t * y2) - (y * y3))) + (t_1 + (y1 * ((z * y3) - (x * y2)))))
    t_3 = (i * y1) - (b * y0)
    t_4 = x * t_3
    t_5 = t * ((b * y4) - (i * y5))
    t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_4)
    t_7 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
    if (y <= (-2.5d+113)) then
        tmp = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_3))
    else if (y <= (-6d+25)) then
        tmp = a * t_1
    else if (y <= (-4.3d-60)) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
    else if (y <= (-1.6d-72)) then
        tmp = j * t_5
    else if (y <= (-3.9d-160)) then
        tmp = j * t_4
    else if (y <= (-1.5d-293)) then
        tmp = t_6
    else if (y <= 3d-274) then
        tmp = t_2
    else if (y <= 1.3d-137) then
        tmp = t_7
    else if (y <= 1.25d-24) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (y <= 9.6d0) then
        tmp = t_6
    else if (y <= 1.52d+88) then
        tmp = t_2
    else if (y <= 1.8d+164) then
        tmp = t_7
    else
        tmp = y4 * (k * ((y1 * y2) - (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 t_1 = b * ((x * y) - (z * t));
	double t_2 = a * ((y5 * ((t * y2) - (y * y3))) + (t_1 + (y1 * ((z * y3) - (x * y2)))));
	double t_3 = (i * y1) - (b * y0);
	double t_4 = x * t_3;
	double t_5 = t * ((b * y4) - (i * y5));
	double t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_4);
	double t_7 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double tmp;
	if (y <= -2.5e+113) {
		tmp = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_3));
	} else if (y <= -6e+25) {
		tmp = a * t_1;
	} else if (y <= -4.3e-60) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -1.6e-72) {
		tmp = j * t_5;
	} else if (y <= -3.9e-160) {
		tmp = j * t_4;
	} else if (y <= -1.5e-293) {
		tmp = t_6;
	} else if (y <= 3e-274) {
		tmp = t_2;
	} else if (y <= 1.3e-137) {
		tmp = t_7;
	} else if (y <= 1.25e-24) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y <= 9.6) {
		tmp = t_6;
	} else if (y <= 1.52e+88) {
		tmp = t_2;
	} else if (y <= 1.8e+164) {
		tmp = t_7;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * ((x * y) - (z * t))
	t_2 = a * ((y5 * ((t * y2) - (y * y3))) + (t_1 + (y1 * ((z * y3) - (x * y2)))))
	t_3 = (i * y1) - (b * y0)
	t_4 = x * t_3
	t_5 = t * ((b * y4) - (i * y5))
	t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_4)
	t_7 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
	tmp = 0
	if y <= -2.5e+113:
		tmp = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_3))
	elif y <= -6e+25:
		tmp = a * t_1
	elif y <= -4.3e-60:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
	elif y <= -1.6e-72:
		tmp = j * t_5
	elif y <= -3.9e-160:
		tmp = j * t_4
	elif y <= -1.5e-293:
		tmp = t_6
	elif y <= 3e-274:
		tmp = t_2
	elif y <= 1.3e-137:
		tmp = t_7
	elif y <= 1.25e-24:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif y <= 9.6:
		tmp = t_6
	elif y <= 1.52e+88:
		tmp = t_2
	elif y <= 1.8e+164:
		tmp = t_7
	else:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(Float64(x * y) - Float64(z * t)))
	t_2 = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(t_1 + Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))))
	t_3 = Float64(Float64(i * y1) - Float64(b * y0))
	t_4 = Float64(x * t_3)
	t_5 = Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))
	t_6 = Float64(j * Float64(Float64(t_5 + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + t_4))
	t_7 = Float64(j * Float64(Float64(Float64(y1 * Float64(x * i)) - Float64(y4 * Float64(y1 * y3))) - Float64(t * Float64(Float64(i * y5) - Float64(b * y4)))))
	tmp = 0.0
	if (y <= -2.5e+113)
		tmp = Float64(x * Float64(Float64(Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))) + Float64(y * Float64(Float64(a * b) - Float64(c * i)))) + Float64(j * t_3)));
	elseif (y <= -6e+25)
		tmp = Float64(a * t_1);
	elseif (y <= -4.3e-60)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (y <= -1.6e-72)
		tmp = Float64(j * t_5);
	elseif (y <= -3.9e-160)
		tmp = Float64(j * t_4);
	elseif (y <= -1.5e-293)
		tmp = t_6;
	elseif (y <= 3e-274)
		tmp = t_2;
	elseif (y <= 1.3e-137)
		tmp = t_7;
	elseif (y <= 1.25e-24)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y <= 9.6)
		tmp = t_6;
	elseif (y <= 1.52e+88)
		tmp = t_2;
	elseif (y <= 1.8e+164)
		tmp = t_7;
	else
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(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)
	t_1 = b * ((x * y) - (z * t));
	t_2 = a * ((y5 * ((t * y2) - (y * y3))) + (t_1 + (y1 * ((z * y3) - (x * y2)))));
	t_3 = (i * y1) - (b * y0);
	t_4 = x * t_3;
	t_5 = t * ((b * y4) - (i * y5));
	t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_4);
	t_7 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	tmp = 0.0;
	if (y <= -2.5e+113)
		tmp = x * (((y2 * ((c * y0) - (a * y1))) + (y * ((a * b) - (c * i)))) + (j * t_3));
	elseif (y <= -6e+25)
		tmp = a * t_1;
	elseif (y <= -4.3e-60)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	elseif (y <= -1.6e-72)
		tmp = j * t_5;
	elseif (y <= -3.9e-160)
		tmp = j * t_4;
	elseif (y <= -1.5e-293)
		tmp = t_6;
	elseif (y <= 3e-274)
		tmp = t_2;
	elseif (y <= 1.3e-137)
		tmp = t_7;
	elseif (y <= 1.25e-24)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (y <= 9.6)
		tmp = t_6;
	elseif (y <= 1.52e+88)
		tmp = t_2;
	elseif (y <= 1.8e+164)
		tmp = t_7;
	else
		tmp = y4 * (k * ((y1 * y2) - (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_] := Block[{t$95$1 = N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 + N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(x * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(j * N[(N[(t$95$5 + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(j * N[(N[(N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.5e+113], N[(x * N[(N[(N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -6e+25], N[(a * t$95$1), $MachinePrecision], If[LessEqual[y, -4.3e-60], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.6e-72], N[(j * t$95$5), $MachinePrecision], If[LessEqual[y, -3.9e-160], N[(j * t$95$4), $MachinePrecision], If[LessEqual[y, -1.5e-293], t$95$6, If[LessEqual[y, 3e-274], t$95$2, If[LessEqual[y, 1.3e-137], t$95$7, If[LessEqual[y, 1.25e-24], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 9.6], t$95$6, If[LessEqual[y, 1.52e+88], t$95$2, If[LessEqual[y, 1.8e+164], t$95$7, N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y < -2.5e113

   1. Initial program 14.6%

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

   3. Taylor expanded in x around inf 62.5%

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

   if -2.5e113 < y < -6.00000000000000011e25

   1. Initial program 21.7%

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

   3. Taylor expanded in b around inf 65.0%

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

   4. Taylor expanded in a around inf 79.0%

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

   if -6.00000000000000011e25 < y < -4.3000000000000001e-60

   1. Initial program 47.6%

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

   3. Taylor expanded in y1 around inf 44.1%

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

   4. Taylor expanded in a around 0 44.5%

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

      1. associate-*r* 44.5%

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

      2. neg-mul-1 44.5%

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

      3. *-commutative 44.5%

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

   6. Simplified 44.5%

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

   if -4.3000000000000001e-60 < y < -1.6e-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. Add Preprocessing

   3. Taylor expanded in j around inf 33.3%

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

      1. +-commutative 33.3%

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

      2. mul-1-neg 33.3%

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

      3. unsub-neg 33.3%

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

      4. *-commutative 33.3%

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

   5. Simplified 33.3%

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

   6. Taylor expanded in t around inf 100.0%

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

   if -1.6e-72 < y < -3.89999999999999989e-160

   1. Initial program 15.8%

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

   3. Taylor expanded in j around inf 31.9%

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

      1. +-commutative 31.9%

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

      2. mul-1-neg 31.9%

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

      3. unsub-neg 31.9%

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

      4. *-commutative 31.9%

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

   5. Simplified 31.9%

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

   6. Taylor expanded in x around inf 63.4%

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

   if -3.89999999999999989e-160 < y < -1.5000000000000001e-293 or 1.24999999999999995e-24 < y < 9.59999999999999964

   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. Add Preprocessing

   3. Taylor expanded in j around inf 55.2%

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

      1. +-commutative 55.2%

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

      2. mul-1-neg 55.2%

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

      3. unsub-neg 55.2%

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

      4. *-commutative 55.2%

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

   5. Simplified 55.2%

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

   if -1.5000000000000001e-293 < y < 2.99999999999999977e-274 or 9.59999999999999964 < y < 1.52000000000000004e88

   1. Initial program 44.1%

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

   3. Taylor expanded in a around -inf 68.3%

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

      1. mul-1-neg 68.3%

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

      2. *-commutative 68.3%

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

      3. distribute-rgt-neg-in 68.3%

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

   5. Simplified 68.3%

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

   if 2.99999999999999977e-274 < y < 1.3e-137 or 1.52000000000000004e88 < y < 1.79999999999999995e164

   1. Initial program 30.6%

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

   3. Taylor expanded in j around inf 51.9%

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

      1. +-commutative 51.9%

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

      2. mul-1-neg 51.9%

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

      3. unsub-neg 51.9%

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

      4. *-commutative 51.9%

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

   5. Simplified 51.9%

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

   6. Taylor expanded in y0 around 0 58.8%

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

      1. +-commutative 58.8%

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

      2. mul-1-neg 58.8%

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

      3. unsub-neg 58.8%

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

      4. associate-*r* 61.1%

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

      5. associate-*r* 63.5%

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

   8. Simplified 63.5%

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

   if 1.3e-137 < y < 1.24999999999999995e-24

   1. Initial program 27.7%

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

   3. Taylor expanded in y2 around inf 46.3%

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

   4. Taylor expanded in t around inf 55.7%

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

   if 1.79999999999999995e164 < y

   1. Initial program 13.0%

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

   3. Taylor expanded in y4 around inf 31.3%

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

   4. Taylor expanded in k around inf 61.3%

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

      1. +-commutative 61.3%

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

      2. mul-1-neg 61.3%

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

      3. unsub-neg 61.3%

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

   6. Simplified 61.3%

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

4. Final simplification 61.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.5 \cdot 10^{+113}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -6 \cdot 10^{+25}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -4.3 \cdot 10^{-60}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -1.6 \cdot 10^{-72}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -3.9 \cdot 10^{-160}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{-293}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-274}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;y \leq 1.3 \cdot 10^{-137}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.25 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 9.6:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 1.52 \cdot 10^{+88}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{+164}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 33.9% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot y5 - c \cdot y4\\ t_2 := i \cdot y1 - b \cdot y0\\ t_3 := x \cdot t\_2\\ t_4 := c \cdot y0 - a \cdot y1\\ t_5 := t \cdot \left(b \cdot y4 - i \cdot y5\right)\\ t_6 := j \cdot \left(\left(t\_5 + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + t\_3\right)\\ \mathbf{if}\;y \leq -6.6 \cdot 10^{+113}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot t\_4 + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot t\_2\right)\\ \mathbf{elif}\;y \leq -9 \cdot 10^{+40}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -5 \cdot 10^{-60}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -1.15 \cdot 10^{-74}:\\ \;\;\;\;j \cdot t\_5\\ \mathbf{elif}\;y \leq -9 \cdot 10^{-160}:\\ \;\;\;\;j \cdot t\_3\\ \mathbf{elif}\;y \leq -8.5 \cdot 10^{-252}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;y \leq 8.5 \cdot 10^{-281}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot t\_4\right) + t \cdot t\_1\right)\\ \mathbf{elif}\;y \leq 3.7 \cdot 10^{-138}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 2.65 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot t\_1\right)\\ \mathbf{elif}\;y \leq 2.3:\\ \;\;\;\;t\_6\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a y5) (* c y4)))
        (t_2 (- (* i y1) (* b y0)))
        (t_3 (* x t_2))
        (t_4 (- (* c y0) (* a y1)))
        (t_5 (* t (- (* b y4) (* i y5))))
        (t_6 (* j (+ (+ t_5 (* y3 (- (* y0 y5) (* y1 y4)))) t_3))))
   (if (<= y -6.6e+113)
     (* x (+ (+ (* y2 t_4) (* y (- (* a b) (* c i)))) (* j t_2)))
     (if (<= y -9e+40)
       (* a (* b (- (* x y) (* z t))))
       (if (<= y -5e-60)
         (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i (- (* z k) (* x j)))))
         (if (<= y -1.15e-74)
           (* j t_5)
           (if (<= y -9e-160)
             (* j t_3)
             (if (<= y -8.5e-252)
               t_6
               (if (<= y 8.5e-281)
                 (*
                  y2
                  (+ (+ (* k (- (* y1 y4) (* y0 y5))) (* x t_4)) (* t t_1)))
                 (if (<= y 3.7e-138)
                   (*
                    j
                    (-
                     (- (* y1 (* x i)) (* y4 (* y1 y3)))
                     (* t (- (* i y5) (* b y4)))))
                   (if (<= y 2.65e-24)
                     (* t (* y2 t_1))
                     (if (<= y 2.3)
                       t_6
                       (* y4 (* k (- (* y1 y2) (* 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 t_1 = (a * y5) - (c * y4);
	double t_2 = (i * y1) - (b * y0);
	double t_3 = x * t_2;
	double t_4 = (c * y0) - (a * y1);
	double t_5 = t * ((b * y4) - (i * y5));
	double t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_3);
	double tmp;
	if (y <= -6.6e+113) {
		tmp = x * (((y2 * t_4) + (y * ((a * b) - (c * i)))) + (j * t_2));
	} else if (y <= -9e+40) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= -5e-60) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -1.15e-74) {
		tmp = j * t_5;
	} else if (y <= -9e-160) {
		tmp = j * t_3;
	} else if (y <= -8.5e-252) {
		tmp = t_6;
	} else if (y <= 8.5e-281) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_4)) + (t * t_1));
	} else if (y <= 3.7e-138) {
		tmp = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	} else if (y <= 2.65e-24) {
		tmp = t * (y2 * t_1);
	} else if (y <= 2.3) {
		tmp = t_6;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (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) :: 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 * y5) - (c * y4)
    t_2 = (i * y1) - (b * y0)
    t_3 = x * t_2
    t_4 = (c * y0) - (a * y1)
    t_5 = t * ((b * y4) - (i * y5))
    t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_3)
    if (y <= (-6.6d+113)) then
        tmp = x * (((y2 * t_4) + (y * ((a * b) - (c * i)))) + (j * t_2))
    else if (y <= (-9d+40)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y <= (-5d-60)) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
    else if (y <= (-1.15d-74)) then
        tmp = j * t_5
    else if (y <= (-9d-160)) then
        tmp = j * t_3
    else if (y <= (-8.5d-252)) then
        tmp = t_6
    else if (y <= 8.5d-281) then
        tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_4)) + (t * t_1))
    else if (y <= 3.7d-138) then
        tmp = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
    else if (y <= 2.65d-24) then
        tmp = t * (y2 * t_1)
    else if (y <= 2.3d0) then
        tmp = t_6
    else
        tmp = y4 * (k * ((y1 * y2) - (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 t_1 = (a * y5) - (c * y4);
	double t_2 = (i * y1) - (b * y0);
	double t_3 = x * t_2;
	double t_4 = (c * y0) - (a * y1);
	double t_5 = t * ((b * y4) - (i * y5));
	double t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_3);
	double tmp;
	if (y <= -6.6e+113) {
		tmp = x * (((y2 * t_4) + (y * ((a * b) - (c * i)))) + (j * t_2));
	} else if (y <= -9e+40) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= -5e-60) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -1.15e-74) {
		tmp = j * t_5;
	} else if (y <= -9e-160) {
		tmp = j * t_3;
	} else if (y <= -8.5e-252) {
		tmp = t_6;
	} else if (y <= 8.5e-281) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_4)) + (t * t_1));
	} else if (y <= 3.7e-138) {
		tmp = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	} else if (y <= 2.65e-24) {
		tmp = t * (y2 * t_1);
	} else if (y <= 2.3) {
		tmp = t_6;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (a * y5) - (c * y4)
	t_2 = (i * y1) - (b * y0)
	t_3 = x * t_2
	t_4 = (c * y0) - (a * y1)
	t_5 = t * ((b * y4) - (i * y5))
	t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_3)
	tmp = 0
	if y <= -6.6e+113:
		tmp = x * (((y2 * t_4) + (y * ((a * b) - (c * i)))) + (j * t_2))
	elif y <= -9e+40:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y <= -5e-60:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
	elif y <= -1.15e-74:
		tmp = j * t_5
	elif y <= -9e-160:
		tmp = j * t_3
	elif y <= -8.5e-252:
		tmp = t_6
	elif y <= 8.5e-281:
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_4)) + (t * t_1))
	elif y <= 3.7e-138:
		tmp = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
	elif y <= 2.65e-24:
		tmp = t * (y2 * t_1)
	elif y <= 2.3:
		tmp = t_6
	else:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(a * y5) - Float64(c * y4))
	t_2 = Float64(Float64(i * y1) - Float64(b * y0))
	t_3 = Float64(x * t_2)
	t_4 = Float64(Float64(c * y0) - Float64(a * y1))
	t_5 = Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))
	t_6 = Float64(j * Float64(Float64(t_5 + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + t_3))
	tmp = 0.0
	if (y <= -6.6e+113)
		tmp = Float64(x * Float64(Float64(Float64(y2 * t_4) + Float64(y * Float64(Float64(a * b) - Float64(c * i)))) + Float64(j * t_2)));
	elseif (y <= -9e+40)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y <= -5e-60)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (y <= -1.15e-74)
		tmp = Float64(j * t_5);
	elseif (y <= -9e-160)
		tmp = Float64(j * t_3);
	elseif (y <= -8.5e-252)
		tmp = t_6;
	elseif (y <= 8.5e-281)
		tmp = Float64(y2 * Float64(Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(x * t_4)) + Float64(t * t_1)));
	elseif (y <= 3.7e-138)
		tmp = Float64(j * Float64(Float64(Float64(y1 * Float64(x * i)) - Float64(y4 * Float64(y1 * y3))) - Float64(t * Float64(Float64(i * y5) - Float64(b * y4)))));
	elseif (y <= 2.65e-24)
		tmp = Float64(t * Float64(y2 * t_1));
	elseif (y <= 2.3)
		tmp = t_6;
	else
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(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)
	t_1 = (a * y5) - (c * y4);
	t_2 = (i * y1) - (b * y0);
	t_3 = x * t_2;
	t_4 = (c * y0) - (a * y1);
	t_5 = t * ((b * y4) - (i * y5));
	t_6 = j * ((t_5 + (y3 * ((y0 * y5) - (y1 * y4)))) + t_3);
	tmp = 0.0;
	if (y <= -6.6e+113)
		tmp = x * (((y2 * t_4) + (y * ((a * b) - (c * i)))) + (j * t_2));
	elseif (y <= -9e+40)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y <= -5e-60)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	elseif (y <= -1.15e-74)
		tmp = j * t_5;
	elseif (y <= -9e-160)
		tmp = j * t_3;
	elseif (y <= -8.5e-252)
		tmp = t_6;
	elseif (y <= 8.5e-281)
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_4)) + (t * t_1));
	elseif (y <= 3.7e-138)
		tmp = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	elseif (y <= 2.65e-24)
		tmp = t * (y2 * t_1);
	elseif (y <= 2.3)
		tmp = t_6;
	else
		tmp = y4 * (k * ((y1 * y2) - (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_] := Block[{t$95$1 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(j * N[(N[(t$95$5 + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -6.6e+113], N[(x * N[(N[(N[(y2 * t$95$4), $MachinePrecision] + N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -9e+40], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -5e-60], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.15e-74], N[(j * t$95$5), $MachinePrecision], If[LessEqual[y, -9e-160], N[(j * t$95$3), $MachinePrecision], If[LessEqual[y, -8.5e-252], t$95$6, If[LessEqual[y, 8.5e-281], N[(y2 * N[(N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3.7e-138], N[(j * N[(N[(N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.65e-24], N[(t * N[(y2 * t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.3], t$95$6, N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y < -6.6000000000000006e113

   1. Initial program 14.6%

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

   3. Taylor expanded in x around inf 62.5%

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

   if -6.6000000000000006e113 < y < -9.00000000000000064e40

   1. Initial program 21.7%

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

   3. Taylor expanded in b around inf 65.0%

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

   4. Taylor expanded in a around inf 79.0%

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

   if -9.00000000000000064e40 < y < -5.0000000000000001e-60

   1. Initial program 47.6%

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

   3. Taylor expanded in y1 around inf 44.1%

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

   4. Taylor expanded in a around 0 44.5%

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

      1. associate-*r* 44.5%

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

      2. neg-mul-1 44.5%

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

      3. *-commutative 44.5%

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

   6. Simplified 44.5%

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

   if -5.0000000000000001e-60 < y < -1.1499999999999999e-74

   1. Initial program 33.3%

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

   3. Taylor expanded in j around inf 33.3%

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

      1. +-commutative 33.3%

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

      2. mul-1-neg 33.3%

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

      3. unsub-neg 33.3%

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

      4. *-commutative 33.3%

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

   5. Simplified 33.3%

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

   6. Taylor expanded in t around inf 100.0%

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

   if -1.1499999999999999e-74 < y < -9.00000000000000053e-160

   1. Initial program 15.8%

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

   3. Taylor expanded in j around inf 31.9%

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

      1. +-commutative 31.9%

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

      2. mul-1-neg 31.9%

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

      3. unsub-neg 31.9%

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

      4. *-commutative 31.9%

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

   5. Simplified 31.9%

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

   6. Taylor expanded in x around inf 63.4%

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

   if -9.00000000000000053e-160 < y < -8.50000000000000042e-252 or 2.64999999999999984e-24 < y < 2.2999999999999998

   1. Initial program 37.7%

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

   3. Taylor expanded in j around inf 60.1%

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

      1. +-commutative 60.1%

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

      2. mul-1-neg 60.1%

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

      3. unsub-neg 60.1%

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

      4. *-commutative 60.1%

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

   5. Simplified 60.1%

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

   if -8.50000000000000042e-252 < y < 8.4999999999999994e-281

   1. Initial program 27.8%

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

   3. Taylor expanded in y2 around inf 56.3%

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

   if 8.4999999999999994e-281 < y < 3.69999999999999991e-138

   1. Initial program 42.4%

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

   3. Taylor expanded in j around inf 52.5%

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

      1. +-commutative 52.5%

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

      2. mul-1-neg 52.5%

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

      3. unsub-neg 52.5%

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

      4. *-commutative 52.5%

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

   5. Simplified 52.5%

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

   6. Taylor expanded in y0 around 0 58.8%

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

      1. +-commutative 58.8%

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

      2. mul-1-neg 58.8%

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

      3. unsub-neg 58.8%

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

      4. associate-*r* 58.8%

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

      5. associate-*r* 58.9%

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

   8. Simplified 58.9%

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

   if 3.69999999999999991e-138 < y < 2.64999999999999984e-24

   1. Initial program 27.7%

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

   3. Taylor expanded in y2 around inf 46.3%

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

   4. Taylor expanded in t around inf 55.7%

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

   if 2.2999999999999998 < y

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.0%

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

   4. Taylor expanded in k around inf 53.3%

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

      1. +-commutative 53.3%

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

      2. mul-1-neg 53.3%

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

      3. unsub-neg 53.3%

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

   6. Simplified 53.3%

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

4. Final simplification 58.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -6.6 \cdot 10^{+113}:\\ \;\;\;\;x \cdot \left(\left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right) + y \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -9 \cdot 10^{+40}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -5 \cdot 10^{-60}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -1.15 \cdot 10^{-74}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -9 \cdot 10^{-160}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -8.5 \cdot 10^{-252}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 8.5 \cdot 10^{-281}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 3.7 \cdot 10^{-138}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 2.65 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 2.3:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 37.8% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \left(b \cdot y4 - i \cdot y5\right)\\ t_2 := y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ t_3 := c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ t_4 := x \cdot y - z \cdot t\\ t_5 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot t\_4 + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{if}\;t \leq -9.5 \cdot 10^{+177}:\\ \;\;\;\;j \cdot t\_1\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-61}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;t \leq -2 \cdot 10^{-124}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{-234}:\\ \;\;\;\;j \cdot t\_2\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-258}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{-257}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;t \leq 9.8 \cdot 10^{-49}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot t\_4 + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{+15} \lor \neg \left(t \leq 8 \cdot 10^{+131}\right):\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(t\_1 + t\_2\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* t (- (* b y4) (* i y5))))
        (t_2 (* y3 (- (* y0 y5) (* y1 y4))))
        (t_3
         (*
          c
          (+
           (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
           (* y4 (- (* y y3) (* t y2))))))
        (t_4 (- (* x y) (* z t)))
        (t_5
         (*
          a
          (+
           (* y5 (- (* t y2) (* y y3)))
           (+ (* b t_4) (* y1 (- (* z y3) (* x y2))))))))
   (if (<= t -9.5e+177)
     (* j t_1)
     (if (<= t -5.2e-61)
       t_5
       (if (<= t -2e-124)
         t_3
         (if (<= t -3.5e-234)
           (* j t_2)
           (if (<= t -4.8e-258)
             t_3
             (if (<= t 1.7e-257)
               t_5
               (if (<= t 9.8e-49)
                 (*
                  i
                  (-
                   (* y1 (- (* x j) (* z k)))
                   (+ (* c t_4) (* y5 (- (* t j) (* y k))))))
                 (if (or (<= t 1.05e+15) (not (<= t 8e+131)))
                   (*
                    y2
                    (+
                     (+
                      (* k (- (* y1 y4) (* y0 y5)))
                      (* x (- (* c y0) (* a y1))))
                     (* t (- (* a y5) (* c y4)))))
                   (* j (+ (+ t_1 t_2) (* x (- (* 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 = t * ((b * y4) - (i * y5));
	double t_2 = y3 * ((y0 * y5) - (y1 * y4));
	double t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	double t_4 = (x * y) - (z * t);
	double t_5 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_4) + (y1 * ((z * y3) - (x * y2)))));
	double tmp;
	if (t <= -9.5e+177) {
		tmp = j * t_1;
	} else if (t <= -5.2e-61) {
		tmp = t_5;
	} else if (t <= -2e-124) {
		tmp = t_3;
	} else if (t <= -3.5e-234) {
		tmp = j * t_2;
	} else if (t <= -4.8e-258) {
		tmp = t_3;
	} else if (t <= 1.7e-257) {
		tmp = t_5;
	} else if (t <= 9.8e-49) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_4) + (y5 * ((t * j) - (y * k)))));
	} else if ((t <= 1.05e+15) || !(t <= 8e+131)) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else {
		tmp = j * ((t_1 + t_2) + (x * ((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) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: tmp
    t_1 = t * ((b * y4) - (i * y5))
    t_2 = y3 * ((y0 * y5) - (y1 * y4))
    t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
    t_4 = (x * y) - (z * t)
    t_5 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_4) + (y1 * ((z * y3) - (x * y2)))))
    if (t <= (-9.5d+177)) then
        tmp = j * t_1
    else if (t <= (-5.2d-61)) then
        tmp = t_5
    else if (t <= (-2d-124)) then
        tmp = t_3
    else if (t <= (-3.5d-234)) then
        tmp = j * t_2
    else if (t <= (-4.8d-258)) then
        tmp = t_3
    else if (t <= 1.7d-257) then
        tmp = t_5
    else if (t <= 9.8d-49) then
        tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_4) + (y5 * ((t * j) - (y * k)))))
    else if ((t <= 1.05d+15) .or. (.not. (t <= 8d+131))) then
        tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else
        tmp = j * ((t_1 + t_2) + (x * ((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 = t * ((b * y4) - (i * y5));
	double t_2 = y3 * ((y0 * y5) - (y1 * y4));
	double t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	double t_4 = (x * y) - (z * t);
	double t_5 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_4) + (y1 * ((z * y3) - (x * y2)))));
	double tmp;
	if (t <= -9.5e+177) {
		tmp = j * t_1;
	} else if (t <= -5.2e-61) {
		tmp = t_5;
	} else if (t <= -2e-124) {
		tmp = t_3;
	} else if (t <= -3.5e-234) {
		tmp = j * t_2;
	} else if (t <= -4.8e-258) {
		tmp = t_3;
	} else if (t <= 1.7e-257) {
		tmp = t_5;
	} else if (t <= 9.8e-49) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_4) + (y5 * ((t * j) - (y * k)))));
	} else if ((t <= 1.05e+15) || !(t <= 8e+131)) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else {
		tmp = j * ((t_1 + t_2) + (x * ((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 = t * ((b * y4) - (i * y5))
	t_2 = y3 * ((y0 * y5) - (y1 * y4))
	t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
	t_4 = (x * y) - (z * t)
	t_5 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_4) + (y1 * ((z * y3) - (x * y2)))))
	tmp = 0
	if t <= -9.5e+177:
		tmp = j * t_1
	elif t <= -5.2e-61:
		tmp = t_5
	elif t <= -2e-124:
		tmp = t_3
	elif t <= -3.5e-234:
		tmp = j * t_2
	elif t <= -4.8e-258:
		tmp = t_3
	elif t <= 1.7e-257:
		tmp = t_5
	elif t <= 9.8e-49:
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_4) + (y5 * ((t * j) - (y * k)))))
	elif (t <= 1.05e+15) or not (t <= 8e+131):
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	else:
		tmp = j * ((t_1 + t_2) + (x * ((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(t * Float64(Float64(b * y4) - Float64(i * y5)))
	t_2 = Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))
	t_3 = Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))))
	t_4 = Float64(Float64(x * y) - Float64(z * t))
	t_5 = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(b * t_4) + Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))))
	tmp = 0.0
	if (t <= -9.5e+177)
		tmp = Float64(j * t_1);
	elseif (t <= -5.2e-61)
		tmp = t_5;
	elseif (t <= -2e-124)
		tmp = t_3;
	elseif (t <= -3.5e-234)
		tmp = Float64(j * t_2);
	elseif (t <= -4.8e-258)
		tmp = t_3;
	elseif (t <= 1.7e-257)
		tmp = t_5;
	elseif (t <= 9.8e-49)
		tmp = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) - Float64(Float64(c * t_4) + Float64(y5 * Float64(Float64(t * j) - Float64(y * k))))));
	elseif ((t <= 1.05e+15) || !(t <= 8e+131))
		tmp = Float64(y2 * Float64(Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	else
		tmp = Float64(j * Float64(Float64(t_1 + t_2) + Float64(x * 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 = t * ((b * y4) - (i * y5));
	t_2 = y3 * ((y0 * y5) - (y1 * y4));
	t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	t_4 = (x * y) - (z * t);
	t_5 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_4) + (y1 * ((z * y3) - (x * y2)))));
	tmp = 0.0;
	if (t <= -9.5e+177)
		tmp = j * t_1;
	elseif (t <= -5.2e-61)
		tmp = t_5;
	elseif (t <= -2e-124)
		tmp = t_3;
	elseif (t <= -3.5e-234)
		tmp = j * t_2;
	elseif (t <= -4.8e-258)
		tmp = t_3;
	elseif (t <= 1.7e-257)
		tmp = t_5;
	elseif (t <= 9.8e-49)
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_4) + (y5 * ((t * j) - (y * k)))));
	elseif ((t <= 1.05e+15) || ~((t <= 8e+131)))
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	else
		tmp = j * ((t_1 + t_2) + (x * ((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[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(b * t$95$4), $MachinePrecision] + N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -9.5e+177], N[(j * t$95$1), $MachinePrecision], If[LessEqual[t, -5.2e-61], t$95$5, If[LessEqual[t, -2e-124], t$95$3, If[LessEqual[t, -3.5e-234], N[(j * t$95$2), $MachinePrecision], If[LessEqual[t, -4.8e-258], t$95$3, If[LessEqual[t, 1.7e-257], t$95$5, If[LessEqual[t, 9.8e-49], N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(c * t$95$4), $MachinePrecision] + N[(y5 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[t, 1.05e+15], N[Not[LessEqual[t, 8e+131]], $MachinePrecision]], N[(y2 * N[(N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(N[(t$95$1 + t$95$2), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -9.49999999999999996e177

   1. Initial program 17.7%

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

   3. Taylor expanded in j around inf 43.8%

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

      1. +-commutative 43.8%

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

      2. mul-1-neg 43.8%

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

      3. unsub-neg 43.8%

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

      4. *-commutative 43.8%

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

   5. Simplified 43.8%

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

   6. Taylor expanded in t around inf 53.2%

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

   if -9.49999999999999996e177 < t < -5.20000000000000021e-61 or -4.8000000000000003e-258 < t < 1.6999999999999999e-257

   1. Initial program 34.9%

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

   3. Taylor expanded in a around -inf 59.9%

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

      1. mul-1-neg 59.9%

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

      2. *-commutative 59.9%

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

      3. distribute-rgt-neg-in 59.9%

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

   5. Simplified 59.9%

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

   if -5.20000000000000021e-61 < t < -1.99999999999999987e-124 or -3.5000000000000001e-234 < t < -4.8000000000000003e-258

   1. Initial program 38.1%

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

   3. Taylor expanded in c around inf 57.6%

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

      1. +-commutative 57.6%

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

      2. mul-1-neg 57.6%

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

      3. unsub-neg 57.6%

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

      4. *-commutative 57.6%

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

      5. *-commutative 57.6%

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

      6. *-commutative 57.6%

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

      7. *-commutative 57.6%

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

   5. Simplified 57.6%

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

   if -1.99999999999999987e-124 < t < -3.5000000000000001e-234

   1. Initial program 13.0%

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

   3. Taylor expanded in j around inf 44.2%

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

      1. +-commutative 44.2%

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

      2. mul-1-neg 44.2%

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

      3. unsub-neg 44.2%

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

      4. *-commutative 44.2%

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

   5. Simplified 44.2%

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

   6. Taylor expanded in y3 around inf 57.6%

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

      1. *-commutative 57.6%

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

      2. *-commutative 57.6%

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

   8. Simplified 57.6%

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

   if 1.6999999999999999e-257 < t < 9.8000000000000005e-49

   1. Initial program 34.4%

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

   3. Taylor expanded in i around -inf 64.4%

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

   if 9.8000000000000005e-49 < t < 1.05e15 or 7.9999999999999993e131 < t

   1. Initial program 21.2%

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

   3. Taylor expanded in y2 around inf 77.2%

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

   if 1.05e15 < t < 7.9999999999999993e131

   1. Initial program 25.8%

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

   3. Taylor expanded in j around inf 55.6%

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

      1. +-commutative 55.6%

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

      2. mul-1-neg 55.6%

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

      3. unsub-neg 55.6%

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

      4. *-commutative 55.6%

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

   5. Simplified 55.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 62.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -9.5 \cdot 10^{+177}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-61}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -2 \cdot 10^{-124}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{-234}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-258}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{-257}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq 9.8 \cdot 10^{-49}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot \left(x \cdot y - z \cdot t\right) + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{+15} \lor \neg \left(t \leq 8 \cdot 10^{+131}\right):\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 39.8% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y4 - i \cdot y5\\ t_2 := y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ t_3 := c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ t_4 := a \cdot y5 - c \cdot y4\\ t_5 := x \cdot y - z \cdot t\\ t_6 := a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot t\_5 + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{if}\;t \leq -1.08 \cdot 10^{+154}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot t\_1\right) + y2 \cdot t\_4\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-62}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-128}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-234}:\\ \;\;\;\;j \cdot t\_2\\ \mathbf{elif}\;t \leq -1.2 \cdot 10^{-258}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-257}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;t \leq 5.6 \cdot 10^{-49}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) - \left(c \cdot t\_5 + y5 \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{+15} \lor \neg \left(t \leq 8.2 \cdot 10^{+130}\right):\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot t\_4\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(t \cdot t\_1 + t\_2\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y4) (* i y5)))
        (t_2 (* y3 (- (* y0 y5) (* y1 y4))))
        (t_3
         (*
          c
          (+
           (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
           (* y4 (- (* y y3) (* t y2))))))
        (t_4 (- (* a y5) (* c y4)))
        (t_5 (- (* x y) (* z t)))
        (t_6
         (*
          a
          (+
           (* y5 (- (* t y2) (* y y3)))
           (+ (* b t_5) (* y1 (- (* z y3) (* x y2))))))))
   (if (<= t -1.08e+154)
     (* t (+ (+ (* z (- (* c i) (* a b))) (* j t_1)) (* y2 t_4)))
     (if (<= t -3.2e-62)
       t_6
       (if (<= t -2.5e-128)
         t_3
         (if (<= t -4.8e-234)
           (* j t_2)
           (if (<= t -1.2e-258)
             t_3
             (if (<= t 1.8e-257)
               t_6
               (if (<= t 5.6e-49)
                 (*
                  i
                  (-
                   (* y1 (- (* x j) (* z k)))
                   (+ (* c t_5) (* y5 (- (* t j) (* y k))))))
                 (if (or (<= t 1.4e+15) (not (<= t 8.2e+130)))
                   (*
                    y2
                    (+
                     (+
                      (* k (- (* y1 y4) (* y0 y5)))
                      (* x (- (* c y0) (* a y1))))
                     (* t t_4)))
                   (*
                    j
                    (+
                     (+ (* t t_1) t_2)
                     (* x (- (* 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 = (b * y4) - (i * y5);
	double t_2 = y3 * ((y0 * y5) - (y1 * y4));
	double t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	double t_4 = (a * y5) - (c * y4);
	double t_5 = (x * y) - (z * t);
	double t_6 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_5) + (y1 * ((z * y3) - (x * y2)))));
	double tmp;
	if (t <= -1.08e+154) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * t_4));
	} else if (t <= -3.2e-62) {
		tmp = t_6;
	} else if (t <= -2.5e-128) {
		tmp = t_3;
	} else if (t <= -4.8e-234) {
		tmp = j * t_2;
	} else if (t <= -1.2e-258) {
		tmp = t_3;
	} else if (t <= 1.8e-257) {
		tmp = t_6;
	} else if (t <= 5.6e-49) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_5) + (y5 * ((t * j) - (y * k)))));
	} else if ((t <= 1.4e+15) || !(t <= 8.2e+130)) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * t_4));
	} else {
		tmp = j * (((t * t_1) + t_2) + (x * ((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) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = (b * y4) - (i * y5)
    t_2 = y3 * ((y0 * y5) - (y1 * y4))
    t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
    t_4 = (a * y5) - (c * y4)
    t_5 = (x * y) - (z * t)
    t_6 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_5) + (y1 * ((z * y3) - (x * y2)))))
    if (t <= (-1.08d+154)) then
        tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * t_4))
    else if (t <= (-3.2d-62)) then
        tmp = t_6
    else if (t <= (-2.5d-128)) then
        tmp = t_3
    else if (t <= (-4.8d-234)) then
        tmp = j * t_2
    else if (t <= (-1.2d-258)) then
        tmp = t_3
    else if (t <= 1.8d-257) then
        tmp = t_6
    else if (t <= 5.6d-49) then
        tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_5) + (y5 * ((t * j) - (y * k)))))
    else if ((t <= 1.4d+15) .or. (.not. (t <= 8.2d+130))) then
        tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * t_4))
    else
        tmp = j * (((t * t_1) + t_2) + (x * ((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 = (b * y4) - (i * y5);
	double t_2 = y3 * ((y0 * y5) - (y1 * y4));
	double t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	double t_4 = (a * y5) - (c * y4);
	double t_5 = (x * y) - (z * t);
	double t_6 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_5) + (y1 * ((z * y3) - (x * y2)))));
	double tmp;
	if (t <= -1.08e+154) {
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * t_4));
	} else if (t <= -3.2e-62) {
		tmp = t_6;
	} else if (t <= -2.5e-128) {
		tmp = t_3;
	} else if (t <= -4.8e-234) {
		tmp = j * t_2;
	} else if (t <= -1.2e-258) {
		tmp = t_3;
	} else if (t <= 1.8e-257) {
		tmp = t_6;
	} else if (t <= 5.6e-49) {
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_5) + (y5 * ((t * j) - (y * k)))));
	} else if ((t <= 1.4e+15) || !(t <= 8.2e+130)) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * t_4));
	} else {
		tmp = j * (((t * t_1) + t_2) + (x * ((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 = (b * y4) - (i * y5)
	t_2 = y3 * ((y0 * y5) - (y1 * y4))
	t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
	t_4 = (a * y5) - (c * y4)
	t_5 = (x * y) - (z * t)
	t_6 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_5) + (y1 * ((z * y3) - (x * y2)))))
	tmp = 0
	if t <= -1.08e+154:
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * t_4))
	elif t <= -3.2e-62:
		tmp = t_6
	elif t <= -2.5e-128:
		tmp = t_3
	elif t <= -4.8e-234:
		tmp = j * t_2
	elif t <= -1.2e-258:
		tmp = t_3
	elif t <= 1.8e-257:
		tmp = t_6
	elif t <= 5.6e-49:
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_5) + (y5 * ((t * j) - (y * k)))))
	elif (t <= 1.4e+15) or not (t <= 8.2e+130):
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * t_4))
	else:
		tmp = j * (((t * t_1) + t_2) + (x * ((i * y1) - (b * y0))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(b * y4) - Float64(i * y5))
	t_2 = Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))
	t_3 = Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))))
	t_4 = Float64(Float64(a * y5) - Float64(c * y4))
	t_5 = Float64(Float64(x * y) - Float64(z * t))
	t_6 = Float64(a * Float64(Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(b * t_5) + Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))))))
	tmp = 0.0
	if (t <= -1.08e+154)
		tmp = Float64(t * Float64(Float64(Float64(z * Float64(Float64(c * i) - Float64(a * b))) + Float64(j * t_1)) + Float64(y2 * t_4)));
	elseif (t <= -3.2e-62)
		tmp = t_6;
	elseif (t <= -2.5e-128)
		tmp = t_3;
	elseif (t <= -4.8e-234)
		tmp = Float64(j * t_2);
	elseif (t <= -1.2e-258)
		tmp = t_3;
	elseif (t <= 1.8e-257)
		tmp = t_6;
	elseif (t <= 5.6e-49)
		tmp = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) - Float64(Float64(c * t_5) + Float64(y5 * Float64(Float64(t * j) - Float64(y * k))))));
	elseif ((t <= 1.4e+15) || !(t <= 8.2e+130))
		tmp = Float64(y2 * Float64(Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * t_4)));
	else
		tmp = Float64(j * Float64(Float64(Float64(t * t_1) + t_2) + Float64(x * 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 = (b * y4) - (i * y5);
	t_2 = y3 * ((y0 * y5) - (y1 * y4));
	t_3 = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	t_4 = (a * y5) - (c * y4);
	t_5 = (x * y) - (z * t);
	t_6 = a * ((y5 * ((t * y2) - (y * y3))) + ((b * t_5) + (y1 * ((z * y3) - (x * y2)))));
	tmp = 0.0;
	if (t <= -1.08e+154)
		tmp = t * (((z * ((c * i) - (a * b))) + (j * t_1)) + (y2 * t_4));
	elseif (t <= -3.2e-62)
		tmp = t_6;
	elseif (t <= -2.5e-128)
		tmp = t_3;
	elseif (t <= -4.8e-234)
		tmp = j * t_2;
	elseif (t <= -1.2e-258)
		tmp = t_3;
	elseif (t <= 1.8e-257)
		tmp = t_6;
	elseif (t <= 5.6e-49)
		tmp = i * ((y1 * ((x * j) - (z * k))) - ((c * t_5) + (y5 * ((t * j) - (y * k)))));
	elseif ((t <= 1.4e+15) || ~((t <= 8.2e+130)))
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * t_4));
	else
		tmp = j * (((t * t_1) + t_2) + (x * ((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[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(a * N[(N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(b * t$95$5), $MachinePrecision] + N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.08e+154], N[(t * N[(N[(N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.2e-62], t$95$6, If[LessEqual[t, -2.5e-128], t$95$3, If[LessEqual[t, -4.8e-234], N[(j * t$95$2), $MachinePrecision], If[LessEqual[t, -1.2e-258], t$95$3, If[LessEqual[t, 1.8e-257], t$95$6, If[LessEqual[t, 5.6e-49], N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(c * t$95$5), $MachinePrecision] + N[(y5 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[t, 1.4e+15], N[Not[LessEqual[t, 8.2e+130]], $MachinePrecision]], N[(y2 * N[(N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(N[(N[(t * t$95$1), $MachinePrecision] + t$95$2), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -1.08e154

   1. Initial program 19.5%

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

   3. Taylor expanded in t around inf 58.4%

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

   if -1.08e154 < t < -3.20000000000000021e-62 or -1.2000000000000001e-258 < t < 1.80000000000000003e-257

   1. Initial program 35.0%

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

   3. Taylor expanded in a around -inf 61.1%

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

      1. mul-1-neg 61.1%

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

      2. *-commutative 61.1%

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

      3. distribute-rgt-neg-in 61.1%

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

   5. Simplified 61.1%

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

   if -3.20000000000000021e-62 < t < -2.5000000000000001e-128 or -4.7999999999999998e-234 < t < -1.2000000000000001e-258

   1. Initial program 38.1%

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

   3. Taylor expanded in c around inf 57.6%

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

      1. +-commutative 57.6%

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

      2. mul-1-neg 57.6%

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

      3. unsub-neg 57.6%

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

      4. *-commutative 57.6%

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

      5. *-commutative 57.6%

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

      6. *-commutative 57.6%

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

      7. *-commutative 57.6%

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

   5. Simplified 57.6%

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

   if -2.5000000000000001e-128 < t < -4.7999999999999998e-234

   1. Initial program 13.0%

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

   3. Taylor expanded in j around inf 44.2%

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

      1. +-commutative 44.2%

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

      2. mul-1-neg 44.2%

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

      3. unsub-neg 44.2%

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

      4. *-commutative 44.2%

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

   5. Simplified 44.2%

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

   6. Taylor expanded in y3 around inf 57.6%

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

      1. *-commutative 57.6%

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

      2. *-commutative 57.6%

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

   8. Simplified 57.6%

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

   if 1.80000000000000003e-257 < t < 5.59999999999999995e-49

   1. Initial program 34.4%

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

   3. Taylor expanded in i around -inf 64.4%

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

   if 5.59999999999999995e-49 < t < 1.4e15 or 8.19999999999999955e130 < t

   1. Initial program 21.2%

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

   3. Taylor expanded in y2 around inf 77.2%

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

   if 1.4e15 < t < 8.19999999999999955e130

   1. Initial program 25.8%

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

   3. Taylor expanded in j around inf 55.6%

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

      1. +-commutative 55.6%

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

      2. mul-1-neg 55.6%

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

      3. unsub-neg 55.6%

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

      4. *-commutative 55.6%

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

   5. Simplified 55.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 63.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.08 \cdot 10^{+154}:\\ \;\;\;\;t \cdot \left(\left(z \cdot \left(c \cdot i - a \cdot b\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-62}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-128}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-234}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -1.2 \cdot 10^{-258}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-257}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(b \cdot \left(x \cdot y - z \cdot t\right) + y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\right)\\ \mathbf{elif}\;t \leq 5.6 \cdot 10^{-49}:\\ \;\;\;\;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}\;t \leq 1.4 \cdot 10^{+15} \lor \neg \left(t \leq 8.2 \cdot 10^{+130}\right):\\ \;\;\;\;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{else}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 33.8% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ t_2 := z \cdot k - x \cdot j\\ \mathbf{if}\;j \leq -2.65 \cdot 10^{+75}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq -2.25 \cdot 10^{-10}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -8.4 \cdot 10^{-45}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.35 \cdot 10^{-111}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -6.8 \cdot 10^{-227}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot t\_2\right)\\ \mathbf{elif}\;j \leq -2.15 \cdot 10^{-288}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-289}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 2.2 \cdot 10^{-145}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 2.05 \cdot 10^{-75}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 2.8 \cdot 10^{+63}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot t\_2\right)\\ \mathbf{elif}\;j \leq 7 \cdot 10^{+213}:\\ \;\;\;\;y3 \cdot \left(y0 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          j
          (- (- (* y1 (* x i)) (* y4 (* y1 y3))) (* t (- (* i y5) (* b y4))))))
        (t_2 (- (* z k) (* x j))))
   (if (<= j -2.65e+75)
     t_1
     (if (<= j -2.25e-10)
       (* y1 (* z (- (* a y3) (* i k))))
       (if (<= j -8.4e-45)
         (* x (* y (- (* a b) (* c i))))
         (if (<= j -1.35e-111)
           (* a (* y1 (- (* z y3) (* x y2))))
           (if (<= j -6.8e-227)
             (*
              b
              (+
               (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
               (* y0 t_2)))
             (if (<= j -2.15e-288)
               t_1
               (if (<= j 1.5e-289)
                 (* c (* y3 (- (* y y4) (* z y0))))
                 (if (<= j 2.2e-145)
                   (* t (* y2 (- (* a y5) (* c y4))))
                   (if (<= j 2.05e-75)
                     (*
                      c
                      (+
                       (+
                        (* y0 (- (* x y2) (* z y3)))
                        (* i (- (* z t) (* x y))))
                       (* y4 (- (* y y3) (* t y2)))))
                     (if (<= j 2.8e+63)
                       (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i t_2)))
                       (if (<= j 7e+213)
                         (* y3 (* y0 (- (* j y5) (* z c))))
                         (* j (* x (- (* 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 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double t_2 = (z * k) - (x * j);
	double tmp;
	if (j <= -2.65e+75) {
		tmp = t_1;
	} else if (j <= -2.25e-10) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -8.4e-45) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -1.35e-111) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (j <= -6.8e-227) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_2));
	} else if (j <= -2.15e-288) {
		tmp = t_1;
	} else if (j <= 1.5e-289) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (j <= 2.2e-145) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 2.05e-75) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 2.8e+63) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_2));
	} else if (j <= 7e+213) {
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	} else {
		tmp = j * (x * ((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 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
    t_2 = (z * k) - (x * j)
    if (j <= (-2.65d+75)) then
        tmp = t_1
    else if (j <= (-2.25d-10)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (j <= (-8.4d-45)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (j <= (-1.35d-111)) then
        tmp = a * (y1 * ((z * y3) - (x * y2)))
    else if (j <= (-6.8d-227)) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_2))
    else if (j <= (-2.15d-288)) then
        tmp = t_1
    else if (j <= 1.5d-289) then
        tmp = c * (y3 * ((y * y4) - (z * y0)))
    else if (j <= 2.2d-145) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (j <= 2.05d-75) then
        tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
    else if (j <= 2.8d+63) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_2))
    else if (j <= 7d+213) then
        tmp = y3 * (y0 * ((j * y5) - (z * c)))
    else
        tmp = j * (x * ((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 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double t_2 = (z * k) - (x * j);
	double tmp;
	if (j <= -2.65e+75) {
		tmp = t_1;
	} else if (j <= -2.25e-10) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -8.4e-45) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -1.35e-111) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (j <= -6.8e-227) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_2));
	} else if (j <= -2.15e-288) {
		tmp = t_1;
	} else if (j <= 1.5e-289) {
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	} else if (j <= 2.2e-145) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 2.05e-75) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 2.8e+63) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_2));
	} else if (j <= 7e+213) {
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	} else {
		tmp = j * (x * ((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 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
	t_2 = (z * k) - (x * j)
	tmp = 0
	if j <= -2.65e+75:
		tmp = t_1
	elif j <= -2.25e-10:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif j <= -8.4e-45:
		tmp = x * (y * ((a * b) - (c * i)))
	elif j <= -1.35e-111:
		tmp = a * (y1 * ((z * y3) - (x * y2)))
	elif j <= -6.8e-227:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_2))
	elif j <= -2.15e-288:
		tmp = t_1
	elif j <= 1.5e-289:
		tmp = c * (y3 * ((y * y4) - (z * y0)))
	elif j <= 2.2e-145:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif j <= 2.05e-75:
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
	elif j <= 2.8e+63:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_2))
	elif j <= 7e+213:
		tmp = y3 * (y0 * ((j * y5) - (z * c)))
	else:
		tmp = j * (x * ((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(j * Float64(Float64(Float64(y1 * Float64(x * i)) - Float64(y4 * Float64(y1 * y3))) - Float64(t * Float64(Float64(i * y5) - Float64(b * y4)))))
	t_2 = Float64(Float64(z * k) - Float64(x * j))
	tmp = 0.0
	if (j <= -2.65e+75)
		tmp = t_1;
	elseif (j <= -2.25e-10)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (j <= -8.4e-45)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (j <= -1.35e-111)
		tmp = Float64(a * Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))));
	elseif (j <= -6.8e-227)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * t_2)));
	elseif (j <= -2.15e-288)
		tmp = t_1;
	elseif (j <= 1.5e-289)
		tmp = Float64(c * Float64(y3 * Float64(Float64(y * y4) - Float64(z * y0))));
	elseif (j <= 2.2e-145)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (j <= 2.05e-75)
		tmp = Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= 2.8e+63)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * t_2)));
	elseif (j <= 7e+213)
		tmp = Float64(y3 * Float64(y0 * Float64(Float64(j * y5) - Float64(z * c))));
	else
		tmp = Float64(j * Float64(x * 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 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	t_2 = (z * k) - (x * j);
	tmp = 0.0;
	if (j <= -2.65e+75)
		tmp = t_1;
	elseif (j <= -2.25e-10)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (j <= -8.4e-45)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (j <= -1.35e-111)
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	elseif (j <= -6.8e-227)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_2));
	elseif (j <= -2.15e-288)
		tmp = t_1;
	elseif (j <= 1.5e-289)
		tmp = c * (y3 * ((y * y4) - (z * y0)));
	elseif (j <= 2.2e-145)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (j <= 2.05e-75)
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (j <= 2.8e+63)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_2));
	elseif (j <= 7e+213)
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	else
		tmp = j * (x * ((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[(j * N[(N[(N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.65e+75], t$95$1, If[LessEqual[j, -2.25e-10], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -8.4e-45], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.35e-111], N[(a * N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -6.8e-227], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.15e-288], t$95$1, If[LessEqual[j, 1.5e-289], N[(c * N[(y3 * N[(N[(y * y4), $MachinePrecision] - N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.2e-145], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.05e-75], N[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.8e+63], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7e+213], N[(y3 * N[(y0 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if j < -2.6499999999999999e75 or -6.79999999999999958e-227 < j < -2.14999999999999988e-288

   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. Add Preprocessing

   3. Taylor expanded in j around inf 57.6%

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

      1. +-commutative 57.6%

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

      2. mul-1-neg 57.6%

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

      3. unsub-neg 57.6%

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

      4. *-commutative 57.6%

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

   5. Simplified 57.6%

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

   6. Taylor expanded in y0 around 0 57.8%

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

      1. +-commutative 57.8%

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

      2. mul-1-neg 57.8%

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

      3. unsub-neg 57.8%

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

      4. associate-*r* 57.8%

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

      5. associate-*r* 57.8%

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

   8. Simplified 57.8%

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

   if -2.6499999999999999e75 < j < -2.25e-10

   1. Initial program 30.4%

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

   3. Taylor expanded in y1 around inf 48.5%

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

   4. Taylor expanded in z around inf 53.1%

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

   if -2.25e-10 < j < -8.3999999999999998e-45

   1. Initial program 56.2%

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

   3. Taylor expanded in x around inf 88.7%

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

   4. Taylor expanded in y around inf 67.2%

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

   if -8.3999999999999998e-45 < j < -1.34999999999999994e-111

   1. Initial program 33.2%

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

   3. Taylor expanded in y1 around inf 67.7%

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

   4. Taylor expanded in a around inf 66.9%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 66.9%

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

      2. neg-mul-1 66.9%

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

   6. Simplified 66.9%

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

   if -1.34999999999999994e-111 < j < -6.79999999999999958e-227

   1. Initial program 24.0%

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

   3. Taylor expanded in b around inf 48.1%

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

   if -2.14999999999999988e-288 < j < 1.4999999999999999e-289

   1. Initial program 11.0%

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

   3. Taylor expanded in y3 around -inf 50.3%

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

   4. Taylor expanded in c around inf 80.2%

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

   if 1.4999999999999999e-289 < j < 2.19999999999999999e-145

   1. Initial program 35.7%

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

   3. Taylor expanded in y2 around inf 48.9%

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

   4. Taylor expanded in t around inf 54.4%

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

   if 2.19999999999999999e-145 < j < 2.05000000000000001e-75

   1. Initial program 31.0%

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

   3. Taylor expanded in c around inf 62.2%

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

      1. +-commutative 62.2%

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

      2. mul-1-neg 62.2%

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

      3. unsub-neg 62.2%

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

      4. *-commutative 62.2%

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

      5. *-commutative 62.2%

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

      6. *-commutative 62.2%

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

      7. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if 2.05000000000000001e-75 < j < 2.79999999999999987e63

   1. Initial program 31.9%

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

   3. Taylor expanded in y1 around inf 53.0%

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

   4. Taylor expanded in a around 0 63.6%

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

      1. associate-*r* 63.6%

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

      2. neg-mul-1 63.6%

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

      3. *-commutative 63.6%

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

   6. Simplified 63.6%

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

   if 2.79999999999999987e63 < j < 6.9999999999999994e213

   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. Add Preprocessing

   3. Taylor expanded in y3 around -inf 38.2%

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

   4. Taylor expanded in y0 around inf 50.6%

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

      1. +-commutative 50.6%

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

      2. mul-1-neg 50.6%

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

      3. unsub-neg 50.6%

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

      4. *-commutative 50.6%

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

   6. Simplified 50.6%

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

   if 6.9999999999999994e213 < j

   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. Add Preprocessing

   3. Taylor expanded in j around inf 66.7%

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

      1. +-commutative 66.7%

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

      2. mul-1-neg 66.7%

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

      3. unsub-neg 66.7%

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

      4. *-commutative 66.7%

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

   5. Simplified 66.7%

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

   6. Taylor expanded in x around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 57.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -2.65 \cdot 10^{+75}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -2.25 \cdot 10^{-10}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -8.4 \cdot 10^{-45}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.35 \cdot 10^{-111}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -6.8 \cdot 10^{-227}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq -2.15 \cdot 10^{-288}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{-289}:\\ \;\;\;\;c \cdot \left(y3 \cdot \left(y \cdot y4 - z \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 2.2 \cdot 10^{-145}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 2.05 \cdot 10^{-75}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 2.8 \cdot 10^{+63}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 7 \cdot 10^{+213}:\\ \;\;\;\;y3 \cdot \left(y0 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 33.7% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -2.05 \cdot 10^{+122}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -7.8 \cdot 10^{+46}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -4.2:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -3.6 \cdot 10^{-41}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -4.4 \cdot 10^{-211}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 2.6 \cdot 10^{-137}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 6.2 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 0.38:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 3.65 \cdot 10^{+87}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 2.2 \cdot 10^{+164}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          j
          (-
           (- (* y1 (* x i)) (* y4 (* y1 y3)))
           (* t (- (* i y5) (* b y4)))))))
   (if (<= y -2.05e+122)
     (* x (* y (- (* a b) (* c i))))
     (if (<= y -7.8e+46)
       (* a (* b (- (* x y) (* z t))))
       (if (<= y -4.2)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= y -3.6e-41)
           (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i (- (* z k) (* x j)))))
           (if (<= y -4.4e-211)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= y 2.6e-137)
               t_1
               (if (<= y 6.2e-24)
                 (* t (* y2 (- (* a y5) (* c y4))))
                 (if (<= y 0.38)
                   (* i (* j (- (* x y1) (* t y5))))
                   (if (<= y 3.65e+87)
                     (* k (* y1 (- (* y2 y4) (* z i))))
                     (if (<= y 2.2e+164)
                       t_1
                       (* y4 (* k (- (* y1 y2) (* 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 t_1 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double tmp;
	if (y <= -2.05e+122) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -7.8e+46) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= -4.2) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (y <= -3.6e-41) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -4.4e-211) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 2.6e-137) {
		tmp = t_1;
	} else if (y <= 6.2e-24) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y <= 0.38) {
		tmp = i * (j * ((x * y1) - (t * y5)));
	} else if (y <= 3.65e+87) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y <= 2.2e+164) {
		tmp = t_1;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (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) :: t_1
    real(8) :: tmp
    t_1 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
    if (y <= (-2.05d+122)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y <= (-7.8d+46)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y <= (-4.2d0)) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (y <= (-3.6d-41)) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
    else if (y <= (-4.4d-211)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y <= 2.6d-137) then
        tmp = t_1
    else if (y <= 6.2d-24) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (y <= 0.38d0) then
        tmp = i * (j * ((x * y1) - (t * y5)))
    else if (y <= 3.65d+87) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (y <= 2.2d+164) then
        tmp = t_1
    else
        tmp = y4 * (k * ((y1 * y2) - (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 t_1 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double tmp;
	if (y <= -2.05e+122) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -7.8e+46) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= -4.2) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (y <= -3.6e-41) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -4.4e-211) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 2.6e-137) {
		tmp = t_1;
	} else if (y <= 6.2e-24) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y <= 0.38) {
		tmp = i * (j * ((x * y1) - (t * y5)));
	} else if (y <= 3.65e+87) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y <= 2.2e+164) {
		tmp = t_1;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
	tmp = 0
	if y <= -2.05e+122:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y <= -7.8e+46:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y <= -4.2:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif y <= -3.6e-41:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
	elif y <= -4.4e-211:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y <= 2.6e-137:
		tmp = t_1
	elif y <= 6.2e-24:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif y <= 0.38:
		tmp = i * (j * ((x * y1) - (t * y5)))
	elif y <= 3.65e+87:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif y <= 2.2e+164:
		tmp = t_1
	else:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(Float64(Float64(y1 * Float64(x * i)) - Float64(y4 * Float64(y1 * y3))) - Float64(t * Float64(Float64(i * y5) - Float64(b * y4)))))
	tmp = 0.0
	if (y <= -2.05e+122)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y <= -7.8e+46)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y <= -4.2)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (y <= -3.6e-41)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (y <= -4.4e-211)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y <= 2.6e-137)
		tmp = t_1;
	elseif (y <= 6.2e-24)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y <= 0.38)
		tmp = Float64(i * Float64(j * Float64(Float64(x * y1) - Float64(t * y5))));
	elseif (y <= 3.65e+87)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (y <= 2.2e+164)
		tmp = t_1;
	else
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(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)
	t_1 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	tmp = 0.0;
	if (y <= -2.05e+122)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y <= -7.8e+46)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y <= -4.2)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (y <= -3.6e-41)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	elseif (y <= -4.4e-211)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y <= 2.6e-137)
		tmp = t_1;
	elseif (y <= 6.2e-24)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (y <= 0.38)
		tmp = i * (j * ((x * y1) - (t * y5)));
	elseif (y <= 3.65e+87)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (y <= 2.2e+164)
		tmp = t_1;
	else
		tmp = y4 * (k * ((y1 * y2) - (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_] := Block[{t$95$1 = N[(j * N[(N[(N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.05e+122], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -7.8e+46], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.2], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -3.6e-41], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.4e-211], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.6e-137], t$95$1, If[LessEqual[y, 6.2e-24], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 0.38], N[(i * N[(j * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3.65e+87], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.2e+164], t$95$1, N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y < -2.0500000000000001e122

   1. Initial program 14.9%

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

   3. Taylor expanded in x around inf 64.0%

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

   4. Taylor expanded in y around inf 56.9%

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

   if -2.0500000000000001e122 < y < -7.7999999999999999e46

   1. Initial program 21.7%

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

   3. Taylor expanded in b around inf 57.8%

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

   4. Taylor expanded in a around inf 71.8%

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

   if -7.7999999999999999e46 < y < -4.20000000000000018

   1. Initial program 14.3%

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

   3. Taylor expanded in j around inf 57.1%

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

      1. +-commutative 57.1%

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

      2. mul-1-neg 57.1%

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

      3. unsub-neg 57.1%

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

      4. *-commutative 57.1%

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

   5. Simplified 57.1%

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

   6. Taylor expanded in y5 around -inf 71.7%

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

      1. associate-*r* 71.7%

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

      2. neg-mul-1 71.7%

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

      3. *-commutative 71.7%

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

   8. Simplified 71.7%

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

   if -4.20000000000000018 < y < -3.6e-41

   1. Initial program 63.4%

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

   3. Taylor expanded in y1 around inf 64.8%

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

   4. Taylor expanded in a around 0 56.5%

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

      1. associate-*r* 56.5%

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

      2. neg-mul-1 56.5%

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

      3. *-commutative 56.5%

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

   6. Simplified 56.5%

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

   if -3.6e-41 < y < -4.39999999999999996e-211

   1. Initial program 24.3%

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

   3. Taylor expanded in j around inf 38.0%

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

      1. +-commutative 38.0%

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

      2. mul-1-neg 38.0%

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

      3. unsub-neg 38.0%

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

      4. *-commutative 38.0%

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

   5. Simplified 38.0%

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

   6. Taylor expanded in x around inf 51.7%

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

   if -4.39999999999999996e-211 < y < 2.6e-137 or 3.64999999999999998e87 < y < 2.20000000000000006e164

   1. Initial program 35.0%

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

   3. Taylor expanded in j around inf 46.3%

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

      1. +-commutative 46.3%

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

      2. mul-1-neg 46.3%

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

      3. unsub-neg 46.3%

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

      4. *-commutative 46.3%

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

   5. Simplified 46.3%

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

   6. Taylor expanded in y0 around 0 46.4%

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

      1. +-commutative 46.4%

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

      2. mul-1-neg 46.4%

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

      3. unsub-neg 46.4%

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

      4. associate-*r* 47.7%

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

      5. associate-*r* 50.4%

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

   8. Simplified 50.4%

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

   if 2.6e-137 < y < 6.2000000000000001e-24

   1. Initial program 27.7%

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

   3. Taylor expanded in y2 around inf 46.3%

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

   4. Taylor expanded in t around inf 55.7%

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

   if 6.2000000000000001e-24 < y < 0.38

   1. Initial program 35.0%

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

   3. Taylor expanded in j around inf 83.6%

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

      1. +-commutative 83.6%

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

      2. mul-1-neg 83.6%

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

      3. unsub-neg 83.6%

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

      4. *-commutative 83.6%

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

   5. Simplified 83.6%

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

   6. Taylor expanded in i around -inf 67.0%

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

      1. associate-*r* 67.0%

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

      2. neg-mul-1 67.0%

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

   8. Simplified 67.0%

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

   if 0.38 < y < 3.64999999999999998e87

   1. Initial program 39.9%

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

   3. Taylor expanded in y1 around inf 50.8%

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

   4. Taylor expanded in k around inf 61.1%

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

   if 2.20000000000000006e164 < y

   1. Initial program 13.0%

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

   3. Taylor expanded in y4 around inf 31.3%

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

   4. Taylor expanded in k around inf 61.3%

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

      1. +-commutative 61.3%

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

      2. mul-1-neg 61.3%

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

      3. unsub-neg 61.3%

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

   6. Simplified 61.3%

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

4. Final simplification 56.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.05 \cdot 10^{+122}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -7.8 \cdot 10^{+46}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -4.2:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -3.6 \cdot 10^{-41}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -4.4 \cdot 10^{-211}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 2.6 \cdot 10^{-137}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 6.2 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 0.38:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 3.65 \cdot 10^{+87}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 2.2 \cdot 10^{+164}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 10: 34.1% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot k - x \cdot j\\ t_2 := j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -8 \cdot 10^{+102}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -6.2 \cdot 10^{+46}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot t\_1\right)\\ \mathbf{elif}\;y \leq -11.5:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -7.5 \cdot 10^{-42}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot t\_1\right)\\ \mathbf{elif}\;y \leq -3.1 \cdot 10^{-211}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 6.5 \cdot 10^{-139}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 2.85 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 3.1:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 2.9 \cdot 10^{+86}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 1.85 \cdot 10^{+165}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* z k) (* x j)))
        (t_2
         (*
          j
          (-
           (- (* y1 (* x i)) (* y4 (* y1 y3)))
           (* t (- (* i y5) (* b y4)))))))
   (if (<= y -8e+102)
     (* x (* y (- (* a b) (* c i))))
     (if (<= y -6.2e+46)
       (*
        b
        (+
         (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
         (* y0 t_1)))
       (if (<= y -11.5)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= y -7.5e-42)
           (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i t_1)))
           (if (<= y -3.1e-211)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= y 6.5e-139)
               t_2
               (if (<= y 2.85e-24)
                 (* t (* y2 (- (* a y5) (* c y4))))
                 (if (<= y 3.1)
                   (* i (* j (- (* x y1) (* t y5))))
                   (if (<= y 2.9e+86)
                     (* k (* y1 (- (* y2 y4) (* z i))))
                     (if (<= y 1.85e+165)
                       t_2
                       (* y4 (* k (- (* y1 y2) (* 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 t_1 = (z * k) - (x * j);
	double t_2 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double tmp;
	if (y <= -8e+102) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -6.2e+46) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_1));
	} else if (y <= -11.5) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (y <= -7.5e-42) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_1));
	} else if (y <= -3.1e-211) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 6.5e-139) {
		tmp = t_2;
	} else if (y <= 2.85e-24) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y <= 3.1) {
		tmp = i * (j * ((x * y1) - (t * y5)));
	} else if (y <= 2.9e+86) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y <= 1.85e+165) {
		tmp = t_2;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (z * k) - (x * j)
    t_2 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
    if (y <= (-8d+102)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y <= (-6.2d+46)) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_1))
    else if (y <= (-11.5d0)) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (y <= (-7.5d-42)) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_1))
    else if (y <= (-3.1d-211)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y <= 6.5d-139) then
        tmp = t_2
    else if (y <= 2.85d-24) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (y <= 3.1d0) then
        tmp = i * (j * ((x * y1) - (t * y5)))
    else if (y <= 2.9d+86) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (y <= 1.85d+165) then
        tmp = t_2
    else
        tmp = y4 * (k * ((y1 * y2) - (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 t_1 = (z * k) - (x * j);
	double t_2 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	double tmp;
	if (y <= -8e+102) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -6.2e+46) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_1));
	} else if (y <= -11.5) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (y <= -7.5e-42) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_1));
	} else if (y <= -3.1e-211) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 6.5e-139) {
		tmp = t_2;
	} else if (y <= 2.85e-24) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y <= 3.1) {
		tmp = i * (j * ((x * y1) - (t * y5)));
	} else if (y <= 2.9e+86) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (y <= 1.85e+165) {
		tmp = t_2;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (z * k) - (x * j)
	t_2 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))))
	tmp = 0
	if y <= -8e+102:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y <= -6.2e+46:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_1))
	elif y <= -11.5:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif y <= -7.5e-42:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_1))
	elif y <= -3.1e-211:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y <= 6.5e-139:
		tmp = t_2
	elif y <= 2.85e-24:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif y <= 3.1:
		tmp = i * (j * ((x * y1) - (t * y5)))
	elif y <= 2.9e+86:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif y <= 1.85e+165:
		tmp = t_2
	else:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(z * k) - Float64(x * j))
	t_2 = Float64(j * Float64(Float64(Float64(y1 * Float64(x * i)) - Float64(y4 * Float64(y1 * y3))) - Float64(t * Float64(Float64(i * y5) - Float64(b * y4)))))
	tmp = 0.0
	if (y <= -8e+102)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y <= -6.2e+46)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * t_1)));
	elseif (y <= -11.5)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (y <= -7.5e-42)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * t_1)));
	elseif (y <= -3.1e-211)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y <= 6.5e-139)
		tmp = t_2;
	elseif (y <= 2.85e-24)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y <= 3.1)
		tmp = Float64(i * Float64(j * Float64(Float64(x * y1) - Float64(t * y5))));
	elseif (y <= 2.9e+86)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (y <= 1.85e+165)
		tmp = t_2;
	else
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(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)
	t_1 = (z * k) - (x * j);
	t_2 = j * (((y1 * (x * i)) - (y4 * (y1 * y3))) - (t * ((i * y5) - (b * y4))));
	tmp = 0.0;
	if (y <= -8e+102)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y <= -6.2e+46)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_1));
	elseif (y <= -11.5)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (y <= -7.5e-42)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_1));
	elseif (y <= -3.1e-211)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y <= 6.5e-139)
		tmp = t_2;
	elseif (y <= 2.85e-24)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (y <= 3.1)
		tmp = i * (j * ((x * y1) - (t * y5)));
	elseif (y <= 2.9e+86)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (y <= 1.85e+165)
		tmp = t_2;
	else
		tmp = y4 * (k * ((y1 * y2) - (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_] := Block[{t$95$1 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -8e+102], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -6.2e+46], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -11.5], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -7.5e-42], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -3.1e-211], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 6.5e-139], t$95$2, If[LessEqual[y, 2.85e-24], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3.1], N[(i * N[(j * N[(N[(x * y1), $MachinePrecision] - N[(t * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.9e+86], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.85e+165], t$95$2, N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if y < -7.99999999999999982e102

   1. Initial program 16.2%

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

   3. Taylor expanded in x around inf 61.9%

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

   4. Taylor expanded in y around inf 57.5%

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

   if -7.99999999999999982e102 < y < -6.1999999999999995e46

   1. Initial program 18.5%

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

   3. Taylor expanded in b around inf 73.6%

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

   if -6.1999999999999995e46 < y < -11.5

   1. Initial program 14.3%

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

   3. Taylor expanded in j around inf 57.1%

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

      1. +-commutative 57.1%

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

      2. mul-1-neg 57.1%

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

      3. unsub-neg 57.1%

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

      4. *-commutative 57.1%

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

   5. Simplified 57.1%

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

   6. Taylor expanded in y5 around -inf 71.7%

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

      1. associate-*r* 71.7%

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

      2. neg-mul-1 71.7%

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

      3. *-commutative 71.7%

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

   8. Simplified 71.7%

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

   if -11.5 < y < -7.49999999999999972e-42

   1. Initial program 63.4%

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

   3. Taylor expanded in y1 around inf 64.8%

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

   4. Taylor expanded in a around 0 56.5%

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

      1. associate-*r* 56.5%

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

      2. neg-mul-1 56.5%

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

      3. *-commutative 56.5%

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

   6. Simplified 56.5%

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

   if -7.49999999999999972e-42 < y < -3.09999999999999995e-211

   1. Initial program 24.3%

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

   3. Taylor expanded in j around inf 38.0%

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

      1. +-commutative 38.0%

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

      2. mul-1-neg 38.0%

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

      3. unsub-neg 38.0%

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

      4. *-commutative 38.0%

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

   5. Simplified 38.0%

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

   6. Taylor expanded in x around inf 51.7%

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

   if -3.09999999999999995e-211 < y < 6.5e-139 or 2.8999999999999999e86 < y < 1.85000000000000003e165

   1. Initial program 35.0%

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

   3. Taylor expanded in j around inf 46.3%

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

      1. +-commutative 46.3%

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

      2. mul-1-neg 46.3%

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

      3. unsub-neg 46.3%

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

      4. *-commutative 46.3%

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

   5. Simplified 46.3%

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

   6. Taylor expanded in y0 around 0 46.4%

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

      1. +-commutative 46.4%

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

      2. mul-1-neg 46.4%

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

      3. unsub-neg 46.4%

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

      4. associate-*r* 47.7%

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

      5. associate-*r* 50.4%

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

   8. Simplified 50.4%

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

   if 6.5e-139 < y < 2.85000000000000001e-24

   1. Initial program 27.7%

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

   3. Taylor expanded in y2 around inf 46.3%

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

   4. Taylor expanded in t around inf 55.7%

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

   if 2.85000000000000001e-24 < y < 3.10000000000000009

   1. Initial program 35.0%

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

   3. Taylor expanded in j around inf 83.6%

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

      1. +-commutative 83.6%

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

      2. mul-1-neg 83.6%

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

      3. unsub-neg 83.6%

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

      4. *-commutative 83.6%

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

   5. Simplified 83.6%

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

   6. Taylor expanded in i around -inf 67.0%

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

      1. associate-*r* 67.0%

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

      2. neg-mul-1 67.0%

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

   8. Simplified 67.0%

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

   if 3.10000000000000009 < y < 2.8999999999999999e86

   1. Initial program 39.9%

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

   3. Taylor expanded in y1 around inf 50.8%

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

   4. Taylor expanded in k around inf 61.1%

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

   if 1.85000000000000003e165 < y

   1. Initial program 13.0%

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

   3. Taylor expanded in y4 around inf 31.3%

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

   4. Taylor expanded in k around inf 61.3%

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

      1. +-commutative 61.3%

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

      2. mul-1-neg 61.3%

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

      3. unsub-neg 61.3%

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

   6. Simplified 61.3%

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

4. Final simplification 56.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -8 \cdot 10^{+102}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -6.2 \cdot 10^{+46}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -11.5:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -7.5 \cdot 10^{-42}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -3.1 \cdot 10^{-211}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 6.5 \cdot 10^{-139}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 2.85 \cdot 10^{-24}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 3.1:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1 - t \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 2.9 \cdot 10^{+86}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 1.85 \cdot 10^{+165}:\\ \;\;\;\;j \cdot \left(\left(y1 \cdot \left(x \cdot i\right) - y4 \cdot \left(y1 \cdot y3\right)\right) - t \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 34.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(i \cdot y1 - b \cdot y0\right)\\ t_2 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + t\_1\right)\\ t_3 := z \cdot k - x \cdot j\\ \mathbf{if}\;j \leq -6.5 \cdot 10^{+45}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;j \leq -8.8 \cdot 10^{-11}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -3.2 \cdot 10^{-43}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-112}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -8 \cdot 10^{-146}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot t\_3\right)\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-290}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;j \leq 10^{-144}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 2.7 \cdot 10^{-75}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 6.2 \cdot 10^{+63}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot t\_3\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{+213}:\\ \;\;\;\;y3 \cdot \left(y0 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (- (* i y1) (* b y0))))
        (t_2
         (*
          j
          (+
           (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
           t_1)))
        (t_3 (- (* z k) (* x j))))
   (if (<= j -6.5e+45)
     t_2
     (if (<= j -8.8e-11)
       (* y1 (* z (- (* a y3) (* i k))))
       (if (<= j -3.2e-43)
         (* x (* y (- (* a b) (* c i))))
         (if (<= j -1.45e-112)
           (* a (* y1 (- (* z y3) (* x y2))))
           (if (<= j -8e-146)
             (*
              b
              (+
               (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
               (* y0 t_3)))
             (if (<= j -5.6e-290)
               t_2
               (if (<= j 1e-144)
                 (* t (* y2 (- (* a y5) (* c y4))))
                 (if (<= j 2.7e-75)
                   (*
                    c
                    (+
                     (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
                     (* y4 (- (* y y3) (* t y2)))))
                   (if (<= j 6.2e+63)
                     (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i t_3)))
                     (if (<= j 6.5e+213)
                       (* y3 (* y0 (- (* j y5) (* z c))))
                       (* j 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 * ((i * y1) - (b * y0));
	double t_2 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + t_1);
	double t_3 = (z * k) - (x * j);
	double tmp;
	if (j <= -6.5e+45) {
		tmp = t_2;
	} else if (j <= -8.8e-11) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -3.2e-43) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -1.45e-112) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (j <= -8e-146) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_3));
	} else if (j <= -5.6e-290) {
		tmp = t_2;
	} else if (j <= 1e-144) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 2.7e-75) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 6.2e+63) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_3));
	} else if (j <= 6.5e+213) {
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	} else {
		tmp = j * 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 = x * ((i * y1) - (b * y0))
    t_2 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + t_1)
    t_3 = (z * k) - (x * j)
    if (j <= (-6.5d+45)) then
        tmp = t_2
    else if (j <= (-8.8d-11)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (j <= (-3.2d-43)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (j <= (-1.45d-112)) then
        tmp = a * (y1 * ((z * y3) - (x * y2)))
    else if (j <= (-8d-146)) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_3))
    else if (j <= (-5.6d-290)) then
        tmp = t_2
    else if (j <= 1d-144) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (j <= 2.7d-75) then
        tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
    else if (j <= 6.2d+63) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_3))
    else if (j <= 6.5d+213) then
        tmp = y3 * (y0 * ((j * y5) - (z * c)))
    else
        tmp = j * 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 * ((i * y1) - (b * y0));
	double t_2 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + t_1);
	double t_3 = (z * k) - (x * j);
	double tmp;
	if (j <= -6.5e+45) {
		tmp = t_2;
	} else if (j <= -8.8e-11) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -3.2e-43) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -1.45e-112) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (j <= -8e-146) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_3));
	} else if (j <= -5.6e-290) {
		tmp = t_2;
	} else if (j <= 1e-144) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 2.7e-75) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (j <= 6.2e+63) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_3));
	} else if (j <= 6.5e+213) {
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	} else {
		tmp = j * 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 * ((i * y1) - (b * y0))
	t_2 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + t_1)
	t_3 = (z * k) - (x * j)
	tmp = 0
	if j <= -6.5e+45:
		tmp = t_2
	elif j <= -8.8e-11:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif j <= -3.2e-43:
		tmp = x * (y * ((a * b) - (c * i)))
	elif j <= -1.45e-112:
		tmp = a * (y1 * ((z * y3) - (x * y2)))
	elif j <= -8e-146:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_3))
	elif j <= -5.6e-290:
		tmp = t_2
	elif j <= 1e-144:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif j <= 2.7e-75:
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
	elif j <= 6.2e+63:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_3))
	elif j <= 6.5e+213:
		tmp = y3 * (y0 * ((j * y5) - (z * c)))
	else:
		tmp = j * t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))
	t_2 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + t_1))
	t_3 = Float64(Float64(z * k) - Float64(x * j))
	tmp = 0.0
	if (j <= -6.5e+45)
		tmp = t_2;
	elseif (j <= -8.8e-11)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (j <= -3.2e-43)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (j <= -1.45e-112)
		tmp = Float64(a * Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))));
	elseif (j <= -8e-146)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * t_3)));
	elseif (j <= -5.6e-290)
		tmp = t_2;
	elseif (j <= 1e-144)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (j <= 2.7e-75)
		tmp = Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= 6.2e+63)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * t_3)));
	elseif (j <= 6.5e+213)
		tmp = Float64(y3 * Float64(y0 * Float64(Float64(j * y5) - Float64(z * c))));
	else
		tmp = Float64(j * 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 * ((i * y1) - (b * y0));
	t_2 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + t_1);
	t_3 = (z * k) - (x * j);
	tmp = 0.0;
	if (j <= -6.5e+45)
		tmp = t_2;
	elseif (j <= -8.8e-11)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (j <= -3.2e-43)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (j <= -1.45e-112)
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	elseif (j <= -8e-146)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * t_3));
	elseif (j <= -5.6e-290)
		tmp = t_2;
	elseif (j <= 1e-144)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (j <= 2.7e-75)
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (j <= 6.2e+63)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * t_3));
	elseif (j <= 6.5e+213)
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	else
		tmp = j * t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -6.5e+45], t$95$2, If[LessEqual[j, -8.8e-11], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -3.2e-43], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.45e-112], N[(a * N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -8e-146], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5.6e-290], t$95$2, If[LessEqual[j, 1e-144], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.7e-75], N[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.2e+63], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.5e+213], N[(y3 * N[(y0 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * t$95$1), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if j < -6.50000000000000034e45 or -8.00000000000000021e-146 < j < -5.59999999999999993e-290

   1. Initial program 26.5%

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

   3. Taylor expanded in j around inf 53.3%

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

      1. +-commutative 53.3%

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

      2. mul-1-neg 53.3%

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

      3. unsub-neg 53.3%

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

      4. *-commutative 53.3%

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

   5. Simplified 53.3%

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

   if -6.50000000000000034e45 < j < -8.8000000000000006e-11

   1. Initial program 33.3%

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

   3. Taylor expanded in y1 around inf 53.3%

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

   4. Taylor expanded in z around inf 60.3%

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

   if -8.8000000000000006e-11 < j < -3.19999999999999985e-43

   1. Initial program 56.2%

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

   3. Taylor expanded in x around inf 88.7%

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

   4. Taylor expanded in y around inf 67.2%

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

   if -3.19999999999999985e-43 < j < -1.44999999999999996e-112

   1. Initial program 33.2%

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

   3. Taylor expanded in y1 around inf 67.7%

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

   4. Taylor expanded in a around inf 66.9%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 66.9%

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

      2. neg-mul-1 66.9%

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

   6. Simplified 66.9%

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

   if -1.44999999999999996e-112 < j < -8.00000000000000021e-146

   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. Add Preprocessing

   3. Taylor expanded in b around inf 81.1%

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

   if -5.59999999999999993e-290 < j < 9.9999999999999995e-145

   1. Initial program 28.5%

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

   3. Taylor expanded in y2 around inf 47.7%

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

   4. Taylor expanded in t around inf 54.9%

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

   if 9.9999999999999995e-145 < j < 2.6999999999999998e-75

   1. Initial program 31.0%

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

   3. Taylor expanded in c around inf 62.2%

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

      1. +-commutative 62.2%

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

      2. mul-1-neg 62.2%

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

      3. unsub-neg 62.2%

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

      4. *-commutative 62.2%

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

      5. *-commutative 62.2%

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

      6. *-commutative 62.2%

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

      7. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if 2.6999999999999998e-75 < j < 6.2000000000000001e63

   1. Initial program 31.9%

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

   3. Taylor expanded in y1 around inf 53.0%

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

   4. Taylor expanded in a around 0 63.6%

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

      1. associate-*r* 63.6%

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

      2. neg-mul-1 63.6%

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

      3. *-commutative 63.6%

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

   6. Simplified 63.6%

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

   if 6.2000000000000001e63 < j < 6.49999999999999982e213

   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. Add Preprocessing

   3. Taylor expanded in y3 around -inf 38.2%

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

   4. Taylor expanded in y0 around inf 50.6%

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

      1. +-commutative 50.6%

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

      2. mul-1-neg 50.6%

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

      3. unsub-neg 50.6%

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

      4. *-commutative 50.6%

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

   6. Simplified 50.6%

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

   if 6.49999999999999982e213 < j

   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. Add Preprocessing

   3. Taylor expanded in j around inf 66.7%

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

      1. +-commutative 66.7%

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

      2. mul-1-neg 66.7%

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

      3. unsub-neg 66.7%

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

      4. *-commutative 66.7%

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

   5. Simplified 66.7%

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

   6. Taylor expanded in x around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 57.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -6.5 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -8.8 \cdot 10^{-11}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -3.2 \cdot 10^{-43}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-112}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -8 \cdot 10^{-146}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-290}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 10^{-144}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 2.7 \cdot 10^{-75}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 6.2 \cdot 10^{+63}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{+213}:\\ \;\;\;\;y3 \cdot \left(y0 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 29.3% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ t_2 := t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -2.3 \cdot 10^{+122}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1650000:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq -2.3 \cdot 10^{-7}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -4.3 \cdot 10^{-13}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{elif}\;y \leq -6.5 \cdot 10^{-75}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq -1.35 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-296}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 2.8 \cdot 10^{-176}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 0.022:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 1.26 \cdot 10^{+148} \lor \neg \left(y \leq 5.3 \cdot 10^{+218}\right):\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* b (- (* x y) (* z t)))))
        (t_2 (* t (* y2 (- (* a y5) (* c y4))))))
   (if (<= y -2.3e+122)
     (* x (* y (- (* a b) (* c i))))
     (if (<= y -1650000.0)
       t_1
       (if (<= y -2.3e-7)
         (* j (* y0 (* y3 y5)))
         (if (<= y -4.3e-13)
           (* (* j y5) (* y0 y3))
           (if (<= y -6.5e-75)
             t_2
             (if (<= y -1.35e-250)
               (* j (* x (- (* i y1) (* b y0))))
               (if (<= y 3e-296)
                 t_2
                 (if (<= y 2.8e-176)
                   t_1
                   (if (<= y 0.022)
                     t_2
                     (if (or (<= y 1.26e+148) (not (<= y 5.3e+218)))
                       (* k (* y1 (- (* y2 y4) (* z i))))
                       t_1))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double t_2 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (y <= -2.3e+122) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -1650000.0) {
		tmp = t_1;
	} else if (y <= -2.3e-7) {
		tmp = j * (y0 * (y3 * y5));
	} else if (y <= -4.3e-13) {
		tmp = (j * y5) * (y0 * y3);
	} else if (y <= -6.5e-75) {
		tmp = t_2;
	} else if (y <= -1.35e-250) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3e-296) {
		tmp = t_2;
	} else if (y <= 2.8e-176) {
		tmp = t_1;
	} else if (y <= 0.022) {
		tmp = t_2;
	} else if ((y <= 1.26e+148) || !(y <= 5.3e+218)) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = a * (b * ((x * y) - (z * t)))
    t_2 = t * (y2 * ((a * y5) - (c * y4)))
    if (y <= (-2.3d+122)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y <= (-1650000.0d0)) then
        tmp = t_1
    else if (y <= (-2.3d-7)) then
        tmp = j * (y0 * (y3 * y5))
    else if (y <= (-4.3d-13)) then
        tmp = (j * y5) * (y0 * y3)
    else if (y <= (-6.5d-75)) then
        tmp = t_2
    else if (y <= (-1.35d-250)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y <= 3d-296) then
        tmp = t_2
    else if (y <= 2.8d-176) then
        tmp = t_1
    else if (y <= 0.022d0) then
        tmp = t_2
    else if ((y <= 1.26d+148) .or. (.not. (y <= 5.3d+218))) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double t_2 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (y <= -2.3e+122) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -1650000.0) {
		tmp = t_1;
	} else if (y <= -2.3e-7) {
		tmp = j * (y0 * (y3 * y5));
	} else if (y <= -4.3e-13) {
		tmp = (j * y5) * (y0 * y3);
	} else if (y <= -6.5e-75) {
		tmp = t_2;
	} else if (y <= -1.35e-250) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3e-296) {
		tmp = t_2;
	} else if (y <= 2.8e-176) {
		tmp = t_1;
	} else if (y <= 0.022) {
		tmp = t_2;
	} else if ((y <= 1.26e+148) || !(y <= 5.3e+218)) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (b * ((x * y) - (z * t)))
	t_2 = t * (y2 * ((a * y5) - (c * y4)))
	tmp = 0
	if y <= -2.3e+122:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y <= -1650000.0:
		tmp = t_1
	elif y <= -2.3e-7:
		tmp = j * (y0 * (y3 * y5))
	elif y <= -4.3e-13:
		tmp = (j * y5) * (y0 * y3)
	elif y <= -6.5e-75:
		tmp = t_2
	elif y <= -1.35e-250:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y <= 3e-296:
		tmp = t_2
	elif y <= 2.8e-176:
		tmp = t_1
	elif y <= 0.022:
		tmp = t_2
	elif (y <= 1.26e+148) or not (y <= 5.3e+218):
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))))
	t_2 = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))))
	tmp = 0.0
	if (y <= -2.3e+122)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y <= -1650000.0)
		tmp = t_1;
	elseif (y <= -2.3e-7)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	elseif (y <= -4.3e-13)
		tmp = Float64(Float64(j * y5) * Float64(y0 * y3));
	elseif (y <= -6.5e-75)
		tmp = t_2;
	elseif (y <= -1.35e-250)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y <= 3e-296)
		tmp = t_2;
	elseif (y <= 2.8e-176)
		tmp = t_1;
	elseif (y <= 0.022)
		tmp = t_2;
	elseif ((y <= 1.26e+148) || !(y <= 5.3e+218))
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (b * ((x * y) - (z * t)));
	t_2 = t * (y2 * ((a * y5) - (c * y4)));
	tmp = 0.0;
	if (y <= -2.3e+122)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y <= -1650000.0)
		tmp = t_1;
	elseif (y <= -2.3e-7)
		tmp = j * (y0 * (y3 * y5));
	elseif (y <= -4.3e-13)
		tmp = (j * y5) * (y0 * y3);
	elseif (y <= -6.5e-75)
		tmp = t_2;
	elseif (y <= -1.35e-250)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y <= 3e-296)
		tmp = t_2;
	elseif (y <= 2.8e-176)
		tmp = t_1;
	elseif (y <= 0.022)
		tmp = t_2;
	elseif ((y <= 1.26e+148) || ~((y <= 5.3e+218)))
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.3e+122], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1650000.0], t$95$1, If[LessEqual[y, -2.3e-7], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.3e-13], N[(N[(j * y5), $MachinePrecision] * N[(y0 * y3), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -6.5e-75], t$95$2, If[LessEqual[y, -1.35e-250], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3e-296], t$95$2, If[LessEqual[y, 2.8e-176], t$95$1, If[LessEqual[y, 0.022], t$95$2, If[Or[LessEqual[y, 1.26e+148], N[Not[LessEqual[y, 5.3e+218]], $MachinePrecision]], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if y < -2.3000000000000001e122

   1. Initial program 14.9%

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

   3. Taylor expanded in x around inf 64.0%

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

   4. Taylor expanded in y around inf 56.9%

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

   if -2.3000000000000001e122 < y < -1.65e6 or 2.9999999999999997e-296 < y < 2.8000000000000001e-176 or 1.25999999999999997e148 < y < 5.3000000000000001e218

   1. Initial program 26.9%

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

   3. Taylor expanded in b around inf 45.4%

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

   4. Taylor expanded in a around inf 49.3%

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

   if -1.65e6 < y < -2.29999999999999995e-7

   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. Add Preprocessing

   3. Taylor expanded in j around inf 43.6%

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

      1. +-commutative 43.6%

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

      2. mul-1-neg 43.6%

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

      3. unsub-neg 43.6%

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

      4. *-commutative 43.6%

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

   5. Simplified 43.6%

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

   6. Taylor expanded in y5 around inf 57.5%

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

      1. associate-*r* 57.5%

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

      2. distribute-lft-out-- 57.5%

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

      3. *-commutative 57.5%

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

   8. Simplified 57.5%

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

   9. Taylor expanded in t around 0 57.8%

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

       1. *-commutative 57.8%

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

   11. Simplified 57.8%

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

   if -2.29999999999999995e-7 < y < -4.2999999999999999e-13

   1. Initial program 50.0%

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

   3. Taylor expanded in j around inf 50.0%

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

      1. +-commutative 50.0%

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

      2. mul-1-neg 50.0%

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

      3. unsub-neg 50.0%

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

      4. *-commutative 50.0%

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

   5. Simplified 50.0%

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

   6. Taylor expanded in y5 around inf 52.8%

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

      1. associate-*r* 100.0%

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

      2. distribute-lft-out-- 100.0%

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

      3. *-commutative 100.0%

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

   8. Simplified 100.0%

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

   9. Taylor expanded in t around 0 100.0%

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

       1. neg-mul-1 100.0%

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

       2. distribute-rgt-neg-in 100.0%

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

   11. Simplified 100.0%

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

   if -4.2999999999999999e-13 < y < -6.5000000000000002e-75 or -1.35000000000000001e-250 < y < 2.9999999999999997e-296 or 2.8000000000000001e-176 < y < 0.021999999999999999

   1. Initial program 36.2%

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

   3. Taylor expanded in y2 around inf 39.8%

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

   4. Taylor expanded in t around inf 49.0%

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

   if -6.5000000000000002e-75 < y < -1.35000000000000001e-250

   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. Add Preprocessing

   3. Taylor expanded in j around inf 41.7%

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

      1. +-commutative 41.7%

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

      2. mul-1-neg 41.7%

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

      3. unsub-neg 41.7%

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

      4. *-commutative 41.7%

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

   5. Simplified 41.7%

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

   6. Taylor expanded in x around inf 49.4%

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

   if 0.021999999999999999 < y < 1.25999999999999997e148 or 5.3000000000000001e218 < y

   1. Initial program 25.0%

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

   3. Taylor expanded in y1 around inf 48.4%

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

   4. Taylor expanded in k around inf 53.4%

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

4. Final simplification 51.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.3 \cdot 10^{+122}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1650000:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -2.3 \cdot 10^{-7}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -4.3 \cdot 10^{-13}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{elif}\;y \leq -6.5 \cdot 10^{-75}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -1.35 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-296}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 2.8 \cdot 10^{-176}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq 0.022:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.26 \cdot 10^{+148} \lor \neg \left(y \leq 5.3 \cdot 10^{+218}\right):\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 31.1% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ t_2 := \left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ t_3 := j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{if}\;c \leq -1.35 \cdot 10^{+228}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;c \leq -1.85 \cdot 10^{+196}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -2050000000:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;c \leq -4.2 \cdot 10^{-150}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq -1.2 \cdot 10^{-230}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq 1.65 \cdot 10^{-156}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;c \leq 4.6 \cdot 10^{-99}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq 1.35 \cdot 10^{-71}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;c \leq 370000000:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq 1.12 \cdot 10^{+52}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+90}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y1 (* z (- (* a y3) (* i k)))))
        (t_2 (* (* x c) (- (* y0 y2) (* y i))))
        (t_3 (* j (* x (- (* i y1) (* b y0))))))
   (if (<= c -1.35e+228)
     t_2
     (if (<= c -1.85e+196)
       (* j (* y1 (- (* x i) (* y3 y4))))
       (if (<= c -2050000000.0)
         t_2
         (if (<= c -4.2e-150)
           (* y4 (* k (- (* y1 y2) (* y b))))
           (if (<= c -1.2e-230)
             t_1
             (if (<= c 1.65e-156)
               t_3
               (if (<= c 4.6e-99)
                 t_1
                 (if (<= c 1.35e-71)
                   t_3
                   (if (<= c 370000000.0)
                     t_1
                     (if (<= c 1.12e+52)
                       (* y4 (* c (- (* y y3) (* t y2))))
                       (if (<= c 2.9e+90)
                         (* x (* y (- (* a b) (* c i))))
                         (* y4 (* y2 (- (* k y1) (* t c)))))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = (x * c) * ((y0 * y2) - (y * i));
	double t_3 = j * (x * ((i * y1) - (b * y0)));
	double tmp;
	if (c <= -1.35e+228) {
		tmp = t_2;
	} else if (c <= -1.85e+196) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (c <= -2050000000.0) {
		tmp = t_2;
	} else if (c <= -4.2e-150) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (c <= -1.2e-230) {
		tmp = t_1;
	} else if (c <= 1.65e-156) {
		tmp = t_3;
	} else if (c <= 4.6e-99) {
		tmp = t_1;
	} else if (c <= 1.35e-71) {
		tmp = t_3;
	} else if (c <= 370000000.0) {
		tmp = t_1;
	} else if (c <= 1.12e+52) {
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	} else if (c <= 2.9e+90) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = y1 * (z * ((a * y3) - (i * k)))
    t_2 = (x * c) * ((y0 * y2) - (y * i))
    t_3 = j * (x * ((i * y1) - (b * y0)))
    if (c <= (-1.35d+228)) then
        tmp = t_2
    else if (c <= (-1.85d+196)) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else if (c <= (-2050000000.0d0)) then
        tmp = t_2
    else if (c <= (-4.2d-150)) then
        tmp = y4 * (k * ((y1 * y2) - (y * b)))
    else if (c <= (-1.2d-230)) then
        tmp = t_1
    else if (c <= 1.65d-156) then
        tmp = t_3
    else if (c <= 4.6d-99) then
        tmp = t_1
    else if (c <= 1.35d-71) then
        tmp = t_3
    else if (c <= 370000000.0d0) then
        tmp = t_1
    else if (c <= 1.12d+52) then
        tmp = y4 * (c * ((y * y3) - (t * y2)))
    else if (c <= 2.9d+90) then
        tmp = x * (y * ((a * b) - (c * i)))
    else
        tmp = y4 * (y2 * ((k * y1) - (t * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = (x * c) * ((y0 * y2) - (y * i));
	double t_3 = j * (x * ((i * y1) - (b * y0)));
	double tmp;
	if (c <= -1.35e+228) {
		tmp = t_2;
	} else if (c <= -1.85e+196) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (c <= -2050000000.0) {
		tmp = t_2;
	} else if (c <= -4.2e-150) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (c <= -1.2e-230) {
		tmp = t_1;
	} else if (c <= 1.65e-156) {
		tmp = t_3;
	} else if (c <= 4.6e-99) {
		tmp = t_1;
	} else if (c <= 1.35e-71) {
		tmp = t_3;
	} else if (c <= 370000000.0) {
		tmp = t_1;
	} else if (c <= 1.12e+52) {
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	} else if (c <= 2.9e+90) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y1 * (z * ((a * y3) - (i * k)))
	t_2 = (x * c) * ((y0 * y2) - (y * i))
	t_3 = j * (x * ((i * y1) - (b * y0)))
	tmp = 0
	if c <= -1.35e+228:
		tmp = t_2
	elif c <= -1.85e+196:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	elif c <= -2050000000.0:
		tmp = t_2
	elif c <= -4.2e-150:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	elif c <= -1.2e-230:
		tmp = t_1
	elif c <= 1.65e-156:
		tmp = t_3
	elif c <= 4.6e-99:
		tmp = t_1
	elif c <= 1.35e-71:
		tmp = t_3
	elif c <= 370000000.0:
		tmp = t_1
	elif c <= 1.12e+52:
		tmp = y4 * (c * ((y * y3) - (t * y2)))
	elif c <= 2.9e+90:
		tmp = x * (y * ((a * b) - (c * i)))
	else:
		tmp = y4 * (y2 * ((k * y1) - (t * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))))
	t_2 = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)))
	t_3 = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))))
	tmp = 0.0
	if (c <= -1.35e+228)
		tmp = t_2;
	elseif (c <= -1.85e+196)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	elseif (c <= -2050000000.0)
		tmp = t_2;
	elseif (c <= -4.2e-150)
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (c <= -1.2e-230)
		tmp = t_1;
	elseif (c <= 1.65e-156)
		tmp = t_3;
	elseif (c <= 4.6e-99)
		tmp = t_1;
	elseif (c <= 1.35e-71)
		tmp = t_3;
	elseif (c <= 370000000.0)
		tmp = t_1;
	elseif (c <= 1.12e+52)
		tmp = Float64(y4 * Float64(c * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (c <= 2.9e+90)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	else
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(t * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y1 * (z * ((a * y3) - (i * k)));
	t_2 = (x * c) * ((y0 * y2) - (y * i));
	t_3 = j * (x * ((i * y1) - (b * y0)));
	tmp = 0.0;
	if (c <= -1.35e+228)
		tmp = t_2;
	elseif (c <= -1.85e+196)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	elseif (c <= -2050000000.0)
		tmp = t_2;
	elseif (c <= -4.2e-150)
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	elseif (c <= -1.2e-230)
		tmp = t_1;
	elseif (c <= 1.65e-156)
		tmp = t_3;
	elseif (c <= 4.6e-99)
		tmp = t_1;
	elseif (c <= 1.35e-71)
		tmp = t_3;
	elseif (c <= 370000000.0)
		tmp = t_1;
	elseif (c <= 1.12e+52)
		tmp = y4 * (c * ((y * y3) - (t * y2)));
	elseif (c <= 2.9e+90)
		tmp = x * (y * ((a * b) - (c * i)));
	else
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.35e+228], t$95$2, If[LessEqual[c, -1.85e+196], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2050000000.0], t$95$2, If[LessEqual[c, -4.2e-150], N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.2e-230], t$95$1, If[LessEqual[c, 1.65e-156], t$95$3, If[LessEqual[c, 4.6e-99], t$95$1, If[LessEqual[c, 1.35e-71], t$95$3, If[LessEqual[c, 370000000.0], t$95$1, If[LessEqual[c, 1.12e+52], N[(y4 * N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.9e+90], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if c < -1.3500000000000001e228 or -1.84999999999999995e196 < c < -2.05e9

   1. Initial program 21.5%

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

   3. Taylor expanded in x around inf 41.5%

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

   4. Taylor expanded in c around inf 57.5%

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

      1. associate-*r* 59.3%

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

      2. +-commutative 59.3%

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

      3. mul-1-neg 59.3%

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

      4. unsub-neg 59.3%

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

      5. *-commutative 59.3%

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

   6. Simplified 59.3%

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

   if -1.3500000000000001e228 < c < -1.84999999999999995e196

   1. Initial program 18.6%

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

   3. Taylor expanded in j around inf 54.7%

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

      1. +-commutative 54.7%

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

      2. mul-1-neg 54.7%

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

      3. unsub-neg 54.7%

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

      4. *-commutative 54.7%

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

   5. Simplified 54.7%

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

   6. Taylor expanded in y1 around -inf 64.0%

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

      1. +-commutative 64.0%

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

      2. mul-1-neg 64.0%

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

      3. unsub-neg 64.0%

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

      4. *-commutative 64.0%

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

   8. Simplified 64.0%

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

   if -2.05e9 < c < -4.2000000000000002e-150

   1. Initial program 31.4%

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

   3. Taylor expanded in y4 around inf 26.2%

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

   4. Taylor expanded in k around inf 57.3%

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

      1. +-commutative 57.3%

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

      2. mul-1-neg 57.3%

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

      3. unsub-neg 57.3%

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

   6. Simplified 57.3%

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

   if -4.2000000000000002e-150 < c < -1.2000000000000001e-230 or 1.6499999999999999e-156 < c < 4.5999999999999997e-99 or 1.3500000000000001e-71 < c < 3.7e8

   1. Initial program 37.8%

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

   3. Taylor expanded in y1 around inf 49.0%

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

   4. Taylor expanded in z around inf 51.2%

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

   if -1.2000000000000001e-230 < c < 1.6499999999999999e-156 or 4.5999999999999997e-99 < c < 1.3500000000000001e-71

   1. Initial program 32.0%

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

   3. Taylor expanded in j around inf 43.9%

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

      1. +-commutative 43.9%

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

      2. mul-1-neg 43.9%

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

      3. unsub-neg 43.9%

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

      4. *-commutative 43.9%

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

   5. Simplified 43.9%

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

   6. Taylor expanded in x around inf 46.4%

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

   if 3.7e8 < c < 1.12000000000000002e52

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 53.9%

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

   4. Taylor expanded in c around inf 61.8%

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

      1. *-commutative 61.8%

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

   6. Simplified 61.8%

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

   if 1.12000000000000002e52 < c < 2.9000000000000001e90

   1. Initial program 40.0%

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

   3. Taylor expanded in x around inf 40.2%

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

   4. Taylor expanded in y around inf 51.9%

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

   if 2.9000000000000001e90 < c

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 35.2%

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

   4. Taylor expanded in y2 around inf 47.8%

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

      1. *-commutative 47.8%

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

      2. *-commutative 47.8%

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

   6. Simplified 47.8%

      \[\leadsto y4 \cdot \color{blue}{\left(y2 \cdot \left(y1 \cdot k - t \cdot c\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 53.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1.35 \cdot 10^{+228}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq -1.85 \cdot 10^{+196}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -2050000000:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq -4.2 \cdot 10^{-150}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq -1.2 \cdot 10^{-230}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;c \leq 1.65 \cdot 10^{-156}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 4.6 \cdot 10^{-99}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;c \leq 1.35 \cdot 10^{-71}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 370000000:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;c \leq 1.12 \cdot 10^{+52}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.9 \cdot 10^{+90}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 14: 29.5% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{if}\;j \leq -9.6 \cdot 10^{+118}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -2.9 \cdot 10^{-12}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -1.2 \cdot 10^{-45}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-112}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -6.8 \cdot 10^{-218}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq -1.65 \cdot 10^{-277}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 3.3 \cdot 10^{-143}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.32 \cdot 10^{-79}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq 3.9 \cdot 10^{+146}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;j \leq 9.2 \cdot 10^{+213}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y (- (* a b) (* c i))))))
   (if (<= j -9.6e+118)
     (* j (* y3 (- (* y0 y5) (* y1 y4))))
     (if (<= j -2.9e-12)
       (* y1 (* z (- (* a y3) (* i k))))
       (if (<= j -1.2e-45)
         t_1
         (if (<= j -5.6e-112)
           (* i (* y1 (- (* x j) (* z k))))
           (if (<= j -6.8e-218)
             (* a (* b (- (* x y) (* z t))))
             (if (<= j -1.65e-277)
               (* x (* y2 (- (* c y0) (* a y1))))
               (if (<= j 3.3e-143)
                 (* t (* y2 (- (* a y5) (* c y4))))
                 (if (<= j 1.32e-79)
                   t_1
                   (if (<= j 3.9e+146)
                     (* y4 (* y2 (- (* k y1) (* t c))))
                     (if (<= j 9.2e+213)
                       (* (* j y5) (* y0 y3))
                       (* j (* x (- (* 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 * (y * ((a * b) - (c * i)));
	double tmp;
	if (j <= -9.6e+118) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (j <= -2.9e-12) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -1.2e-45) {
		tmp = t_1;
	} else if (j <= -5.6e-112) {
		tmp = i * (y1 * ((x * j) - (z * k)));
	} else if (j <= -6.8e-218) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= -1.65e-277) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (j <= 3.3e-143) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 1.32e-79) {
		tmp = t_1;
	} else if (j <= 3.9e+146) {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	} else if (j <= 9.2e+213) {
		tmp = (j * y5) * (y0 * y3);
	} else {
		tmp = j * (x * ((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) :: tmp
    t_1 = x * (y * ((a * b) - (c * i)))
    if (j <= (-9.6d+118)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (j <= (-2.9d-12)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (j <= (-1.2d-45)) then
        tmp = t_1
    else if (j <= (-5.6d-112)) then
        tmp = i * (y1 * ((x * j) - (z * k)))
    else if (j <= (-6.8d-218)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (j <= (-1.65d-277)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (j <= 3.3d-143) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (j <= 1.32d-79) then
        tmp = t_1
    else if (j <= 3.9d+146) then
        tmp = y4 * (y2 * ((k * y1) - (t * c)))
    else if (j <= 9.2d+213) then
        tmp = (j * y5) * (y0 * y3)
    else
        tmp = j * (x * ((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 * (y * ((a * b) - (c * i)));
	double tmp;
	if (j <= -9.6e+118) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (j <= -2.9e-12) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -1.2e-45) {
		tmp = t_1;
	} else if (j <= -5.6e-112) {
		tmp = i * (y1 * ((x * j) - (z * k)));
	} else if (j <= -6.8e-218) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= -1.65e-277) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (j <= 3.3e-143) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 1.32e-79) {
		tmp = t_1;
	} else if (j <= 3.9e+146) {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	} else if (j <= 9.2e+213) {
		tmp = (j * y5) * (y0 * y3);
	} else {
		tmp = j * (x * ((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 * (y * ((a * b) - (c * i)))
	tmp = 0
	if j <= -9.6e+118:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif j <= -2.9e-12:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif j <= -1.2e-45:
		tmp = t_1
	elif j <= -5.6e-112:
		tmp = i * (y1 * ((x * j) - (z * k)))
	elif j <= -6.8e-218:
		tmp = a * (b * ((x * y) - (z * t)))
	elif j <= -1.65e-277:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif j <= 3.3e-143:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif j <= 1.32e-79:
		tmp = t_1
	elif j <= 3.9e+146:
		tmp = y4 * (y2 * ((k * y1) - (t * c)))
	elif j <= 9.2e+213:
		tmp = (j * y5) * (y0 * y3)
	else:
		tmp = j * (x * ((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(y * Float64(Float64(a * b) - Float64(c * i))))
	tmp = 0.0
	if (j <= -9.6e+118)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (j <= -2.9e-12)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (j <= -1.2e-45)
		tmp = t_1;
	elseif (j <= -5.6e-112)
		tmp = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))));
	elseif (j <= -6.8e-218)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (j <= -1.65e-277)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (j <= 3.3e-143)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (j <= 1.32e-79)
		tmp = t_1;
	elseif (j <= 3.9e+146)
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(t * c))));
	elseif (j <= 9.2e+213)
		tmp = Float64(Float64(j * y5) * Float64(y0 * y3));
	else
		tmp = Float64(j * Float64(x * 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 * (y * ((a * b) - (c * i)));
	tmp = 0.0;
	if (j <= -9.6e+118)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (j <= -2.9e-12)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (j <= -1.2e-45)
		tmp = t_1;
	elseif (j <= -5.6e-112)
		tmp = i * (y1 * ((x * j) - (z * k)));
	elseif (j <= -6.8e-218)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (j <= -1.65e-277)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (j <= 3.3e-143)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (j <= 1.32e-79)
		tmp = t_1;
	elseif (j <= 3.9e+146)
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	elseif (j <= 9.2e+213)
		tmp = (j * y5) * (y0 * y3);
	else
		tmp = j * (x * ((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[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -9.6e+118], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.9e-12], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.2e-45], t$95$1, If[LessEqual[j, -5.6e-112], N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -6.8e-218], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.65e-277], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.3e-143], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.32e-79], t$95$1, If[LessEqual[j, 3.9e+146], N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 9.2e+213], N[(N[(j * y5), $MachinePrecision] * N[(y0 * y3), $MachinePrecision]), $MachinePrecision], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if j < -9.6e118

   1. Initial program 22.5%

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

   3. Taylor expanded in j around inf 62.6%

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

      1. +-commutative 62.6%

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

      2. mul-1-neg 62.6%

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

      3. unsub-neg 62.6%

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

      4. *-commutative 62.6%

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

   5. Simplified 62.6%

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

   6. Taylor expanded in y3 around inf 53.8%

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

      1. *-commutative 53.8%

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

      2. *-commutative 53.8%

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

   8. Simplified 53.8%

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

   if -9.6e118 < j < -2.9000000000000002e-12

   1. Initial program 30.6%

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

   3. Taylor expanded in y1 around inf 42.6%

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

   4. Taylor expanded in z around inf 45.6%

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

   if -2.9000000000000002e-12 < j < -1.19999999999999995e-45 or 3.3000000000000001e-143 < j < 1.32e-79

   1. Initial program 44.7%

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

   3. Taylor expanded in x around inf 72.2%

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

   4. Taylor expanded in y around inf 67.6%

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

   if -1.19999999999999995e-45 < j < -5.60000000000000046e-112

   1. Initial program 33.2%

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

   3. Taylor expanded in y1 around inf 67.7%

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

   4. Taylor expanded in i around inf 56.5%

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

   if -5.60000000000000046e-112 < j < -6.79999999999999971e-218

   1. Initial program 25.7%

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

   3. Taylor expanded in b around inf 47.8%

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

   4. Taylor expanded in a around inf 44.1%

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

   if -6.79999999999999971e-218 < j < -1.64999999999999991e-277

   1. Initial program 38.3%

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

   3. Taylor expanded in y2 around inf 39.4%

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

   4. Taylor expanded in x around inf 48.0%

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

   if -1.64999999999999991e-277 < j < 3.3000000000000001e-143

   1. Initial program 29.9%

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

   3. Taylor expanded in y2 around inf 45.0%

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

   4. Taylor expanded in t around inf 50.7%

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

   if 1.32e-79 < j < 3.9e146

   1. Initial program 31.8%

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

   3. Taylor expanded in y4 around inf 29.9%

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

   4. Taylor expanded in y2 around inf 45.9%

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

      1. *-commutative 45.9%

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

      2. *-commutative 45.9%

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

   6. Simplified 45.9%

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

   if 3.9e146 < j < 9.19999999999999992e213

   1. Initial program 7.1%

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

   3. Taylor expanded in j around inf 40.7%

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

      1. +-commutative 40.7%

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

      2. mul-1-neg 40.7%

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

      3. unsub-neg 40.7%

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

      4. *-commutative 40.7%

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

   5. Simplified 40.7%

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

   6. Taylor expanded in y5 around inf 41.0%

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

      1. associate-*r* 47.1%

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

      2. distribute-lft-out-- 47.1%

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

      3. *-commutative 47.1%

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

   8. Simplified 47.1%

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

   9. Taylor expanded in t around 0 47.3%

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

       1. neg-mul-1 47.3%

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

       2. distribute-rgt-neg-in 47.3%

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

   11. Simplified 47.3%

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

   if 9.19999999999999992e213 < j

   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. Add Preprocessing

   3. Taylor expanded in j around inf 66.7%

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

      1. +-commutative 66.7%

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

      2. mul-1-neg 66.7%

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

      3. unsub-neg 66.7%

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

      4. *-commutative 66.7%

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

   5. Simplified 66.7%

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

   6. Taylor expanded in x around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 51.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -9.6 \cdot 10^{+118}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -2.9 \cdot 10^{-12}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -1.2 \cdot 10^{-45}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-112}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -6.8 \cdot 10^{-218}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq -1.65 \cdot 10^{-277}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 3.3 \cdot 10^{-143}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.32 \cdot 10^{-79}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq 3.9 \cdot 10^{+146}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;j \leq 9.2 \cdot 10^{+213}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 29.8% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{if}\;j \leq -7.5 \cdot 10^{+116}:\\ \;\;\;\;\left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \mathbf{elif}\;j \leq -7.2 \cdot 10^{-13}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-44}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq -4 \cdot 10^{-112}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -3.7 \cdot 10^{-219}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq -1.7 \cdot 10^{-275}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 3.3 \cdot 10^{-143}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.1 \cdot 10^{-78}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+147}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;j \leq 7.6 \cdot 10^{+213}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y (- (* a b) (* c i))))))
   (if (<= j -7.5e+116)
     (* (* j y3) (- (* y0 y5) (* y1 y4)))
     (if (<= j -7.2e-13)
       (* y1 (* z (- (* a y3) (* i k))))
       (if (<= j -5.6e-44)
         t_1
         (if (<= j -4e-112)
           (* i (* y1 (- (* x j) (* z k))))
           (if (<= j -3.7e-219)
             (* a (* b (- (* x y) (* z t))))
             (if (<= j -1.7e-275)
               (* x (* y2 (- (* c y0) (* a y1))))
               (if (<= j 3.3e-143)
                 (* t (* y2 (- (* a y5) (* c y4))))
                 (if (<= j 1.1e-78)
                   t_1
                   (if (<= j 1.9e+147)
                     (* y4 (* y2 (- (* k y1) (* t c))))
                     (if (<= j 7.6e+213)
                       (* (* j y5) (* y0 y3))
                       (* j (* x (- (* 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 * (y * ((a * b) - (c * i)));
	double tmp;
	if (j <= -7.5e+116) {
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4));
	} else if (j <= -7.2e-13) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -5.6e-44) {
		tmp = t_1;
	} else if (j <= -4e-112) {
		tmp = i * (y1 * ((x * j) - (z * k)));
	} else if (j <= -3.7e-219) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= -1.7e-275) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (j <= 3.3e-143) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 1.1e-78) {
		tmp = t_1;
	} else if (j <= 1.9e+147) {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	} else if (j <= 7.6e+213) {
		tmp = (j * y5) * (y0 * y3);
	} else {
		tmp = j * (x * ((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) :: tmp
    t_1 = x * (y * ((a * b) - (c * i)))
    if (j <= (-7.5d+116)) then
        tmp = (j * y3) * ((y0 * y5) - (y1 * y4))
    else if (j <= (-7.2d-13)) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (j <= (-5.6d-44)) then
        tmp = t_1
    else if (j <= (-4d-112)) then
        tmp = i * (y1 * ((x * j) - (z * k)))
    else if (j <= (-3.7d-219)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (j <= (-1.7d-275)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (j <= 3.3d-143) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (j <= 1.1d-78) then
        tmp = t_1
    else if (j <= 1.9d+147) then
        tmp = y4 * (y2 * ((k * y1) - (t * c)))
    else if (j <= 7.6d+213) then
        tmp = (j * y5) * (y0 * y3)
    else
        tmp = j * (x * ((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 * (y * ((a * b) - (c * i)));
	double tmp;
	if (j <= -7.5e+116) {
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4));
	} else if (j <= -7.2e-13) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (j <= -5.6e-44) {
		tmp = t_1;
	} else if (j <= -4e-112) {
		tmp = i * (y1 * ((x * j) - (z * k)));
	} else if (j <= -3.7e-219) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= -1.7e-275) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (j <= 3.3e-143) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 1.1e-78) {
		tmp = t_1;
	} else if (j <= 1.9e+147) {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	} else if (j <= 7.6e+213) {
		tmp = (j * y5) * (y0 * y3);
	} else {
		tmp = j * (x * ((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 * (y * ((a * b) - (c * i)))
	tmp = 0
	if j <= -7.5e+116:
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4))
	elif j <= -7.2e-13:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif j <= -5.6e-44:
		tmp = t_1
	elif j <= -4e-112:
		tmp = i * (y1 * ((x * j) - (z * k)))
	elif j <= -3.7e-219:
		tmp = a * (b * ((x * y) - (z * t)))
	elif j <= -1.7e-275:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif j <= 3.3e-143:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif j <= 1.1e-78:
		tmp = t_1
	elif j <= 1.9e+147:
		tmp = y4 * (y2 * ((k * y1) - (t * c)))
	elif j <= 7.6e+213:
		tmp = (j * y5) * (y0 * y3)
	else:
		tmp = j * (x * ((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(y * Float64(Float64(a * b) - Float64(c * i))))
	tmp = 0.0
	if (j <= -7.5e+116)
		tmp = Float64(Float64(j * y3) * Float64(Float64(y0 * y5) - Float64(y1 * y4)));
	elseif (j <= -7.2e-13)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (j <= -5.6e-44)
		tmp = t_1;
	elseif (j <= -4e-112)
		tmp = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))));
	elseif (j <= -3.7e-219)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (j <= -1.7e-275)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (j <= 3.3e-143)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (j <= 1.1e-78)
		tmp = t_1;
	elseif (j <= 1.9e+147)
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(t * c))));
	elseif (j <= 7.6e+213)
		tmp = Float64(Float64(j * y5) * Float64(y0 * y3));
	else
		tmp = Float64(j * Float64(x * 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 * (y * ((a * b) - (c * i)));
	tmp = 0.0;
	if (j <= -7.5e+116)
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4));
	elseif (j <= -7.2e-13)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (j <= -5.6e-44)
		tmp = t_1;
	elseif (j <= -4e-112)
		tmp = i * (y1 * ((x * j) - (z * k)));
	elseif (j <= -3.7e-219)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (j <= -1.7e-275)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (j <= 3.3e-143)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (j <= 1.1e-78)
		tmp = t_1;
	elseif (j <= 1.9e+147)
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	elseif (j <= 7.6e+213)
		tmp = (j * y5) * (y0 * y3);
	else
		tmp = j * (x * ((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[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -7.5e+116], N[(N[(j * y3), $MachinePrecision] * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -7.2e-13], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -5.6e-44], t$95$1, If[LessEqual[j, -4e-112], N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -3.7e-219], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.7e-275], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.3e-143], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.1e-78], t$95$1, If[LessEqual[j, 1.9e+147], N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.6e+213], N[(N[(j * y5), $MachinePrecision] * N[(y0 * y3), $MachinePrecision]), $MachinePrecision], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if j < -7.5e116

   1. Initial program 22.5%

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

   3. Taylor expanded in j around inf 62.6%

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

      1. +-commutative 62.6%

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

      2. mul-1-neg 62.6%

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

      3. unsub-neg 62.6%

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

      4. *-commutative 62.6%

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

   5. Simplified 62.6%

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

   6. Taylor expanded in y3 around inf 53.8%

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

      1. associate-*r* 58.4%

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

      2. *-commutative 58.4%

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

      3. *-commutative 58.4%

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

   8. Simplified 58.4%

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

   if -7.5e116 < j < -7.1999999999999996e-13

   1. Initial program 30.6%

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

   3. Taylor expanded in y1 around inf 42.6%

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

   4. Taylor expanded in z around inf 45.6%

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

   if -7.1999999999999996e-13 < j < -5.6e-44 or 3.3000000000000001e-143 < j < 1.0999999999999999e-78

   1. Initial program 44.7%

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

   3. Taylor expanded in x around inf 72.2%

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

   4. Taylor expanded in y around inf 67.6%

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

   if -5.6e-44 < j < -3.9999999999999998e-112

   1. Initial program 33.2%

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

   3. Taylor expanded in y1 around inf 67.7%

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

   4. Taylor expanded in i around inf 56.5%

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

   if -3.9999999999999998e-112 < j < -3.7e-219

   1. Initial program 25.7%

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

   3. Taylor expanded in b around inf 47.8%

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

   4. Taylor expanded in a around inf 44.1%

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

   if -3.7e-219 < j < -1.69999999999999984e-275

   1. Initial program 38.3%

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

   3. Taylor expanded in y2 around inf 39.4%

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

   4. Taylor expanded in x around inf 48.0%

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

   if -1.69999999999999984e-275 < j < 3.3000000000000001e-143

   1. Initial program 29.9%

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

   3. Taylor expanded in y2 around inf 45.0%

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

   4. Taylor expanded in t around inf 50.7%

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

   if 1.0999999999999999e-78 < j < 1.89999999999999985e147

   1. Initial program 31.8%

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

   3. Taylor expanded in y4 around inf 29.9%

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

   4. Taylor expanded in y2 around inf 45.9%

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

      1. *-commutative 45.9%

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

      2. *-commutative 45.9%

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

   6. Simplified 45.9%

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

   if 1.89999999999999985e147 < j < 7.5999999999999995e213

   1. Initial program 7.1%

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

   3. Taylor expanded in j around inf 40.7%

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

      1. +-commutative 40.7%

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

      2. mul-1-neg 40.7%

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

      3. unsub-neg 40.7%

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

      4. *-commutative 40.7%

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

   5. Simplified 40.7%

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

   6. Taylor expanded in y5 around inf 41.0%

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

      1. associate-*r* 47.1%

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

      2. distribute-lft-out-- 47.1%

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

      3. *-commutative 47.1%

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

   8. Simplified 47.1%

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

   9. Taylor expanded in t around 0 47.3%

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

       1. neg-mul-1 47.3%

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

       2. distribute-rgt-neg-in 47.3%

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

   11. Simplified 47.3%

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

   if 7.5999999999999995e213 < j

   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. Add Preprocessing

   3. Taylor expanded in j around inf 66.7%

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

      1. +-commutative 66.7%

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

      2. mul-1-neg 66.7%

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

      3. unsub-neg 66.7%

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

      4. *-commutative 66.7%

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

   5. Simplified 66.7%

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

   6. Taylor expanded in x around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 51.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -7.5 \cdot 10^{+116}:\\ \;\;\;\;\left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \mathbf{elif}\;j \leq -7.2 \cdot 10^{-13}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -5.6 \cdot 10^{-44}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -4 \cdot 10^{-112}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;j \leq -3.7 \cdot 10^{-219}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq -1.7 \cdot 10^{-275}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq 3.3 \cdot 10^{-143}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.1 \cdot 10^{-78}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+147}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;j \leq 7.6 \cdot 10^{+213}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 28.2% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ t_2 := t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -6.8 \cdot 10^{+115}:\\ \;\;\;\;x \cdot \left(b \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{+45}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq -1.9 \cdot 10^{-75}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-296}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{-176}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 0.009:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 5 \cdot 10^{+147} \lor \neg \left(y \leq 3.5 \cdot 10^{+218}\right):\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* b (- (* x y) (* z t)))))
        (t_2 (* t (* y2 (- (* a y5) (* c y4))))))
   (if (<= y -6.8e+115)
     (* x (* b (- (* y a) (* j y0))))
     (if (<= y -1.5e+45)
       t_1
       (if (<= y -1.9e-75)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= y -1.5e-250)
           (* j (* x (- (* i y1) (* b y0))))
           (if (<= y 3e-296)
             t_2
             (if (<= y 1.55e-176)
               t_1
               (if (<= y 0.009)
                 t_2
                 (if (or (<= y 5e+147) (not (<= y 3.5e+218)))
                   (* k (* y1 (- (* y2 y4) (* z i))))
                   t_1))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double t_2 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (y <= -6.8e+115) {
		tmp = x * (b * ((y * a) - (j * y0)));
	} else if (y <= -1.5e+45) {
		tmp = t_1;
	} else if (y <= -1.9e-75) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= -1.5e-250) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3e-296) {
		tmp = t_2;
	} else if (y <= 1.55e-176) {
		tmp = t_1;
	} else if (y <= 0.009) {
		tmp = t_2;
	} else if ((y <= 5e+147) || !(y <= 3.5e+218)) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = a * (b * ((x * y) - (z * t)))
    t_2 = t * (y2 * ((a * y5) - (c * y4)))
    if (y <= (-6.8d+115)) then
        tmp = x * (b * ((y * a) - (j * y0)))
    else if (y <= (-1.5d+45)) then
        tmp = t_1
    else if (y <= (-1.9d-75)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y <= (-1.5d-250)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y <= 3d-296) then
        tmp = t_2
    else if (y <= 1.55d-176) then
        tmp = t_1
    else if (y <= 0.009d0) then
        tmp = t_2
    else if ((y <= 5d+147) .or. (.not. (y <= 3.5d+218))) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double t_2 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (y <= -6.8e+115) {
		tmp = x * (b * ((y * a) - (j * y0)));
	} else if (y <= -1.5e+45) {
		tmp = t_1;
	} else if (y <= -1.9e-75) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= -1.5e-250) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3e-296) {
		tmp = t_2;
	} else if (y <= 1.55e-176) {
		tmp = t_1;
	} else if (y <= 0.009) {
		tmp = t_2;
	} else if ((y <= 5e+147) || !(y <= 3.5e+218)) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (b * ((x * y) - (z * t)))
	t_2 = t * (y2 * ((a * y5) - (c * y4)))
	tmp = 0
	if y <= -6.8e+115:
		tmp = x * (b * ((y * a) - (j * y0)))
	elif y <= -1.5e+45:
		tmp = t_1
	elif y <= -1.9e-75:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y <= -1.5e-250:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y <= 3e-296:
		tmp = t_2
	elif y <= 1.55e-176:
		tmp = t_1
	elif y <= 0.009:
		tmp = t_2
	elif (y <= 5e+147) or not (y <= 3.5e+218):
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))))
	t_2 = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))))
	tmp = 0.0
	if (y <= -6.8e+115)
		tmp = Float64(x * Float64(b * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= -1.5e+45)
		tmp = t_1;
	elseif (y <= -1.9e-75)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y <= -1.5e-250)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y <= 3e-296)
		tmp = t_2;
	elseif (y <= 1.55e-176)
		tmp = t_1;
	elseif (y <= 0.009)
		tmp = t_2;
	elseif ((y <= 5e+147) || !(y <= 3.5e+218))
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (b * ((x * y) - (z * t)));
	t_2 = t * (y2 * ((a * y5) - (c * y4)));
	tmp = 0.0;
	if (y <= -6.8e+115)
		tmp = x * (b * ((y * a) - (j * y0)));
	elseif (y <= -1.5e+45)
		tmp = t_1;
	elseif (y <= -1.9e-75)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y <= -1.5e-250)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y <= 3e-296)
		tmp = t_2;
	elseif (y <= 1.55e-176)
		tmp = t_1;
	elseif (y <= 0.009)
		tmp = t_2;
	elseif ((y <= 5e+147) || ~((y <= 3.5e+218)))
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -6.8e+115], N[(x * N[(b * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.5e+45], t$95$1, If[LessEqual[y, -1.9e-75], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.5e-250], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3e-296], t$95$2, If[LessEqual[y, 1.55e-176], t$95$1, If[LessEqual[y, 0.009], t$95$2, If[Or[LessEqual[y, 5e+147], N[Not[LessEqual[y, 3.5e+218]], $MachinePrecision]], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y < -6.8000000000000001e115

   1. Initial program 14.9%

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

   3. Taylor expanded in x around inf 64.0%

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

   4. Taylor expanded in b around inf 42.1%

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

      1. *-commutative 42.1%

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

      2. *-commutative 42.1%

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

   6. Simplified 42.1%

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

   if -6.8000000000000001e115 < y < -1.50000000000000005e45 or 2.9999999999999997e-296 < y < 1.54999999999999996e-176 or 5.0000000000000002e147 < y < 3.50000000000000019e218

   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. Add Preprocessing

   3. Taylor expanded in b around inf 46.1%

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

   4. Taylor expanded in a around inf 50.1%

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

   if -1.50000000000000005e45 < y < -1.89999999999999997e-75

   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. Add Preprocessing

   3. Taylor expanded in j around inf 41.3%

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

      1. +-commutative 41.3%

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

      2. mul-1-neg 41.3%

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

      3. unsub-neg 41.3%

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

      4. *-commutative 41.3%

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

   5. Simplified 41.3%

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

   6. Taylor expanded in t around inf 45.5%

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

   if -1.89999999999999997e-75 < y < -1.50000000000000008e-250

   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. Add Preprocessing

   3. Taylor expanded in j around inf 41.7%

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

      1. +-commutative 41.7%

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

      2. mul-1-neg 41.7%

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

      3. unsub-neg 41.7%

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

      4. *-commutative 41.7%

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

   5. Simplified 41.7%

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

   6. Taylor expanded in x around inf 49.4%

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

   if -1.50000000000000008e-250 < y < 2.9999999999999997e-296 or 1.54999999999999996e-176 < y < 0.00899999999999999932

   1. Initial program 31.4%

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

   3. Taylor expanded in y2 around inf 41.4%

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

   4. Taylor expanded in t around inf 49.4%

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

   if 0.00899999999999999932 < y < 5.0000000000000002e147 or 3.50000000000000019e218 < y

   1. Initial program 25.0%

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

   3. Taylor expanded in y1 around inf 48.4%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in k around inf 53.4%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 48.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -6.8 \cdot 10^{+115}:\\ \;\;\;\;x \cdot \left(b \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{+45}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -1.9 \cdot 10^{-75}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-296}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{-176}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq 0.009:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 5 \cdot 10^{+147} \lor \neg \left(y \leq 3.5 \cdot 10^{+218}\right):\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 17: 26.7% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ t_2 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -1.5 \cdot 10^{+163}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(t \cdot \left(-i\right)\right)\\ \mathbf{elif}\;t \leq -6.5 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -9.8 \cdot 10^{-101}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -5.1 \cdot 10^{-166}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.8 \cdot 10^{-210}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{-264}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 1.55 \cdot 10^{-198}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{-106}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{+155}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* y1 (- (* x j) (* z k)))))
        (t_2 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -1.5e+163)
     (* (* j y5) (* t (- i)))
     (if (<= t -6.5e-35)
       (* a (* b (- (* x y) (* z t))))
       (if (<= t -9.8e-101)
         t_1
         (if (<= t -5.1e-166)
           (* a (* z (* y1 y3)))
           (if (<= t -1.8e-210)
             t_2
             (if (<= t 2.5e-264)
               (* (* x y) (* a b))
               (if (<= t 1.55e-198)
                 t_2
                 (if (<= t 1.2e-106)
                   t_1
                   (if (<= t 2.4e+155) t_2 (* y4 (* y2 (* t (- c)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (y1 * ((x * j) - (z * k)));
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -1.5e+163) {
		tmp = (j * y5) * (t * -i);
	} else if (t <= -6.5e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -9.8e-101) {
		tmp = t_1;
	} else if (t <= -5.1e-166) {
		tmp = a * (z * (y1 * y3));
	} else if (t <= -1.8e-210) {
		tmp = t_2;
	} else if (t <= 2.5e-264) {
		tmp = (x * y) * (a * b);
	} else if (t <= 1.55e-198) {
		tmp = t_2;
	} else if (t <= 1.2e-106) {
		tmp = t_1;
	} else if (t <= 2.4e+155) {
		tmp = t_2;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = i * (y1 * ((x * j) - (z * k)))
    t_2 = b * (y0 * ((z * k) - (x * j)))
    if (t <= (-1.5d+163)) then
        tmp = (j * y5) * (t * -i)
    else if (t <= (-6.5d-35)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (t <= (-9.8d-101)) then
        tmp = t_1
    else if (t <= (-5.1d-166)) then
        tmp = a * (z * (y1 * y3))
    else if (t <= (-1.8d-210)) then
        tmp = t_2
    else if (t <= 2.5d-264) then
        tmp = (x * y) * (a * b)
    else if (t <= 1.55d-198) then
        tmp = t_2
    else if (t <= 1.2d-106) then
        tmp = t_1
    else if (t <= 2.4d+155) then
        tmp = t_2
    else
        tmp = y4 * (y2 * (t * -c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (y1 * ((x * j) - (z * k)));
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -1.5e+163) {
		tmp = (j * y5) * (t * -i);
	} else if (t <= -6.5e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -9.8e-101) {
		tmp = t_1;
	} else if (t <= -5.1e-166) {
		tmp = a * (z * (y1 * y3));
	} else if (t <= -1.8e-210) {
		tmp = t_2;
	} else if (t <= 2.5e-264) {
		tmp = (x * y) * (a * b);
	} else if (t <= 1.55e-198) {
		tmp = t_2;
	} else if (t <= 1.2e-106) {
		tmp = t_1;
	} else if (t <= 2.4e+155) {
		tmp = t_2;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (y1 * ((x * j) - (z * k)))
	t_2 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -1.5e+163:
		tmp = (j * y5) * (t * -i)
	elif t <= -6.5e-35:
		tmp = a * (b * ((x * y) - (z * t)))
	elif t <= -9.8e-101:
		tmp = t_1
	elif t <= -5.1e-166:
		tmp = a * (z * (y1 * y3))
	elif t <= -1.8e-210:
		tmp = t_2
	elif t <= 2.5e-264:
		tmp = (x * y) * (a * b)
	elif t <= 1.55e-198:
		tmp = t_2
	elif t <= 1.2e-106:
		tmp = t_1
	elif t <= 2.4e+155:
		tmp = t_2
	else:
		tmp = y4 * (y2 * (t * -c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))))
	t_2 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -1.5e+163)
		tmp = Float64(Float64(j * y5) * Float64(t * Float64(-i)));
	elseif (t <= -6.5e-35)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= -9.8e-101)
		tmp = t_1;
	elseif (t <= -5.1e-166)
		tmp = Float64(a * Float64(z * Float64(y1 * y3)));
	elseif (t <= -1.8e-210)
		tmp = t_2;
	elseif (t <= 2.5e-264)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (t <= 1.55e-198)
		tmp = t_2;
	elseif (t <= 1.2e-106)
		tmp = t_1;
	elseif (t <= 2.4e+155)
		tmp = t_2;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (y1 * ((x * j) - (z * k)));
	t_2 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -1.5e+163)
		tmp = (j * y5) * (t * -i);
	elseif (t <= -6.5e-35)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (t <= -9.8e-101)
		tmp = t_1;
	elseif (t <= -5.1e-166)
		tmp = a * (z * (y1 * y3));
	elseif (t <= -1.8e-210)
		tmp = t_2;
	elseif (t <= 2.5e-264)
		tmp = (x * y) * (a * b);
	elseif (t <= 1.55e-198)
		tmp = t_2;
	elseif (t <= 1.2e-106)
		tmp = t_1;
	elseif (t <= 2.4e+155)
		tmp = t_2;
	else
		tmp = y4 * (y2 * (t * -c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.5e+163], N[(N[(j * y5), $MachinePrecision] * N[(t * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -6.5e-35], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -9.8e-101], t$95$1, If[LessEqual[t, -5.1e-166], N[(a * N[(z * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.8e-210], t$95$2, If[LessEqual[t, 2.5e-264], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.55e-198], t$95$2, If[LessEqual[t, 1.2e-106], t$95$1, If[LessEqual[t, 2.4e+155], t$95$2, N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -1.50000000000000007e163

   1. Initial program 19.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 39.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 39.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 39.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 46.9%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 46.5%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 46.5%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 46.5%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 46.5%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around inf 50.5%

      \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(i \cdot t\right)}\right) \]
   10. Step-by-step derivation

       1. *-commutative 50.5%

          \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(t \cdot i\right)}\right) \]

   11. Simplified 50.5%

       \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(t \cdot i\right)}\right) \]

   if -1.50000000000000007e163 < t < -6.4999999999999999e-35

   1. Initial program 28.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 35.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 41.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -6.4999999999999999e-35 < t < -9.8000000000000001e-101 or 1.5499999999999999e-198 < t < 1.1999999999999999e-106

   1. Initial program 32.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 58.4%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in i around inf 50.9%

      \[\leadsto \color{blue}{i \cdot \left(y1 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -9.8000000000000001e-101 < t < -5.1000000000000002e-166

   1. Initial program 38.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 17.3%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 18.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 18.0%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 18.0%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 18.0%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 23.8%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 34.4%

         \[\leadsto a \cdot \color{blue}{\left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   9. Simplified 34.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   if -5.1000000000000002e-166 < t < -1.7999999999999999e-210 or 2.5e-264 < t < 1.5499999999999999e-198 or 1.1999999999999999e-106 < t < 2.40000000000000021e155

   1. Initial program 27.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 35.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 42.2%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if -1.7999999999999999e-210 < t < 2.5e-264

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 33.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 31.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 31.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. add0 31.2%

         \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right) + 0} \]

      2. associate-*r* 34.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)} + 0 \]

      3. *-commutative 34.1%

         \[\leadsto \left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)} + 0 \]

   7. Applied egg-rr 34.1%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right) + 0} \]
   8. Step-by-step derivation

      1. add0 34.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

   9. Simplified 34.1%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

   if 2.40000000000000021e155 < t

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 57.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 64.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 67.3%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 67.3%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 70.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 46.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.5 \cdot 10^{+163}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(t \cdot \left(-i\right)\right)\\ \mathbf{elif}\;t \leq -6.5 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -9.8 \cdot 10^{-101}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -5.1 \cdot 10^{-166}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.8 \cdot 10^{-210}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{-264}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 1.55 \cdot 10^{-198}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{-106}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{+155}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 18: 28.2% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ t_2 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -5.5 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-101}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -4.4 \cdot 10^{-167}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.08 \cdot 10^{-213}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-261}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-198}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.65 \cdot 10^{-101}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 1.35 \cdot 10^{+155}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* y1 (- (* x j) (* z k)))))
        (t_2 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -5.5e+178)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= t -5.2e-35)
       (* a (* b (- (* x y) (* z t))))
       (if (<= t -2.8e-101)
         t_1
         (if (<= t -4.4e-167)
           (* a (* z (* y1 y3)))
           (if (<= t -1.08e-213)
             t_2
             (if (<= t 2e-261)
               (* (* x y) (* a b))
               (if (<= t 1.05e-198)
                 t_2
                 (if (<= t 2.65e-101)
                   t_1
                   (if (<= t 1.35e+155)
                     t_2
                     (* y4 (* y2 (* t (- c)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (y1 * ((x * j) - (z * k)));
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -5.5e+178) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -5.2e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -2.8e-101) {
		tmp = t_1;
	} else if (t <= -4.4e-167) {
		tmp = a * (z * (y1 * y3));
	} else if (t <= -1.08e-213) {
		tmp = t_2;
	} else if (t <= 2e-261) {
		tmp = (x * y) * (a * b);
	} else if (t <= 1.05e-198) {
		tmp = t_2;
	} else if (t <= 2.65e-101) {
		tmp = t_1;
	} else if (t <= 1.35e+155) {
		tmp = t_2;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = i * (y1 * ((x * j) - (z * k)))
    t_2 = b * (y0 * ((z * k) - (x * j)))
    if (t <= (-5.5d+178)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-5.2d-35)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (t <= (-2.8d-101)) then
        tmp = t_1
    else if (t <= (-4.4d-167)) then
        tmp = a * (z * (y1 * y3))
    else if (t <= (-1.08d-213)) then
        tmp = t_2
    else if (t <= 2d-261) then
        tmp = (x * y) * (a * b)
    else if (t <= 1.05d-198) then
        tmp = t_2
    else if (t <= 2.65d-101) then
        tmp = t_1
    else if (t <= 1.35d+155) then
        tmp = t_2
    else
        tmp = y4 * (y2 * (t * -c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (y1 * ((x * j) - (z * k)));
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -5.5e+178) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -5.2e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -2.8e-101) {
		tmp = t_1;
	} else if (t <= -4.4e-167) {
		tmp = a * (z * (y1 * y3));
	} else if (t <= -1.08e-213) {
		tmp = t_2;
	} else if (t <= 2e-261) {
		tmp = (x * y) * (a * b);
	} else if (t <= 1.05e-198) {
		tmp = t_2;
	} else if (t <= 2.65e-101) {
		tmp = t_1;
	} else if (t <= 1.35e+155) {
		tmp = t_2;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (y1 * ((x * j) - (z * k)))
	t_2 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -5.5e+178:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -5.2e-35:
		tmp = a * (b * ((x * y) - (z * t)))
	elif t <= -2.8e-101:
		tmp = t_1
	elif t <= -4.4e-167:
		tmp = a * (z * (y1 * y3))
	elif t <= -1.08e-213:
		tmp = t_2
	elif t <= 2e-261:
		tmp = (x * y) * (a * b)
	elif t <= 1.05e-198:
		tmp = t_2
	elif t <= 2.65e-101:
		tmp = t_1
	elif t <= 1.35e+155:
		tmp = t_2
	else:
		tmp = y4 * (y2 * (t * -c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))))
	t_2 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -5.5e+178)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -5.2e-35)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= -2.8e-101)
		tmp = t_1;
	elseif (t <= -4.4e-167)
		tmp = Float64(a * Float64(z * Float64(y1 * y3)));
	elseif (t <= -1.08e-213)
		tmp = t_2;
	elseif (t <= 2e-261)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (t <= 1.05e-198)
		tmp = t_2;
	elseif (t <= 2.65e-101)
		tmp = t_1;
	elseif (t <= 1.35e+155)
		tmp = t_2;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (y1 * ((x * j) - (z * k)));
	t_2 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -5.5e+178)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -5.2e-35)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (t <= -2.8e-101)
		tmp = t_1;
	elseif (t <= -4.4e-167)
		tmp = a * (z * (y1 * y3));
	elseif (t <= -1.08e-213)
		tmp = t_2;
	elseif (t <= 2e-261)
		tmp = (x * y) * (a * b);
	elseif (t <= 1.05e-198)
		tmp = t_2;
	elseif (t <= 2.65e-101)
		tmp = t_1;
	elseif (t <= 1.35e+155)
		tmp = t_2;
	else
		tmp = y4 * (y2 * (t * -c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -5.5e+178], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.2e-35], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.8e-101], t$95$1, If[LessEqual[t, -4.4e-167], N[(a * N[(z * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.08e-213], t$95$2, If[LessEqual[t, 2e-261], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.05e-198], t$95$2, If[LessEqual[t, 2.65e-101], t$95$1, If[LessEqual[t, 1.35e+155], t$95$2, N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -5.5000000000000001e178

   1. Initial program 17.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in t around inf 53.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -5.5000000000000001e178 < t < -5.20000000000000009e-35

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 32.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 41.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -5.20000000000000009e-35 < t < -2.79999999999999989e-101 or 1.04999999999999996e-198 < t < 2.6500000000000001e-101

   1. Initial program 32.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 57.9%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in i around inf 50.8%

      \[\leadsto \color{blue}{i \cdot \left(y1 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -2.79999999999999989e-101 < t < -4.3999999999999999e-167

   1. Initial program 38.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 17.3%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 18.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 18.0%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 18.0%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 18.0%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 23.8%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 34.4%

         \[\leadsto a \cdot \color{blue}{\left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   9. Simplified 34.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   if -4.3999999999999999e-167 < t < -1.08e-213 or 1.99999999999999997e-261 < t < 1.04999999999999996e-198 or 2.6500000000000001e-101 < t < 1.34999999999999997e155

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 35.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 42.0%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if -1.08e-213 < t < 1.99999999999999997e-261

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 33.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 31.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 31.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. add0 31.2%

         \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right) + 0} \]

      2. associate-*r* 34.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)} + 0 \]

      3. *-commutative 34.1%

         \[\leadsto \left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)} + 0 \]

   7. Applied egg-rr 34.1%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right) + 0} \]
   8. Step-by-step derivation

      1. add0 34.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

   9. Simplified 34.1%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

   if 1.34999999999999997e155 < t

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 57.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 64.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 67.3%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 67.3%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 70.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 46.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5.5 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-101}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -4.4 \cdot 10^{-167}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.08 \cdot 10^{-213}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-261}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-198}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.65 \cdot 10^{-101}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 1.35 \cdot 10^{+155}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 19: 30.5% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ t_2 := j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -4.5 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -5.4 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -8.2 \cdot 10^{-60}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq -6.7 \cdot 10^{-99}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{-258}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-221}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-159}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-52}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 4.4 \cdot 10^{+89}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* y1 (- (* x j) (* z k)))))
        (t_2 (* j (* y3 (- (* y0 y5) (* y1 y4))))))
   (if (<= t -4.5e+178)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= t -5.4e-35)
       (* a (* b (- (* x y) (* z t))))
       (if (<= t -8.2e-60)
         t_2
         (if (<= t -6.7e-99)
           t_1
           (if (<= t -3.5e-258)
             t_2
             (if (<= t 1.45e-221)
               (* j (* x (- (* i y1) (* b y0))))
               (if (<= t 7e-159)
                 t_2
                 (if (<= t 1.45e-52)
                   t_1
                   (if (<= t 4.4e+89) t_2 (* y4 (* y2 (* t (- c)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (y1 * ((x * j) - (z * k)));
	double t_2 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	double tmp;
	if (t <= -4.5e+178) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -5.4e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -8.2e-60) {
		tmp = t_2;
	} else if (t <= -6.7e-99) {
		tmp = t_1;
	} else if (t <= -3.5e-258) {
		tmp = t_2;
	} else if (t <= 1.45e-221) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 7e-159) {
		tmp = t_2;
	} else if (t <= 1.45e-52) {
		tmp = t_1;
	} else if (t <= 4.4e+89) {
		tmp = t_2;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = i * (y1 * ((x * j) - (z * k)))
    t_2 = j * (y3 * ((y0 * y5) - (y1 * y4)))
    if (t <= (-4.5d+178)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-5.4d-35)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (t <= (-8.2d-60)) then
        tmp = t_2
    else if (t <= (-6.7d-99)) then
        tmp = t_1
    else if (t <= (-3.5d-258)) then
        tmp = t_2
    else if (t <= 1.45d-221) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 7d-159) then
        tmp = t_2
    else if (t <= 1.45d-52) then
        tmp = t_1
    else if (t <= 4.4d+89) then
        tmp = t_2
    else
        tmp = y4 * (y2 * (t * -c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (y1 * ((x * j) - (z * k)));
	double t_2 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	double tmp;
	if (t <= -4.5e+178) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -5.4e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -8.2e-60) {
		tmp = t_2;
	} else if (t <= -6.7e-99) {
		tmp = t_1;
	} else if (t <= -3.5e-258) {
		tmp = t_2;
	} else if (t <= 1.45e-221) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 7e-159) {
		tmp = t_2;
	} else if (t <= 1.45e-52) {
		tmp = t_1;
	} else if (t <= 4.4e+89) {
		tmp = t_2;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (y1 * ((x * j) - (z * k)))
	t_2 = j * (y3 * ((y0 * y5) - (y1 * y4)))
	tmp = 0
	if t <= -4.5e+178:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -5.4e-35:
		tmp = a * (b * ((x * y) - (z * t)))
	elif t <= -8.2e-60:
		tmp = t_2
	elif t <= -6.7e-99:
		tmp = t_1
	elif t <= -3.5e-258:
		tmp = t_2
	elif t <= 1.45e-221:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 7e-159:
		tmp = t_2
	elif t <= 1.45e-52:
		tmp = t_1
	elif t <= 4.4e+89:
		tmp = t_2
	else:
		tmp = y4 * (y2 * (t * -c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))))
	t_2 = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))))
	tmp = 0.0
	if (t <= -4.5e+178)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -5.4e-35)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= -8.2e-60)
		tmp = t_2;
	elseif (t <= -6.7e-99)
		tmp = t_1;
	elseif (t <= -3.5e-258)
		tmp = t_2;
	elseif (t <= 1.45e-221)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 7e-159)
		tmp = t_2;
	elseif (t <= 1.45e-52)
		tmp = t_1;
	elseif (t <= 4.4e+89)
		tmp = t_2;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (y1 * ((x * j) - (z * k)));
	t_2 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	tmp = 0.0;
	if (t <= -4.5e+178)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -5.4e-35)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (t <= -8.2e-60)
		tmp = t_2;
	elseif (t <= -6.7e-99)
		tmp = t_1;
	elseif (t <= -3.5e-258)
		tmp = t_2;
	elseif (t <= 1.45e-221)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 7e-159)
		tmp = t_2;
	elseif (t <= 1.45e-52)
		tmp = t_1;
	elseif (t <= 4.4e+89)
		tmp = t_2;
	else
		tmp = y4 * (y2 * (t * -c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -4.5e+178], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.4e-35], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -8.2e-60], t$95$2, If[LessEqual[t, -6.7e-99], t$95$1, If[LessEqual[t, -3.5e-258], t$95$2, If[LessEqual[t, 1.45e-221], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7e-159], t$95$2, If[LessEqual[t, 1.45e-52], t$95$1, If[LessEqual[t, 4.4e+89], t$95$2, N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -4.4999999999999997e178

   1. Initial program 17.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in t around inf 53.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -4.4999999999999997e178 < t < -5.3999999999999995e-35

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 32.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 41.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -5.3999999999999995e-35 < t < -8.20000000000000025e-60 or -6.6999999999999999e-99 < t < -3.50000000000000001e-258 or 1.44999999999999997e-221 < t < 7.00000000000000005e-159 or 1.4500000000000001e-52 < t < 4.4e89

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 46.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 46.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 46.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 46.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 46.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y3 around inf 50.0%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 50.0%

         \[\leadsto j \cdot \left(y3 \cdot \left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right)\right) \]

      2. *-commutative 50.0%

         \[\leadsto j \cdot \left(y3 \cdot \left(y5 \cdot y0 - \color{blue}{y4 \cdot y1}\right)\right) \]

   8. Simplified 50.0%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y5 \cdot y0 - y4 \cdot y1\right)\right)} \]

   if -8.20000000000000025e-60 < t < -6.6999999999999999e-99 or 7.00000000000000005e-159 < t < 1.4500000000000001e-52

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 47.4%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in i around inf 59.7%

      \[\leadsto \color{blue}{i \cdot \left(y1 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -3.50000000000000001e-258 < t < 1.44999999999999997e-221

   1. Initial program 45.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 25.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 25.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 25.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 25.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 25.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 25.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 34.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 4.4e89 < t

   1. Initial program 16.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 51.7%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 54.3%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 54.3%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 54.3%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 54.4%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 54.4%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 58.9%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 58.9%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 58.9%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 49.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -4.5 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -5.4 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -8.2 \cdot 10^{-60}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -6.7 \cdot 10^{-99}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{-258}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-221}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-159}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-52}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 4.4 \cdot 10^{+89}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 20: 31.2% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ t_2 := \left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ t_3 := j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{if}\;c \leq -1.4 \cdot 10^{+228}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;c \leq -5.1 \cdot 10^{+196}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -5800000000:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;c \leq -6.5 \cdot 10^{-148}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq -1.2 \cdot 10^{-233}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq 1.1 \cdot 10^{-158}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;c \leq 1.8 \cdot 10^{-99}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.6 \cdot 10^{-69}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;c \leq 8.5 \cdot 10^{+31}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y1 (* z (- (* a y3) (* i k)))))
        (t_2 (* (* x c) (- (* y0 y2) (* y i))))
        (t_3 (* j (* x (- (* i y1) (* b y0))))))
   (if (<= c -1.4e+228)
     t_2
     (if (<= c -5.1e+196)
       (* j (* y1 (- (* x i) (* y3 y4))))
       (if (<= c -5800000000.0)
         t_2
         (if (<= c -6.5e-148)
           (* y4 (* k (- (* y1 y2) (* y b))))
           (if (<= c -1.2e-233)
             t_1
             (if (<= c 1.1e-158)
               t_3
               (if (<= c 1.8e-99)
                 (* a (* y1 (- (* z y3) (* x y2))))
                 (if (<= c 2.6e-69)
                   t_3
                   (if (<= c 8.5e+31)
                     t_1
                     (* y4 (* y2 (- (* k y1) (* t c)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = (x * c) * ((y0 * y2) - (y * i));
	double t_3 = j * (x * ((i * y1) - (b * y0)));
	double tmp;
	if (c <= -1.4e+228) {
		tmp = t_2;
	} else if (c <= -5.1e+196) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (c <= -5800000000.0) {
		tmp = t_2;
	} else if (c <= -6.5e-148) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (c <= -1.2e-233) {
		tmp = t_1;
	} else if (c <= 1.1e-158) {
		tmp = t_3;
	} else if (c <= 1.8e-99) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (c <= 2.6e-69) {
		tmp = t_3;
	} else if (c <= 8.5e+31) {
		tmp = t_1;
	} else {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = y1 * (z * ((a * y3) - (i * k)))
    t_2 = (x * c) * ((y0 * y2) - (y * i))
    t_3 = j * (x * ((i * y1) - (b * y0)))
    if (c <= (-1.4d+228)) then
        tmp = t_2
    else if (c <= (-5.1d+196)) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else if (c <= (-5800000000.0d0)) then
        tmp = t_2
    else if (c <= (-6.5d-148)) then
        tmp = y4 * (k * ((y1 * y2) - (y * b)))
    else if (c <= (-1.2d-233)) then
        tmp = t_1
    else if (c <= 1.1d-158) then
        tmp = t_3
    else if (c <= 1.8d-99) then
        tmp = a * (y1 * ((z * y3) - (x * y2)))
    else if (c <= 2.6d-69) then
        tmp = t_3
    else if (c <= 8.5d+31) then
        tmp = t_1
    else
        tmp = y4 * (y2 * ((k * y1) - (t * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = (x * c) * ((y0 * y2) - (y * i));
	double t_3 = j * (x * ((i * y1) - (b * y0)));
	double tmp;
	if (c <= -1.4e+228) {
		tmp = t_2;
	} else if (c <= -5.1e+196) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (c <= -5800000000.0) {
		tmp = t_2;
	} else if (c <= -6.5e-148) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (c <= -1.2e-233) {
		tmp = t_1;
	} else if (c <= 1.1e-158) {
		tmp = t_3;
	} else if (c <= 1.8e-99) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (c <= 2.6e-69) {
		tmp = t_3;
	} else if (c <= 8.5e+31) {
		tmp = t_1;
	} else {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y1 * (z * ((a * y3) - (i * k)))
	t_2 = (x * c) * ((y0 * y2) - (y * i))
	t_3 = j * (x * ((i * y1) - (b * y0)))
	tmp = 0
	if c <= -1.4e+228:
		tmp = t_2
	elif c <= -5.1e+196:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	elif c <= -5800000000.0:
		tmp = t_2
	elif c <= -6.5e-148:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	elif c <= -1.2e-233:
		tmp = t_1
	elif c <= 1.1e-158:
		tmp = t_3
	elif c <= 1.8e-99:
		tmp = a * (y1 * ((z * y3) - (x * y2)))
	elif c <= 2.6e-69:
		tmp = t_3
	elif c <= 8.5e+31:
		tmp = t_1
	else:
		tmp = y4 * (y2 * ((k * y1) - (t * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))))
	t_2 = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)))
	t_3 = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))))
	tmp = 0.0
	if (c <= -1.4e+228)
		tmp = t_2;
	elseif (c <= -5.1e+196)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	elseif (c <= -5800000000.0)
		tmp = t_2;
	elseif (c <= -6.5e-148)
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (c <= -1.2e-233)
		tmp = t_1;
	elseif (c <= 1.1e-158)
		tmp = t_3;
	elseif (c <= 1.8e-99)
		tmp = Float64(a * Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))));
	elseif (c <= 2.6e-69)
		tmp = t_3;
	elseif (c <= 8.5e+31)
		tmp = t_1;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(t * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = y1 * (z * ((a * y3) - (i * k)));
	t_2 = (x * c) * ((y0 * y2) - (y * i));
	t_3 = j * (x * ((i * y1) - (b * y0)));
	tmp = 0.0;
	if (c <= -1.4e+228)
		tmp = t_2;
	elseif (c <= -5.1e+196)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	elseif (c <= -5800000000.0)
		tmp = t_2;
	elseif (c <= -6.5e-148)
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	elseif (c <= -1.2e-233)
		tmp = t_1;
	elseif (c <= 1.1e-158)
		tmp = t_3;
	elseif (c <= 1.8e-99)
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	elseif (c <= 2.6e-69)
		tmp = t_3;
	elseif (c <= 8.5e+31)
		tmp = t_1;
	else
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.4e+228], t$95$2, If[LessEqual[c, -5.1e+196], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -5800000000.0], t$95$2, If[LessEqual[c, -6.5e-148], N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.2e-233], t$95$1, If[LessEqual[c, 1.1e-158], t$95$3, If[LessEqual[c, 1.8e-99], N[(a * N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.6e-69], t$95$3, If[LessEqual[c, 8.5e+31], t$95$1, N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if c < -1.4e228 or -5.10000000000000041e196 < c < -5.8e9

   1. Initial program 21.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 41.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in c around inf 57.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 59.3%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 59.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 59.3%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 59.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

      5. *-commutative 59.3%

         \[\leadsto \left(c \cdot x\right) \cdot \left(\color{blue}{y2 \cdot y0} - i \cdot y\right) \]

   6. Simplified 59.3%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y2 \cdot y0 - i \cdot y\right)} \]

   if -1.4e228 < c < -5.10000000000000041e196

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 54.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 54.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 54.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 54.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 54.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 54.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around -inf 64.0%

      \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(y3 \cdot y4\right) + i \cdot x\right)\right)} \]
   7. Step-by-step derivation

      1. +-commutative 64.0%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x + -1 \cdot \left(y3 \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 64.0%

         \[\leadsto j \cdot \left(y1 \cdot \left(i \cdot x + \color{blue}{\left(-y3 \cdot y4\right)}\right)\right) \]

      3. unsub-neg 64.0%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x - y3 \cdot y4\right)}\right) \]

      4. *-commutative 64.0%

         \[\leadsto j \cdot \left(y1 \cdot \left(i \cdot x - \color{blue}{y4 \cdot y3}\right)\right) \]

   8. Simplified 64.0%

      \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(i \cdot x - y4 \cdot y3\right)\right)} \]

   if -5.8e9 < c < -6.4999999999999997e-148

   1. Initial program 31.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 26.2%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in k around inf 57.3%

      \[\leadsto y4 \cdot \color{blue}{\left(k \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 57.3%

         \[\leadsto y4 \cdot \left(k \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 57.3%

         \[\leadsto y4 \cdot \left(k \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 57.3%

         \[\leadsto y4 \cdot \left(k \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

   6. Simplified 57.3%

      \[\leadsto y4 \cdot \color{blue}{\left(k \cdot \left(y1 \cdot y2 - b \cdot y\right)\right)} \]

   if -6.4999999999999997e-148 < c < -1.19999999999999995e-233 or 2.6000000000000002e-69 < c < 8.49999999999999947e31

   1. Initial program 39.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 47.7%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in z around inf 45.0%

      \[\leadsto \color{blue}{y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)} \]

   if -1.19999999999999995e-233 < c < 1.1000000000000001e-158 or 1.8e-99 < c < 2.6000000000000002e-69

   1. Initial program 32.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 43.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 43.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 43.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 43.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 43.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 46.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 1.1000000000000001e-158 < c < 1.8e-99

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 46.7%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 55.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.3%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 55.3%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 55.3%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 8.49999999999999947e31 < c

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.3%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in y2 around inf 46.3%

      \[\leadsto y4 \cdot \color{blue}{\left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 46.3%

         \[\leadsto y4 \cdot \left(y2 \cdot \left(\color{blue}{y1 \cdot k} - c \cdot t\right)\right) \]

      2. *-commutative 46.3%

         \[\leadsto y4 \cdot \left(y2 \cdot \left(y1 \cdot k - \color{blue}{t \cdot c}\right)\right) \]

   6. Simplified 46.3%

      \[\leadsto y4 \cdot \color{blue}{\left(y2 \cdot \left(y1 \cdot k - t \cdot c\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 51.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -1.4 \cdot 10^{+228}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq -5.1 \cdot 10^{+196}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;c \leq -5800000000:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq -6.5 \cdot 10^{-148}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq -1.2 \cdot 10^{-233}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;c \leq 1.1 \cdot 10^{-158}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 1.8 \cdot 10^{-99}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 2.6 \cdot 10^{-69}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 8.5 \cdot 10^{+31}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 21: 31.4% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ t_2 := j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_3 := y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{if}\;c \leq -3.5 \cdot 10^{+232}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq -1.26 \cdot 10^{+141}:\\ \;\;\;\;y3 \cdot \left(y0 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;c \leq -19000000000:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;c \leq -1.4 \cdot 10^{-149}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq -1.65 \cdot 10^{-239}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;c \leq 8.8 \cdot 10^{-155}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;c \leq 5.2 \cdot 10^{-98}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.55 \cdot 10^{-70}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;c \leq 1.25 \cdot 10^{+34}:\\ \;\;\;\;t\_3\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (* x c) (- (* y0 y2) (* y i))))
        (t_2 (* j (* x (- (* i y1) (* b y0)))))
        (t_3 (* y1 (* z (- (* a y3) (* i k))))))
   (if (<= c -3.5e+232)
     t_1
     (if (<= c -1.26e+141)
       (* y3 (* y0 (- (* j y5) (* z c))))
       (if (<= c -19000000000.0)
         t_1
         (if (<= c -1.4e-149)
           (* y4 (* k (- (* y1 y2) (* y b))))
           (if (<= c -1.65e-239)
             t_3
             (if (<= c 8.8e-155)
               t_2
               (if (<= c 5.2e-98)
                 (* a (* y1 (- (* z y3) (* x y2))))
                 (if (<= c 1.55e-70)
                   t_2
                   (if (<= c 1.25e+34)
                     t_3
                     (* y4 (* y2 (- (* k y1) (* t c)))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (x * c) * ((y0 * y2) - (y * i));
	double t_2 = j * (x * ((i * y1) - (b * y0)));
	double t_3 = y1 * (z * ((a * y3) - (i * k)));
	double tmp;
	if (c <= -3.5e+232) {
		tmp = t_1;
	} else if (c <= -1.26e+141) {
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	} else if (c <= -19000000000.0) {
		tmp = t_1;
	} else if (c <= -1.4e-149) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (c <= -1.65e-239) {
		tmp = t_3;
	} else if (c <= 8.8e-155) {
		tmp = t_2;
	} else if (c <= 5.2e-98) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (c <= 1.55e-70) {
		tmp = t_2;
	} else if (c <= 1.25e+34) {
		tmp = t_3;
	} else {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = (x * c) * ((y0 * y2) - (y * i))
    t_2 = j * (x * ((i * y1) - (b * y0)))
    t_3 = y1 * (z * ((a * y3) - (i * k)))
    if (c <= (-3.5d+232)) then
        tmp = t_1
    else if (c <= (-1.26d+141)) then
        tmp = y3 * (y0 * ((j * y5) - (z * c)))
    else if (c <= (-19000000000.0d0)) then
        tmp = t_1
    else if (c <= (-1.4d-149)) then
        tmp = y4 * (k * ((y1 * y2) - (y * b)))
    else if (c <= (-1.65d-239)) then
        tmp = t_3
    else if (c <= 8.8d-155) then
        tmp = t_2
    else if (c <= 5.2d-98) then
        tmp = a * (y1 * ((z * y3) - (x * y2)))
    else if (c <= 1.55d-70) then
        tmp = t_2
    else if (c <= 1.25d+34) then
        tmp = t_3
    else
        tmp = y4 * (y2 * ((k * y1) - (t * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (x * c) * ((y0 * y2) - (y * i));
	double t_2 = j * (x * ((i * y1) - (b * y0)));
	double t_3 = y1 * (z * ((a * y3) - (i * k)));
	double tmp;
	if (c <= -3.5e+232) {
		tmp = t_1;
	} else if (c <= -1.26e+141) {
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	} else if (c <= -19000000000.0) {
		tmp = t_1;
	} else if (c <= -1.4e-149) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (c <= -1.65e-239) {
		tmp = t_3;
	} else if (c <= 8.8e-155) {
		tmp = t_2;
	} else if (c <= 5.2e-98) {
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	} else if (c <= 1.55e-70) {
		tmp = t_2;
	} else if (c <= 1.25e+34) {
		tmp = t_3;
	} else {
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	}
	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 = j * (x * ((i * y1) - (b * y0)))
	t_3 = y1 * (z * ((a * y3) - (i * k)))
	tmp = 0
	if c <= -3.5e+232:
		tmp = t_1
	elif c <= -1.26e+141:
		tmp = y3 * (y0 * ((j * y5) - (z * c)))
	elif c <= -19000000000.0:
		tmp = t_1
	elif c <= -1.4e-149:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	elif c <= -1.65e-239:
		tmp = t_3
	elif c <= 8.8e-155:
		tmp = t_2
	elif c <= 5.2e-98:
		tmp = a * (y1 * ((z * y3) - (x * y2)))
	elif c <= 1.55e-70:
		tmp = t_2
	elif c <= 1.25e+34:
		tmp = t_3
	else:
		tmp = y4 * (y2 * ((k * y1) - (t * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)))
	t_2 = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))))
	t_3 = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))))
	tmp = 0.0
	if (c <= -3.5e+232)
		tmp = t_1;
	elseif (c <= -1.26e+141)
		tmp = Float64(y3 * Float64(y0 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (c <= -19000000000.0)
		tmp = t_1;
	elseif (c <= -1.4e-149)
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (c <= -1.65e-239)
		tmp = t_3;
	elseif (c <= 8.8e-155)
		tmp = t_2;
	elseif (c <= 5.2e-98)
		tmp = Float64(a * Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))));
	elseif (c <= 1.55e-70)
		tmp = t_2;
	elseif (c <= 1.25e+34)
		tmp = t_3;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(Float64(k * y1) - Float64(t * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (x * c) * ((y0 * y2) - (y * i));
	t_2 = j * (x * ((i * y1) - (b * y0)));
	t_3 = y1 * (z * ((a * y3) - (i * k)));
	tmp = 0.0;
	if (c <= -3.5e+232)
		tmp = t_1;
	elseif (c <= -1.26e+141)
		tmp = y3 * (y0 * ((j * y5) - (z * c)));
	elseif (c <= -19000000000.0)
		tmp = t_1;
	elseif (c <= -1.4e-149)
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	elseif (c <= -1.65e-239)
		tmp = t_3;
	elseif (c <= 8.8e-155)
		tmp = t_2;
	elseif (c <= 5.2e-98)
		tmp = a * (y1 * ((z * y3) - (x * y2)));
	elseif (c <= 1.55e-70)
		tmp = t_2;
	elseif (c <= 1.25e+34)
		tmp = t_3;
	else
		tmp = y4 * (y2 * ((k * y1) - (t * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -3.5e+232], t$95$1, If[LessEqual[c, -1.26e+141], N[(y3 * N[(y0 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -19000000000.0], t$95$1, If[LessEqual[c, -1.4e-149], N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.65e-239], t$95$3, If[LessEqual[c, 8.8e-155], t$95$2, If[LessEqual[c, 5.2e-98], N[(a * N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.55e-70], t$95$2, If[LessEqual[c, 1.25e+34], t$95$3, N[(y4 * N[(y2 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if c < -3.50000000000000013e232 or -1.25999999999999994e141 < c < -1.9e10

   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. Add Preprocessing

   3. Taylor expanded in x around inf 42.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in c around inf 58.8%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 61.0%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 61.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 61.0%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 61.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

      5. *-commutative 61.0%

         \[\leadsto \left(c \cdot x\right) \cdot \left(\color{blue}{y2 \cdot y0} - i \cdot y\right) \]

   6. Simplified 61.0%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y2 \cdot y0 - i \cdot y\right)} \]

   if -3.50000000000000013e232 < c < -1.25999999999999994e141

   1. Initial program 21.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 37.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y0 around inf 63.8%

      \[\leadsto -1 \cdot \left(y3 \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(j \cdot y5\right) + c \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. +-commutative 63.8%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot z + -1 \cdot \left(j \cdot y5\right)\right)}\right)\right) \]

      2. mul-1-neg 63.8%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y0 \cdot \left(c \cdot z + \color{blue}{\left(-j \cdot y5\right)}\right)\right)\right) \]

      3. unsub-neg 63.8%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot z - j \cdot y5\right)}\right)\right) \]

      4. *-commutative 63.8%

         \[\leadsto -1 \cdot \left(y3 \cdot \left(y0 \cdot \left(\color{blue}{z \cdot c} - j \cdot y5\right)\right)\right) \]

   6. Simplified 63.8%

      \[\leadsto -1 \cdot \left(y3 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot c - j \cdot y5\right)\right)}\right) \]

   if -1.9e10 < c < -1.3999999999999999e-149

   1. Initial program 31.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 26.2%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in k around inf 57.3%

      \[\leadsto y4 \cdot \color{blue}{\left(k \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 57.3%

         \[\leadsto y4 \cdot \left(k \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 57.3%

         \[\leadsto y4 \cdot \left(k \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 57.3%

         \[\leadsto y4 \cdot \left(k \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

   6. Simplified 57.3%

      \[\leadsto y4 \cdot \color{blue}{\left(k \cdot \left(y1 \cdot y2 - b \cdot y\right)\right)} \]

   if -1.3999999999999999e-149 < c < -1.64999999999999998e-239 or 1.55e-70 < c < 1.25e34

   1. Initial program 39.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 47.7%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in z around inf 45.0%

      \[\leadsto \color{blue}{y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)} \]

   if -1.64999999999999998e-239 < c < 8.7999999999999996e-155 or 5.20000000000000027e-98 < c < 1.55e-70

   1. Initial program 32.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 43.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 43.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 43.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 43.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 43.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 46.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 8.7999999999999996e-155 < c < 5.20000000000000027e-98

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 46.7%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 55.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 55.3%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 55.3%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 55.3%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 1.25e34 < c

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.3%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in y2 around inf 46.3%

      \[\leadsto y4 \cdot \color{blue}{\left(y2 \cdot \left(k \cdot y1 - c \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 46.3%

         \[\leadsto y4 \cdot \left(y2 \cdot \left(\color{blue}{y1 \cdot k} - c \cdot t\right)\right) \]

      2. *-commutative 46.3%

         \[\leadsto y4 \cdot \left(y2 \cdot \left(y1 \cdot k - \color{blue}{t \cdot c}\right)\right) \]

   6. Simplified 46.3%

      \[\leadsto y4 \cdot \color{blue}{\left(y2 \cdot \left(y1 \cdot k - t \cdot c\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 51.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;c \leq -3.5 \cdot 10^{+232}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq -1.26 \cdot 10^{+141}:\\ \;\;\;\;y3 \cdot \left(y0 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;c \leq -19000000000:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;c \leq -1.4 \cdot 10^{-149}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;c \leq -1.65 \cdot 10^{-239}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;c \leq 8.8 \cdot 10^{-155}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 5.2 \cdot 10^{-98}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;c \leq 1.55 \cdot 10^{-70}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;c \leq 1.25 \cdot 10^{+34}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 22: 30.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ t_2 := i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{if}\;t \leq -1.1 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -4 \cdot 10^{+16}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -2.4 \cdot 10^{-60}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -4.1 \cdot 10^{-100}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-131}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 2.2 \cdot 10^{-216}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{-101}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{+155}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (- (* z k) (* x j)))))
        (t_2 (* i (* y1 (- (* x j) (* z k))))))
   (if (<= t -1.1e+178)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= t -4e+16)
       (* a (* b (- (* x y) (* z t))))
       (if (<= t -2.4e-60)
         (* j (* y1 (- (* x i) (* y3 y4))))
         (if (<= t -4.1e-100)
           t_2
           (if (<= t -3.2e-131)
             t_1
             (if (<= t 2.2e-216)
               (* j (* x (- (* i y1) (* b y0))))
               (if (<= t 2.6e-101)
                 t_2
                 (if (<= t 6.8e+155) t_1 (* y4 (* y2 (* t (- c))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double t_2 = i * (y1 * ((x * j) - (z * k)));
	double tmp;
	if (t <= -1.1e+178) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -4e+16) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -2.4e-60) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (t <= -4.1e-100) {
		tmp = t_2;
	} else if (t <= -3.2e-131) {
		tmp = t_1;
	} else if (t <= 2.2e-216) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 2.6e-101) {
		tmp = t_2;
	} else if (t <= 6.8e+155) {
		tmp = t_1;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = b * (y0 * ((z * k) - (x * j)))
    t_2 = i * (y1 * ((x * j) - (z * k)))
    if (t <= (-1.1d+178)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-4d+16)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (t <= (-2.4d-60)) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else if (t <= (-4.1d-100)) then
        tmp = t_2
    else if (t <= (-3.2d-131)) then
        tmp = t_1
    else if (t <= 2.2d-216) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 2.6d-101) then
        tmp = t_2
    else if (t <= 6.8d+155) then
        tmp = t_1
    else
        tmp = y4 * (y2 * (t * -c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double t_2 = i * (y1 * ((x * j) - (z * k)));
	double tmp;
	if (t <= -1.1e+178) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -4e+16) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -2.4e-60) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (t <= -4.1e-100) {
		tmp = t_2;
	} else if (t <= -3.2e-131) {
		tmp = t_1;
	} else if (t <= 2.2e-216) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 2.6e-101) {
		tmp = t_2;
	} else if (t <= 6.8e+155) {
		tmp = t_1;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y0 * ((z * k) - (x * j)))
	t_2 = i * (y1 * ((x * j) - (z * k)))
	tmp = 0
	if t <= -1.1e+178:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -4e+16:
		tmp = a * (b * ((x * y) - (z * t)))
	elif t <= -2.4e-60:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	elif t <= -4.1e-100:
		tmp = t_2
	elif t <= -3.2e-131:
		tmp = t_1
	elif t <= 2.2e-216:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 2.6e-101:
		tmp = t_2
	elif t <= 6.8e+155:
		tmp = t_1
	else:
		tmp = y4 * (y2 * (t * -c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	t_2 = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))))
	tmp = 0.0
	if (t <= -1.1e+178)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -4e+16)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= -2.4e-60)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	elseif (t <= -4.1e-100)
		tmp = t_2;
	elseif (t <= -3.2e-131)
		tmp = t_1;
	elseif (t <= 2.2e-216)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 2.6e-101)
		tmp = t_2;
	elseif (t <= 6.8e+155)
		tmp = t_1;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y0 * ((z * k) - (x * j)));
	t_2 = i * (y1 * ((x * j) - (z * k)));
	tmp = 0.0;
	if (t <= -1.1e+178)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -4e+16)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (t <= -2.4e-60)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	elseif (t <= -4.1e-100)
		tmp = t_2;
	elseif (t <= -3.2e-131)
		tmp = t_1;
	elseif (t <= 2.2e-216)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 2.6e-101)
		tmp = t_2;
	elseif (t <= 6.8e+155)
		tmp = t_1;
	else
		tmp = y4 * (y2 * (t * -c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.1e+178], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4e+16], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.4e-60], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.1e-100], t$95$2, If[LessEqual[t, -3.2e-131], t$95$1, If[LessEqual[t, 2.2e-216], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.6e-101], t$95$2, If[LessEqual[t, 6.8e+155], t$95$1, N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -1.09999999999999999e178

   1. Initial program 17.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in t around inf 53.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.09999999999999999e178 < t < -4e16

   1. Initial program 30.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 34.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 44.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -4e16 < t < -2.40000000000000009e-60

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 64.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 64.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 64.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 64.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 64.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 64.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around -inf 58.0%

      \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(y3 \cdot y4\right) + i \cdot x\right)\right)} \]
   7. Step-by-step derivation

      1. +-commutative 58.0%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x + -1 \cdot \left(y3 \cdot y4\right)\right)}\right) \]

      2. mul-1-neg 58.0%

         \[\leadsto j \cdot \left(y1 \cdot \left(i \cdot x + \color{blue}{\left(-y3 \cdot y4\right)}\right)\right) \]

      3. unsub-neg 58.0%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x - y3 \cdot y4\right)}\right) \]

      4. *-commutative 58.0%

         \[\leadsto j \cdot \left(y1 \cdot \left(i \cdot x - \color{blue}{y4 \cdot y3}\right)\right) \]

   8. Simplified 58.0%

      \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(i \cdot x - y4 \cdot y3\right)\right)} \]

   if -2.40000000000000009e-60 < t < -4.0999999999999999e-100 or 2.1999999999999999e-216 < t < 2.6000000000000001e-101

   1. Initial program 29.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 54.8%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in i around inf 55.4%

      \[\leadsto \color{blue}{i \cdot \left(y1 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if -4.0999999999999999e-100 < t < -3.2e-131 or 2.6000000000000001e-101 < t < 6.8000000000000002e155

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 32.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 37.8%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if -3.2e-131 < t < 2.1999999999999999e-216

   1. Initial program 31.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 30.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 30.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 30.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 30.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 30.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 30.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 37.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 6.8000000000000002e155 < t

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 57.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 64.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 67.3%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 67.3%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 70.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 47.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.1 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -4 \cdot 10^{+16}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -2.4 \cdot 10^{-60}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -4.1 \cdot 10^{-100}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-131}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.2 \cdot 10^{-216}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{-101}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{+155}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 23: 32.3% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -1.22 \cdot 10^{+119}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -5.8 \cdot 10^{+45}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -13.6:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1.18 \cdot 10^{-42}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -9.2 \cdot 10^{-251}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-296}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 3.3 \cdot 10^{-177}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y \leq 0.01:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* t (* y2 (- (* a y5) (* c y4))))))
   (if (<= y -1.22e+119)
     (* x (* y (- (* a b) (* c i))))
     (if (<= y -5.8e+45)
       (* a (* b (- (* x y) (* z t))))
       (if (<= y -13.6)
         (* j (* y5 (- (* y0 y3) (* t i))))
         (if (<= y -1.18e-42)
           (* y1 (- (* y4 (- (* k y2) (* j y3))) (* i (- (* z k) (* x j)))))
           (if (<= y -9.2e-251)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= y 3e-296)
               t_1
               (if (<= y 3.3e-177)
                 (* y1 (* z (- (* a y3) (* i k))))
                 (if (<= y 0.01)
                   t_1
                   (* y4 (* k (- (* y1 y2) (* 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 t_1 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (y <= -1.22e+119) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -5.8e+45) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= -13.6) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (y <= -1.18e-42) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -9.2e-251) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3e-296) {
		tmp = t_1;
	} else if (y <= 3.3e-177) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (y <= 0.01) {
		tmp = t_1;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (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) :: t_1
    real(8) :: tmp
    t_1 = t * (y2 * ((a * y5) - (c * y4)))
    if (y <= (-1.22d+119)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y <= (-5.8d+45)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y <= (-13.6d0)) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (y <= (-1.18d-42)) then
        tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
    else if (y <= (-9.2d-251)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y <= 3d-296) then
        tmp = t_1
    else if (y <= 3.3d-177) then
        tmp = y1 * (z * ((a * y3) - (i * k)))
    else if (y <= 0.01d0) then
        tmp = t_1
    else
        tmp = y4 * (k * ((y1 * y2) - (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 t_1 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (y <= -1.22e+119) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y <= -5.8e+45) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= -13.6) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (y <= -1.18e-42) {
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	} else if (y <= -9.2e-251) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3e-296) {
		tmp = t_1;
	} else if (y <= 3.3e-177) {
		tmp = y1 * (z * ((a * y3) - (i * k)));
	} else if (y <= 0.01) {
		tmp = t_1;
	} else {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = t * (y2 * ((a * y5) - (c * y4)))
	tmp = 0
	if y <= -1.22e+119:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y <= -5.8e+45:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y <= -13.6:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif y <= -1.18e-42:
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))))
	elif y <= -9.2e-251:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y <= 3e-296:
		tmp = t_1
	elif y <= 3.3e-177:
		tmp = y1 * (z * ((a * y3) - (i * k)))
	elif y <= 0.01:
		tmp = t_1
	else:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))))
	tmp = 0.0
	if (y <= -1.22e+119)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y <= -5.8e+45)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y <= -13.6)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (y <= -1.18e-42)
		tmp = Float64(y1 * Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(i * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (y <= -9.2e-251)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y <= 3e-296)
		tmp = t_1;
	elseif (y <= 3.3e-177)
		tmp = Float64(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))));
	elseif (y <= 0.01)
		tmp = t_1;
	else
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(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)
	t_1 = t * (y2 * ((a * y5) - (c * y4)));
	tmp = 0.0;
	if (y <= -1.22e+119)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y <= -5.8e+45)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y <= -13.6)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (y <= -1.18e-42)
		tmp = y1 * ((y4 * ((k * y2) - (j * y3))) - (i * ((z * k) - (x * j))));
	elseif (y <= -9.2e-251)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y <= 3e-296)
		tmp = t_1;
	elseif (y <= 3.3e-177)
		tmp = y1 * (z * ((a * y3) - (i * k)));
	elseif (y <= 0.01)
		tmp = t_1;
	else
		tmp = y4 * (k * ((y1 * y2) - (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_] := Block[{t$95$1 = N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -1.22e+119], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -5.8e+45], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -13.6], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.18e-42], N[(y1 * N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -9.2e-251], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3e-296], t$95$1, If[LessEqual[y, 3.3e-177], N[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 0.01], t$95$1, N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y < -1.2200000000000001e119

   1. Initial program 14.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in x around inf 64.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y around inf 56.9%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if -1.2200000000000001e119 < y < -5.7999999999999994e45

   1. Initial program 21.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 57.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 71.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -5.7999999999999994e45 < y < -13.5999999999999996

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 57.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 57.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 57.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 57.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 57.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 57.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around -inf 71.7%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 71.7%

         \[\leadsto \color{blue}{\left(-1 \cdot j\right) \cdot \left(y5 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      2. neg-mul-1 71.7%

         \[\leadsto \color{blue}{\left(-j\right)} \cdot \left(y5 \cdot \left(i \cdot t - y0 \cdot y3\right)\right) \]

      3. *-commutative 71.7%

         \[\leadsto \left(-j\right) \cdot \left(y5 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 71.7%

      \[\leadsto \color{blue}{\left(-j\right) \cdot \left(y5 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   if -13.5999999999999996 < y < -1.17999999999999995e-42

   1. Initial program 63.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 64.8%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around 0 56.5%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 56.5%

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - \color{blue}{\left(-1 \cdot i\right) \cdot \left(j \cdot x - k \cdot z\right)}\right) \]

      2. neg-mul-1 56.5%

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - \color{blue}{\left(-i\right)} \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 56.5%

         \[\leadsto y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - \left(-i\right) \cdot \left(j \cdot x - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 56.5%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - \left(-i\right) \cdot \left(j \cdot x - z \cdot k\right)\right)} \]

   if -1.17999999999999995e-42 < y < -9.20000000000000068e-251

   1. Initial program 31.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 40.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 40.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 40.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 40.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 40.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 40.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 46.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if -9.20000000000000068e-251 < y < 2.9999999999999997e-296 or 3.3e-177 < y < 0.0100000000000000002

   1. Initial program 31.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 41.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 49.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if 2.9999999999999997e-296 < y < 3.3e-177

   1. Initial program 40.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 36.9%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in z around inf 53.1%

      \[\leadsto \color{blue}{y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)} \]

   if 0.0100000000000000002 < y

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 40.3%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in k around inf 52.4%

      \[\leadsto y4 \cdot \color{blue}{\left(k \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 52.4%

         \[\leadsto y4 \cdot \left(k \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)}\right) \]

      2. mul-1-neg 52.4%

         \[\leadsto y4 \cdot \left(k \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right)\right) \]

      3. unsub-neg 52.4%

         \[\leadsto y4 \cdot \left(k \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)}\right) \]

   6. Simplified 52.4%

      \[\leadsto y4 \cdot \color{blue}{\left(k \cdot \left(y1 \cdot y2 - b \cdot y\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 53.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1.22 \cdot 10^{+119}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -5.8 \cdot 10^{+45}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq -13.6:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1.18 \cdot 10^{-42}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - i \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -9.2 \cdot 10^{-251}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-296}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 3.3 \cdot 10^{-177}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;y \leq 0.01:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 24: 32.2% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ t_2 := t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{if}\;z \leq -1.65 \cdot 10^{+171}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq -5.4 \cdot 10^{-122}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -3.15 \cdot 10^{-187}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;z \leq -6 \cdot 10^{-252}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 3.8 \cdot 10^{-99}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+138}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y1 (* z (- (* a y3) (* i k)))))
        (t_2 (* t (* y2 (- (* a y5) (* c y4))))))
   (if (<= z -1.65e+171)
     t_1
     (if (<= z -5.4e-122)
       (* j (* x (- (* i y1) (* b y0))))
       (if (<= z -3.15e-187)
         t_2
         (if (<= z -6e-252)
           (* x (* y (- (* a b) (* c i))))
           (if (<= z 3.8e-99)
             (* j (* y3 (- (* y0 y5) (* y1 y4))))
             (if (<= z 1.8e+138) 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 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (z <= -1.65e+171) {
		tmp = t_1;
	} else if (z <= -5.4e-122) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= -3.15e-187) {
		tmp = t_2;
	} else if (z <= -6e-252) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 3.8e-99) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (z <= 1.8e+138) {
		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 = y1 * (z * ((a * y3) - (i * k)))
    t_2 = t * (y2 * ((a * y5) - (c * y4)))
    if (z <= (-1.65d+171)) then
        tmp = t_1
    else if (z <= (-5.4d-122)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (z <= (-3.15d-187)) then
        tmp = t_2
    else if (z <= (-6d-252)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (z <= 3.8d-99) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (z <= 1.8d+138) 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 = y1 * (z * ((a * y3) - (i * k)));
	double t_2 = t * (y2 * ((a * y5) - (c * y4)));
	double tmp;
	if (z <= -1.65e+171) {
		tmp = t_1;
	} else if (z <= -5.4e-122) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (z <= -3.15e-187) {
		tmp = t_2;
	} else if (z <= -6e-252) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (z <= 3.8e-99) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (z <= 1.8e+138) {
		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 = y1 * (z * ((a * y3) - (i * k)))
	t_2 = t * (y2 * ((a * y5) - (c * y4)))
	tmp = 0
	if z <= -1.65e+171:
		tmp = t_1
	elif z <= -5.4e-122:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif z <= -3.15e-187:
		tmp = t_2
	elif z <= -6e-252:
		tmp = x * (y * ((a * b) - (c * i)))
	elif z <= 3.8e-99:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif z <= 1.8e+138:
		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(y1 * Float64(z * Float64(Float64(a * y3) - Float64(i * k))))
	t_2 = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))))
	tmp = 0.0
	if (z <= -1.65e+171)
		tmp = t_1;
	elseif (z <= -5.4e-122)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (z <= -3.15e-187)
		tmp = t_2;
	elseif (z <= -6e-252)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (z <= 3.8e-99)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (z <= 1.8e+138)
		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 = y1 * (z * ((a * y3) - (i * k)));
	t_2 = t * (y2 * ((a * y5) - (c * y4)));
	tmp = 0.0;
	if (z <= -1.65e+171)
		tmp = t_1;
	elseif (z <= -5.4e-122)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (z <= -3.15e-187)
		tmp = t_2;
	elseif (z <= -6e-252)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (z <= 3.8e-99)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (z <= 1.8e+138)
		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[(y1 * N[(z * N[(N[(a * y3), $MachinePrecision] - N[(i * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.65e+171], t$95$1, If[LessEqual[z, -5.4e-122], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -3.15e-187], t$95$2, If[LessEqual[z, -6e-252], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.8e-99], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e+138], t$95$2, t$95$1]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -1.64999999999999996e171 or 1.8000000000000001e138 < z

   1. Initial program 24.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 44.6%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in z around inf 55.4%

      \[\leadsto \color{blue}{y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)} \]

   if -1.64999999999999996e171 < z < -5.40000000000000019e-122

   1. Initial program 37.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 45.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 45.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 45.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 36.3%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if -5.40000000000000019e-122 < z < -3.14999999999999976e-187 or 3.7999999999999997e-99 < z < 1.8000000000000001e138

   1. Initial program 24.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 52.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 46.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if -3.14999999999999976e-187 < z < -5.9999999999999999e-252

   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. Add Preprocessing

   3. Taylor expanded in x around inf 46.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y around inf 56.9%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if -5.9999999999999999e-252 < z < 3.7999999999999997e-99

   1. Initial program 23.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 47.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 47.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 47.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 47.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 47.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 47.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y3 around inf 54.4%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 54.4%

         \[\leadsto j \cdot \left(y3 \cdot \left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right)\right) \]

      2. *-commutative 54.4%

         \[\leadsto j \cdot \left(y3 \cdot \left(y5 \cdot y0 - \color{blue}{y4 \cdot y1}\right)\right) \]

   8. Simplified 54.4%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y5 \cdot y0 - y4 \cdot y1\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 48.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.65 \cdot 10^{+171}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \mathbf{elif}\;z \leq -5.4 \cdot 10^{-122}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq -3.15 \cdot 10^{-187}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -6 \cdot 10^{-252}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 3.8 \cdot 10^{-99}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+138}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y1 \cdot \left(z \cdot \left(a \cdot y3 - i \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 25: 27.5% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -3.5 \cdot 10^{+162}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(t \cdot \left(-i\right)\right)\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-34}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -1.05 \cdot 10^{-211}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 3.4 \cdot 10^{-261}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+156}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -3.5e+162)
     (* (* j y5) (* t (- i)))
     (if (<= t -1.7e-34)
       (* a (* b (- (* x y) (* z t))))
       (if (<= t -1.05e-211)
         t_1
         (if (<= t 3.4e-261)
           (* (* x y) (* a b))
           (if (<= t 6.2e+156) t_1 (* y4 (* y2 (* t (- c)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -3.5e+162) {
		tmp = (j * y5) * (t * -i);
	} else if (t <= -1.7e-34) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -1.05e-211) {
		tmp = t_1;
	} else if (t <= 3.4e-261) {
		tmp = (x * y) * (a * b);
	} else if (t <= 6.2e+156) {
		tmp = t_1;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (y0 * ((z * k) - (x * j)))
    if (t <= (-3.5d+162)) then
        tmp = (j * y5) * (t * -i)
    else if (t <= (-1.7d-34)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (t <= (-1.05d-211)) then
        tmp = t_1
    else if (t <= 3.4d-261) then
        tmp = (x * y) * (a * b)
    else if (t <= 6.2d+156) then
        tmp = t_1
    else
        tmp = y4 * (y2 * (t * -c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -3.5e+162) {
		tmp = (j * y5) * (t * -i);
	} else if (t <= -1.7e-34) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= -1.05e-211) {
		tmp = t_1;
	} else if (t <= 3.4e-261) {
		tmp = (x * y) * (a * b);
	} else if (t <= 6.2e+156) {
		tmp = t_1;
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -3.5e+162:
		tmp = (j * y5) * (t * -i)
	elif t <= -1.7e-34:
		tmp = a * (b * ((x * y) - (z * t)))
	elif t <= -1.05e-211:
		tmp = t_1
	elif t <= 3.4e-261:
		tmp = (x * y) * (a * b)
	elif t <= 6.2e+156:
		tmp = t_1
	else:
		tmp = y4 * (y2 * (t * -c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -3.5e+162)
		tmp = Float64(Float64(j * y5) * Float64(t * Float64(-i)));
	elseif (t <= -1.7e-34)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= -1.05e-211)
		tmp = t_1;
	elseif (t <= 3.4e-261)
		tmp = Float64(Float64(x * y) * Float64(a * b));
	elseif (t <= 6.2e+156)
		tmp = t_1;
	else
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -3.5e+162)
		tmp = (j * y5) * (t * -i);
	elseif (t <= -1.7e-34)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (t <= -1.05e-211)
		tmp = t_1;
	elseif (t <= 3.4e-261)
		tmp = (x * y) * (a * b);
	elseif (t <= 6.2e+156)
		tmp = t_1;
	else
		tmp = y4 * (y2 * (t * -c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.5e+162], N[(N[(j * y5), $MachinePrecision] * N[(t * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.7e-34], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.05e-211], t$95$1, If[LessEqual[t, 3.4e-261], N[(N[(x * y), $MachinePrecision] * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.2e+156], t$95$1, N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -3.50000000000000018e162

   1. Initial program 19.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 39.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 39.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 39.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 46.9%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 46.5%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 46.5%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 46.5%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 46.5%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around inf 50.5%

      \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(i \cdot t\right)}\right) \]
   10. Step-by-step derivation

       1. *-commutative 50.5%

          \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(t \cdot i\right)}\right) \]

   11. Simplified 50.5%

       \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(t \cdot i\right)}\right) \]

   if -3.50000000000000018e162 < t < -1.7e-34

   1. Initial program 28.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 35.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 41.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -1.7e-34 < t < -1.05000000000000004e-211 or 3.4e-261 < t < 6.2000000000000004e156

   1. Initial program 30.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 30.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 34.1%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if -1.05000000000000004e-211 < t < 3.4e-261

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 33.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 31.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 31.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. add0 31.2%

         \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right) + 0} \]

      2. associate-*r* 34.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(x \cdot y\right)} + 0 \]

      3. *-commutative 34.1%

         \[\leadsto \left(a \cdot b\right) \cdot \color{blue}{\left(y \cdot x\right)} + 0 \]

   7. Applied egg-rr 34.1%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right) + 0} \]
   8. Step-by-step derivation

      1. add0 34.1%

         \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

   9. Simplified 34.1%

      \[\leadsto \color{blue}{\left(a \cdot b\right) \cdot \left(y \cdot x\right)} \]

   if 6.2000000000000004e156 < t

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 57.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 64.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 67.3%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 67.3%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 70.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 41.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.5 \cdot 10^{+162}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(t \cdot \left(-i\right)\right)\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-34}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -1.05 \cdot 10^{-211}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 3.4 \cdot 10^{-261}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+156}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 26: 30.7% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -2.35 \cdot 10^{+179}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -9.2 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-218}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.6 \cdot 10^{-102}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{+159}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -2.35e+179)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -9.2e-35)
     (* a (* b (- (* x y) (* z t))))
     (if (<= t 2e-218)
       (* j (* x (- (* i y1) (* b y0))))
       (if (<= t 6.6e-102)
         (* i (* y1 (- (* x j) (* z k))))
         (if (<= t 4.8e+159)
           (* b (* y0 (- (* z k) (* x j))))
           (* y4 (* y2 (* t (- c))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -2.35e+179) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -9.2e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= 2e-218) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 6.6e-102) {
		tmp = i * (y1 * ((x * j) - (z * k)));
	} else if (t <= 4.8e+159) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (t <= (-2.35d+179)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-9.2d-35)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (t <= 2d-218) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 6.6d-102) then
        tmp = i * (y1 * ((x * j) - (z * k)))
    else if (t <= 4.8d+159) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else
        tmp = y4 * (y2 * (t * -c))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -2.35e+179) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -9.2e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (t <= 2e-218) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 6.6e-102) {
		tmp = i * (y1 * ((x * j) - (z * k)));
	} else if (t <= 4.8e+159) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = y4 * (y2 * (t * -c));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if t <= -2.35e+179:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -9.2e-35:
		tmp = a * (b * ((x * y) - (z * t)))
	elif t <= 2e-218:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 6.6e-102:
		tmp = i * (y1 * ((x * j) - (z * k)))
	elif t <= 4.8e+159:
		tmp = b * (y0 * ((z * k) - (x * j)))
	else:
		tmp = y4 * (y2 * (t * -c))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (t <= -2.35e+179)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -9.2e-35)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= 2e-218)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 6.6e-102)
		tmp = Float64(i * Float64(y1 * Float64(Float64(x * j) - Float64(z * k))));
	elseif (t <= 4.8e+159)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	else
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (t <= -2.35e+179)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -9.2e-35)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (t <= 2e-218)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 6.6e-102)
		tmp = i * (y1 * ((x * j) - (z * k)));
	elseif (t <= 4.8e+159)
		tmp = b * (y0 * ((z * k) - (x * j)));
	else
		tmp = y4 * (y2 * (t * -c));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -2.35e+179], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -9.2e-35], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2e-218], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.6e-102], N[(i * N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.8e+159], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -2.35000000000000003e179

   1. Initial program 17.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 43.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 43.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 43.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in t around inf 53.2%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -2.35000000000000003e179 < t < -9.1999999999999996e-35

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 32.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 41.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -9.1999999999999996e-35 < t < 2.0000000000000001e-218

   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. Add Preprocessing

   3. Taylor expanded in j around inf 36.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 36.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 36.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 36.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 36.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 36.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 33.3%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 2.0000000000000001e-218 < t < 6.6e-102

   1. Initial program 32.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 52.6%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in i around inf 49.2%

      \[\leadsto \color{blue}{i \cdot \left(y1 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 6.6e-102 < t < 4.8e159

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 32.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 38.8%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if 4.8e159 < t

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 57.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 64.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 64.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 67.3%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 67.3%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 70.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 70.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 43.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.35 \cdot 10^{+179}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -9.2 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-218}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.6 \cdot 10^{-102}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{+159}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 27: 30.8% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -4.2 \cdot 10^{+108}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{-112}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -9.2 \cdot 10^{-221}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 8.6 \cdot 10^{+70}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 9.2 \cdot 10^{+213}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= j -4.2e+108)
   (* j (* y3 (- (* y0 y5) (* y1 y4))))
   (if (<= j -1.15e-112)
     (* k (* y1 (- (* y2 y4) (* z i))))
     (if (<= j -9.2e-221)
       (* a (* b (- (* x y) (* z t))))
       (if (<= j 8.6e+70)
         (* t (* y2 (- (* a y5) (* c y4))))
         (if (<= j 9.2e+213)
           (* j (* t (- (* b y4) (* i y5))))
           (* j (* x (- (* 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 tmp;
	if (j <= -4.2e+108) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (j <= -1.15e-112) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (j <= -9.2e-221) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 8.6e+70) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 9.2e+213) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else {
		tmp = j * (x * ((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) :: tmp
    if (j <= (-4.2d+108)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (j <= (-1.15d-112)) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (j <= (-9.2d-221)) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (j <= 8.6d+70) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (j <= 9.2d+213) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else
        tmp = j * (x * ((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 tmp;
	if (j <= -4.2e+108) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (j <= -1.15e-112) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (j <= -9.2e-221) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (j <= 8.6e+70) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= 9.2e+213) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else {
		tmp = j * (x * ((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):
	tmp = 0
	if j <= -4.2e+108:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif j <= -1.15e-112:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif j <= -9.2e-221:
		tmp = a * (b * ((x * y) - (z * t)))
	elif j <= 8.6e+70:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif j <= 9.2e+213:
		tmp = j * (t * ((b * y4) - (i * y5)))
	else:
		tmp = j * (x * ((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)
	tmp = 0.0
	if (j <= -4.2e+108)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (j <= -1.15e-112)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (j <= -9.2e-221)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (j <= 8.6e+70)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (j <= 9.2e+213)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	else
		tmp = Float64(j * Float64(x * 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)
	tmp = 0.0;
	if (j <= -4.2e+108)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (j <= -1.15e-112)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (j <= -9.2e-221)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (j <= 8.6e+70)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (j <= 9.2e+213)
		tmp = j * (t * ((b * y4) - (i * y5)));
	else
		tmp = j * (x * ((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_] := If[LessEqual[j, -4.2e+108], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.15e-112], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -9.2e-221], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 8.6e+70], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 9.2e+213], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -4.20000000000000019e108

   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. Add Preprocessing

   3. Taylor expanded in j around inf 60.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 60.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 60.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 60.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 60.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 60.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y3 around inf 52.4%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 52.4%

         \[\leadsto j \cdot \left(y3 \cdot \left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right)\right) \]

      2. *-commutative 52.4%

         \[\leadsto j \cdot \left(y3 \cdot \left(y5 \cdot y0 - \color{blue}{y4 \cdot y1}\right)\right) \]

   8. Simplified 52.4%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y5 \cdot y0 - y4 \cdot y1\right)\right)} \]

   if -4.20000000000000019e108 < j < -1.14999999999999995e-112

   1. Initial program 36.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 47.9%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in k around inf 35.7%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]

   if -1.14999999999999995e-112 < j < -9.2e-221

   1. Initial program 24.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 49.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 46.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -9.2e-221 < j < 8.6000000000000002e70

   1. Initial program 31.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 41.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 42.1%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if 8.6000000000000002e70 < j < 9.19999999999999992e213

   1. Initial program 21.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 36.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 36.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 36.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 36.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 36.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 36.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in t around inf 36.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if 9.19999999999999992e213 < j

   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. Add Preprocessing

   3. Taylor expanded in j around inf 66.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 66.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 66.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 66.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 66.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 66.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 44.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -4.2 \cdot 10^{+108}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{-112}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -9.2 \cdot 10^{-221}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 8.6 \cdot 10^{+70}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 9.2 \cdot 10^{+213}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 28: 26.4% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ t_2 := a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;y2 \leq -2.9 \cdot 10^{-39}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y2 \leq 9 \cdot 10^{-280}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y2 \leq 4.4 \cdot 10^{-24}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 1.55 \cdot 10^{+68}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* t (* y2 (- y4))))) (t_2 (* a (* b (- (* x y) (* z t))))))
   (if (<= y2 -2.9e-39)
     t_1
     (if (<= y2 9e-280)
       t_2
       (if (<= y2 4.4e-24)
         (* (- j) (* x (* b y0)))
         (if (<= y2 1.55e+68) 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 = c * (t * (y2 * -y4));
	double t_2 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y2 <= -2.9e-39) {
		tmp = t_1;
	} else if (y2 <= 9e-280) {
		tmp = t_2;
	} else if (y2 <= 4.4e-24) {
		tmp = -j * (x * (b * y0));
	} else if (y2 <= 1.55e+68) {
		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 = c * (t * (y2 * -y4))
    t_2 = a * (b * ((x * y) - (z * t)))
    if (y2 <= (-2.9d-39)) then
        tmp = t_1
    else if (y2 <= 9d-280) then
        tmp = t_2
    else if (y2 <= 4.4d-24) then
        tmp = -j * (x * (b * y0))
    else if (y2 <= 1.55d+68) 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 = c * (t * (y2 * -y4));
	double t_2 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y2 <= -2.9e-39) {
		tmp = t_1;
	} else if (y2 <= 9e-280) {
		tmp = t_2;
	} else if (y2 <= 4.4e-24) {
		tmp = -j * (x * (b * y0));
	} else if (y2 <= 1.55e+68) {
		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 = c * (t * (y2 * -y4))
	t_2 = a * (b * ((x * y) - (z * t)))
	tmp = 0
	if y2 <= -2.9e-39:
		tmp = t_1
	elif y2 <= 9e-280:
		tmp = t_2
	elif y2 <= 4.4e-24:
		tmp = -j * (x * (b * y0))
	elif y2 <= 1.55e+68:
		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(c * Float64(t * Float64(y2 * Float64(-y4))))
	t_2 = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (y2 <= -2.9e-39)
		tmp = t_1;
	elseif (y2 <= 9e-280)
		tmp = t_2;
	elseif (y2 <= 4.4e-24)
		tmp = Float64(Float64(-j) * Float64(x * Float64(b * y0)));
	elseif (y2 <= 1.55e+68)
		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 = c * (t * (y2 * -y4));
	t_2 = a * (b * ((x * y) - (z * t)));
	tmp = 0.0;
	if (y2 <= -2.9e-39)
		tmp = t_1;
	elseif (y2 <= 9e-280)
		tmp = t_2;
	elseif (y2 <= 4.4e-24)
		tmp = -j * (x * (b * y0));
	elseif (y2 <= 1.55e+68)
		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[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -2.9e-39], t$95$1, If[LessEqual[y2, 9e-280], t$95$2, If[LessEqual[y2, 4.4e-24], N[((-j) * N[(x * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 1.55e+68], t$95$2, t$95$1]]]]]]

Derivation

1. Split input into 3 regimes

2. if y2 < -2.89999999999999988e-39 or 1.5499999999999999e68 < y2

   1. Initial program 21.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 33.1%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 35.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 35.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 35.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 35.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 35.8%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. *-commutative 35.8%

         \[\leadsto -c \cdot \left(t \cdot \color{blue}{\left(y4 \cdot y2\right)}\right) \]

   9. Simplified 35.8%

      \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y4 \cdot y2\right)\right)} \]

   if -2.89999999999999988e-39 < y2 < 8.9999999999999991e-280 or 4.40000000000000003e-24 < y2 < 1.5499999999999999e68

   1. Initial program 30.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 40.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 36.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if 8.9999999999999991e-280 < y2 < 4.40000000000000003e-24

   1. Initial program 41.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 56.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 56.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 56.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 56.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 56.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 56.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 33.9%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around 0 29.6%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 29.6%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-b \cdot y0\right)}\right) \]

      2. distribute-rgt-neg-in 29.6%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]

   9. Simplified 29.6%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]
3. Recombined 3 regimes into one program.

4. Final simplification 34.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -2.9 \cdot 10^{-39}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 9 \cdot 10^{-280}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y2 \leq 4.4 \cdot 10^{-24}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 1.55 \cdot 10^{+68}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 29: 21.8% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ t_2 := c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{if}\;y3 \leq -1.45 \cdot 10^{-73}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y3 \leq 2.55 \cdot 10^{-104}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y3 \leq 9 \cdot 10^{+68}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;y3 \leq 2 \cdot 10^{+119}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* y1 (* z y3)))) (t_2 (* c (* t (* y2 (- y4))))))
   (if (<= y3 -1.45e-73)
     t_1
     (if (<= y3 2.55e-104)
       t_2
       (if (<= y3 9e+68) (* a (* y (* x b))) (if (<= y3 2e+119) t_2 t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (y1 * (z * y3));
	double t_2 = c * (t * (y2 * -y4));
	double tmp;
	if (y3 <= -1.45e-73) {
		tmp = t_1;
	} else if (y3 <= 2.55e-104) {
		tmp = t_2;
	} else if (y3 <= 9e+68) {
		tmp = a * (y * (x * b));
	} else if (y3 <= 2e+119) {
		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 = a * (y1 * (z * y3))
    t_2 = c * (t * (y2 * -y4))
    if (y3 <= (-1.45d-73)) then
        tmp = t_1
    else if (y3 <= 2.55d-104) then
        tmp = t_2
    else if (y3 <= 9d+68) then
        tmp = a * (y * (x * b))
    else if (y3 <= 2d+119) 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 = a * (y1 * (z * y3));
	double t_2 = c * (t * (y2 * -y4));
	double tmp;
	if (y3 <= -1.45e-73) {
		tmp = t_1;
	} else if (y3 <= 2.55e-104) {
		tmp = t_2;
	} else if (y3 <= 9e+68) {
		tmp = a * (y * (x * b));
	} else if (y3 <= 2e+119) {
		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 = a * (y1 * (z * y3))
	t_2 = c * (t * (y2 * -y4))
	tmp = 0
	if y3 <= -1.45e-73:
		tmp = t_1
	elif y3 <= 2.55e-104:
		tmp = t_2
	elif y3 <= 9e+68:
		tmp = a * (y * (x * b))
	elif y3 <= 2e+119:
		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(a * Float64(y1 * Float64(z * y3)))
	t_2 = Float64(c * Float64(t * Float64(y2 * Float64(-y4))))
	tmp = 0.0
	if (y3 <= -1.45e-73)
		tmp = t_1;
	elseif (y3 <= 2.55e-104)
		tmp = t_2;
	elseif (y3 <= 9e+68)
		tmp = Float64(a * Float64(y * Float64(x * b)));
	elseif (y3 <= 2e+119)
		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 = a * (y1 * (z * y3));
	t_2 = c * (t * (y2 * -y4));
	tmp = 0.0;
	if (y3 <= -1.45e-73)
		tmp = t_1;
	elseif (y3 <= 2.55e-104)
		tmp = t_2;
	elseif (y3 <= 9e+68)
		tmp = a * (y * (x * b));
	elseif (y3 <= 2e+119)
		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[(a * N[(y1 * N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y3, -1.45e-73], t$95$1, If[LessEqual[y3, 2.55e-104], t$95$2, If[LessEqual[y3, 9e+68], N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 2e+119], t$95$2, t$95$1]]]]]]

Derivation

1. Split input into 3 regimes

2. if y3 < -1.45e-73 or 1.99999999999999989e119 < y3

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 41.2%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 34.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 34.0%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 34.0%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 34.0%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 33.1%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]

   if -1.45e-73 < y3 < 2.54999999999999996e-104 or 9.0000000000000007e68 < y3 < 1.99999999999999989e119

   1. Initial program 24.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 31.6%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 22.4%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 22.4%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 22.4%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 29.9%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 29.9%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. *-commutative 29.9%

         \[\leadsto -c \cdot \left(t \cdot \color{blue}{\left(y4 \cdot y2\right)}\right) \]

   9. Simplified 29.9%

      \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y4 \cdot y2\right)\right)} \]

   if 2.54999999999999996e-104 < y3 < 9.0000000000000007e68

   1. Initial program 37.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 31.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 36.1%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 30.6%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 33.1%

         \[\leadsto a \cdot \color{blue}{\left(\left(b \cdot x\right) \cdot y\right)} \]

   7. Simplified 33.1%

      \[\leadsto \color{blue}{a \cdot \left(\left(b \cdot x\right) \cdot y\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 31.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -1.45 \cdot 10^{-73}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ \mathbf{elif}\;y3 \leq 2.55 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 9 \cdot 10^{+68}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;y3 \leq 2 \cdot 10^{+119}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 30: 23.1% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \mathbf{if}\;y0 \leq -5 \cdot 10^{-8}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq 9.5 \cdot 10^{-246}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 2.05 \cdot 10^{-20}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 9.6 \cdot 10^{+109}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (- j) (* x (* b y0)))))
   (if (<= y0 -5e-8)
     t_1
     (if (<= y0 9.5e-246)
       (* c (* t (* y2 (- y4))))
       (if (<= y0 2.05e-20)
         (* j (* y1 (* x i)))
         (if (<= y0 9.6e+109) (* j (* y0 (* y3 y5))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = -j * (x * (b * y0));
	double tmp;
	if (y0 <= -5e-8) {
		tmp = t_1;
	} else if (y0 <= 9.5e-246) {
		tmp = c * (t * (y2 * -y4));
	} else if (y0 <= 2.05e-20) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 9.6e+109) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = -j * (x * (b * y0))
    if (y0 <= (-5d-8)) then
        tmp = t_1
    else if (y0 <= 9.5d-246) then
        tmp = c * (t * (y2 * -y4))
    else if (y0 <= 2.05d-20) then
        tmp = j * (y1 * (x * i))
    else if (y0 <= 9.6d+109) then
        tmp = j * (y0 * (y3 * y5))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = -j * (x * (b * y0));
	double tmp;
	if (y0 <= -5e-8) {
		tmp = t_1;
	} else if (y0 <= 9.5e-246) {
		tmp = c * (t * (y2 * -y4));
	} else if (y0 <= 2.05e-20) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 9.6e+109) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = -j * (x * (b * y0))
	tmp = 0
	if y0 <= -5e-8:
		tmp = t_1
	elif y0 <= 9.5e-246:
		tmp = c * (t * (y2 * -y4))
	elif y0 <= 2.05e-20:
		tmp = j * (y1 * (x * i))
	elif y0 <= 9.6e+109:
		tmp = j * (y0 * (y3 * y5))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(-j) * Float64(x * Float64(b * y0)))
	tmp = 0.0
	if (y0 <= -5e-8)
		tmp = t_1;
	elseif (y0 <= 9.5e-246)
		tmp = Float64(c * Float64(t * Float64(y2 * Float64(-y4))));
	elseif (y0 <= 2.05e-20)
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	elseif (y0 <= 9.6e+109)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = -j * (x * (b * y0));
	tmp = 0.0;
	if (y0 <= -5e-8)
		tmp = t_1;
	elseif (y0 <= 9.5e-246)
		tmp = c * (t * (y2 * -y4));
	elseif (y0 <= 2.05e-20)
		tmp = j * (y1 * (x * i));
	elseif (y0 <= 9.6e+109)
		tmp = j * (y0 * (y3 * y5));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[((-j) * N[(x * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -5e-8], t$95$1, If[LessEqual[y0, 9.5e-246], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.05e-20], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 9.6e+109], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -4.9999999999999998e-8 or 9.59999999999999949e109 < y0

   1. Initial program 25.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 44.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 44.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 44.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 44.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 44.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 44.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 44.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around 0 38.1%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 38.1%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-b \cdot y0\right)}\right) \]

      2. distribute-rgt-neg-in 38.1%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]

   9. Simplified 38.1%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]

   if -4.9999999999999998e-8 < y0 < 9.5000000000000002e-246

   1. Initial program 31.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 28.5%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 28.6%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 28.6%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 28.6%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 28.9%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 28.9%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. *-commutative 28.9%

         \[\leadsto -c \cdot \left(t \cdot \color{blue}{\left(y4 \cdot y2\right)}\right) \]

   9. Simplified 28.9%

      \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y4 \cdot y2\right)\right)} \]

   if 9.5000000000000002e-246 < y0 < 2.05e-20

   1. Initial program 26.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 21.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 23.3%

      \[\leadsto j \cdot \color{blue}{\left(i \cdot \left(x \cdot y1\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 27.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   9. Simplified 27.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   if 2.05e-20 < y0 < 9.59999999999999949e109

   1. Initial program 29.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 40.3%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 40.2%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 40.2%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around 0 30.8%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.8%

          \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \]

   11. Simplified 30.8%

       \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y5 \cdot y3\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 32.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -5 \cdot 10^{-8}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 9.5 \cdot 10^{-246}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 2.05 \cdot 10^{-20}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 9.6 \cdot 10^{+109}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 31: 21.9% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -7.6 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 7.5 \cdot 10^{-247}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 5.3 \cdot 10^{-21}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 5.2 \cdot 10^{+107}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y0 -7.6e+141)
   (* b (* z (* k y0)))
   (if (<= y0 7.5e-247)
     (* y4 (* y2 (* t (- c))))
     (if (<= y0 5.3e-21)
       (* j (* y1 (* x i)))
       (if (<= y0 5.2e+107)
         (* j (* y0 (* y3 y5)))
         (* (- j) (* x (* 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 tmp;
	if (y0 <= -7.6e+141) {
		tmp = b * (z * (k * y0));
	} else if (y0 <= 7.5e-247) {
		tmp = y4 * (y2 * (t * -c));
	} else if (y0 <= 5.3e-21) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 5.2e+107) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = -j * (x * (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) :: tmp
    if (y0 <= (-7.6d+141)) then
        tmp = b * (z * (k * y0))
    else if (y0 <= 7.5d-247) then
        tmp = y4 * (y2 * (t * -c))
    else if (y0 <= 5.3d-21) then
        tmp = j * (y1 * (x * i))
    else if (y0 <= 5.2d+107) then
        tmp = j * (y0 * (y3 * y5))
    else
        tmp = -j * (x * (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 tmp;
	if (y0 <= -7.6e+141) {
		tmp = b * (z * (k * y0));
	} else if (y0 <= 7.5e-247) {
		tmp = y4 * (y2 * (t * -c));
	} else if (y0 <= 5.3e-21) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 5.2e+107) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = -j * (x * (b * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y0 <= -7.6e+141:
		tmp = b * (z * (k * y0))
	elif y0 <= 7.5e-247:
		tmp = y4 * (y2 * (t * -c))
	elif y0 <= 5.3e-21:
		tmp = j * (y1 * (x * i))
	elif y0 <= 5.2e+107:
		tmp = j * (y0 * (y3 * y5))
	else:
		tmp = -j * (x * (b * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y0 <= -7.6e+141)
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	elseif (y0 <= 7.5e-247)
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	elseif (y0 <= 5.3e-21)
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	elseif (y0 <= 5.2e+107)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	else
		tmp = Float64(Float64(-j) * Float64(x * 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)
	tmp = 0.0;
	if (y0 <= -7.6e+141)
		tmp = b * (z * (k * y0));
	elseif (y0 <= 7.5e-247)
		tmp = y4 * (y2 * (t * -c));
	elseif (y0 <= 5.3e-21)
		tmp = j * (y1 * (x * i));
	elseif (y0 <= 5.2e+107)
		tmp = j * (y0 * (y3 * y5));
	else
		tmp = -j * (x * (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_] := If[LessEqual[y0, -7.6e+141], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 7.5e-247], N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.3e-21], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.2e+107], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[((-j) * N[(x * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y0 < -7.59999999999999952e141

   1. Initial program 18.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 37.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in z around -inf 45.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(z \cdot \left(a \cdot t - k \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 45.8%

         \[\leadsto \color{blue}{-b \cdot \left(z \cdot \left(a \cdot t - k \cdot y0\right)\right)} \]

      2. associate-*r* 40.8%

         \[\leadsto -\color{blue}{\left(b \cdot z\right) \cdot \left(a \cdot t - k \cdot y0\right)} \]

      3. *-commutative 40.8%

         \[\leadsto -\left(b \cdot z\right) \cdot \left(\color{blue}{t \cdot a} - k \cdot y0\right) \]

      4. *-commutative 40.8%

         \[\leadsto -\left(b \cdot z\right) \cdot \left(t \cdot a - \color{blue}{y0 \cdot k}\right) \]

   6. Simplified 40.8%

      \[\leadsto \color{blue}{-\left(b \cdot z\right) \cdot \left(t \cdot a - y0 \cdot k\right)} \]

   7. Taylor expanded in t around 0 48.0%

      \[\leadsto -\color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 48.0%

         \[\leadsto -\color{blue}{\left(-b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]

      2. associate-*r* 43.0%

         \[\leadsto -\left(-b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)}\right) \]

      3. *-commutative 43.0%

         \[\leadsto -\left(-b \cdot \left(\color{blue}{\left(y0 \cdot k\right)} \cdot z\right)\right) \]

   9. Simplified 43.0%

      \[\leadsto -\color{blue}{\left(-b \cdot \left(\left(y0 \cdot k\right) \cdot z\right)\right)} \]

   if -7.59999999999999952e141 < y0 < 7.5e-247

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 31.1%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 28.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 28.5%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 28.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 25.6%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 25.6%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 27.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 27.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 27.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]

   if 7.5e-247 < y0 < 5.2999999999999999e-21

   1. Initial program 26.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 21.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 23.3%

      \[\leadsto j \cdot \color{blue}{\left(i \cdot \left(x \cdot y1\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 27.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   9. Simplified 27.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   if 5.2999999999999999e-21 < y0 < 5.2000000000000002e107

   1. Initial program 29.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 40.3%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 40.2%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 40.2%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around 0 30.8%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.8%

          \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \]

   11. Simplified 30.8%

       \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y5 \cdot y3\right)\right)} \]

   if 5.2000000000000002e107 < y0

   1. Initial program 21.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 42.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 42.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 42.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 42.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 45.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around 0 42.9%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 42.9%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-b \cdot y0\right)}\right) \]

      2. distribute-rgt-neg-in 42.9%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]

   9. Simplified 42.9%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 32.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -7.6 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 7.5 \cdot 10^{-247}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 5.3 \cdot 10^{-21}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 5.2 \cdot 10^{+107}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 32: 21.7% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -9.5 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 5 \cdot 10^{-246}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 1.85 \cdot 10^{-23}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 5.8 \cdot 10^{+112}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y0 -9.5e+141)
   (* b (* k (* z y0)))
   (if (<= y0 5e-246)
     (* y4 (* y2 (* t (- c))))
     (if (<= y0 1.85e-23)
       (* j (* y1 (* x i)))
       (if (<= y0 5.8e+112)
         (* j (* y0 (* y3 y5)))
         (* (- j) (* x (* 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 tmp;
	if (y0 <= -9.5e+141) {
		tmp = b * (k * (z * y0));
	} else if (y0 <= 5e-246) {
		tmp = y4 * (y2 * (t * -c));
	} else if (y0 <= 1.85e-23) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 5.8e+112) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = -j * (x * (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) :: tmp
    if (y0 <= (-9.5d+141)) then
        tmp = b * (k * (z * y0))
    else if (y0 <= 5d-246) then
        tmp = y4 * (y2 * (t * -c))
    else if (y0 <= 1.85d-23) then
        tmp = j * (y1 * (x * i))
    else if (y0 <= 5.8d+112) then
        tmp = j * (y0 * (y3 * y5))
    else
        tmp = -j * (x * (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 tmp;
	if (y0 <= -9.5e+141) {
		tmp = b * (k * (z * y0));
	} else if (y0 <= 5e-246) {
		tmp = y4 * (y2 * (t * -c));
	} else if (y0 <= 1.85e-23) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 5.8e+112) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = -j * (x * (b * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y0 <= -9.5e+141:
		tmp = b * (k * (z * y0))
	elif y0 <= 5e-246:
		tmp = y4 * (y2 * (t * -c))
	elif y0 <= 1.85e-23:
		tmp = j * (y1 * (x * i))
	elif y0 <= 5.8e+112:
		tmp = j * (y0 * (y3 * y5))
	else:
		tmp = -j * (x * (b * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y0 <= -9.5e+141)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (y0 <= 5e-246)
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	elseif (y0 <= 1.85e-23)
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	elseif (y0 <= 5.8e+112)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	else
		tmp = Float64(Float64(-j) * Float64(x * 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)
	tmp = 0.0;
	if (y0 <= -9.5e+141)
		tmp = b * (k * (z * y0));
	elseif (y0 <= 5e-246)
		tmp = y4 * (y2 * (t * -c));
	elseif (y0 <= 1.85e-23)
		tmp = j * (y1 * (x * i));
	elseif (y0 <= 5.8e+112)
		tmp = j * (y0 * (y3 * y5));
	else
		tmp = -j * (x * (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_] := If[LessEqual[y0, -9.5e+141], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5e-246], N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.85e-23], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.8e+112], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[((-j) * N[(x * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y0 < -9.49999999999999974e141

   1. Initial program 18.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 37.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in z around -inf 45.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(z \cdot \left(a \cdot t - k \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 45.8%

         \[\leadsto \color{blue}{-b \cdot \left(z \cdot \left(a \cdot t - k \cdot y0\right)\right)} \]

      2. associate-*r* 40.8%

         \[\leadsto -\color{blue}{\left(b \cdot z\right) \cdot \left(a \cdot t - k \cdot y0\right)} \]

      3. *-commutative 40.8%

         \[\leadsto -\left(b \cdot z\right) \cdot \left(\color{blue}{t \cdot a} - k \cdot y0\right) \]

      4. *-commutative 40.8%

         \[\leadsto -\left(b \cdot z\right) \cdot \left(t \cdot a - \color{blue}{y0 \cdot k}\right) \]

   6. Simplified 40.8%

      \[\leadsto \color{blue}{-\left(b \cdot z\right) \cdot \left(t \cdot a - y0 \cdot k\right)} \]

   7. Taylor expanded in t around 0 48.0%

      \[\leadsto -\color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 48.0%

         \[\leadsto -\color{blue}{\left(-b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]

      2. *-commutative 48.0%

         \[\leadsto -\left(-\color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right) \cdot b}\right) \]

      3. distribute-rgt-neg-in 48.0%

         \[\leadsto -\color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right) \cdot \left(-b\right)} \]

   9. Simplified 48.0%

      \[\leadsto -\color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right) \cdot \left(-b\right)} \]

   if -9.49999999999999974e141 < y0 < 4.9999999999999997e-246

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 31.1%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 28.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 28.5%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 28.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 25.6%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 25.6%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 27.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 27.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 27.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]

   if 4.9999999999999997e-246 < y0 < 1.8500000000000001e-23

   1. Initial program 26.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 21.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 23.3%

      \[\leadsto j \cdot \color{blue}{\left(i \cdot \left(x \cdot y1\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 27.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   9. Simplified 27.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   if 1.8500000000000001e-23 < y0 < 5.8000000000000004e112

   1. Initial program 29.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 40.3%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 40.2%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 40.2%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around 0 30.8%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 30.8%

          \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \]

   11. Simplified 30.8%

       \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y5 \cdot y3\right)\right)} \]

   if 5.8000000000000004e112 < y0

   1. Initial program 21.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 42.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 42.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 42.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 42.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 45.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around 0 42.9%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 42.9%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-b \cdot y0\right)}\right) \]

      2. distribute-rgt-neg-in 42.9%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]

   9. Simplified 42.9%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 33.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -9.5 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 5 \cdot 10^{-246}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 1.85 \cdot 10^{-23}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 5.8 \cdot 10^{+112}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 33: 21.8% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -6.6 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 5.9 \cdot 10^{-248}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 1.05 \cdot 10^{-20}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 1.26 \cdot 10^{+108}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y0 -6.6e+141)
   (* b (* k (* z y0)))
   (if (<= y0 5.9e-248)
     (* y4 (* y2 (* t (- c))))
     (if (<= y0 1.05e-20)
       (* j (* y1 (* x i)))
       (if (<= y0 1.26e+108)
         (* (* j y5) (* y0 y3))
         (* (- j) (* x (* 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 tmp;
	if (y0 <= -6.6e+141) {
		tmp = b * (k * (z * y0));
	} else if (y0 <= 5.9e-248) {
		tmp = y4 * (y2 * (t * -c));
	} else if (y0 <= 1.05e-20) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 1.26e+108) {
		tmp = (j * y5) * (y0 * y3);
	} else {
		tmp = -j * (x * (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) :: tmp
    if (y0 <= (-6.6d+141)) then
        tmp = b * (k * (z * y0))
    else if (y0 <= 5.9d-248) then
        tmp = y4 * (y2 * (t * -c))
    else if (y0 <= 1.05d-20) then
        tmp = j * (y1 * (x * i))
    else if (y0 <= 1.26d+108) then
        tmp = (j * y5) * (y0 * y3)
    else
        tmp = -j * (x * (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 tmp;
	if (y0 <= -6.6e+141) {
		tmp = b * (k * (z * y0));
	} else if (y0 <= 5.9e-248) {
		tmp = y4 * (y2 * (t * -c));
	} else if (y0 <= 1.05e-20) {
		tmp = j * (y1 * (x * i));
	} else if (y0 <= 1.26e+108) {
		tmp = (j * y5) * (y0 * y3);
	} else {
		tmp = -j * (x * (b * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y0 <= -6.6e+141:
		tmp = b * (k * (z * y0))
	elif y0 <= 5.9e-248:
		tmp = y4 * (y2 * (t * -c))
	elif y0 <= 1.05e-20:
		tmp = j * (y1 * (x * i))
	elif y0 <= 1.26e+108:
		tmp = (j * y5) * (y0 * y3)
	else:
		tmp = -j * (x * (b * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y0 <= -6.6e+141)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (y0 <= 5.9e-248)
		tmp = Float64(y4 * Float64(y2 * Float64(t * Float64(-c))));
	elseif (y0 <= 1.05e-20)
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	elseif (y0 <= 1.26e+108)
		tmp = Float64(Float64(j * y5) * Float64(y0 * y3));
	else
		tmp = Float64(Float64(-j) * Float64(x * 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)
	tmp = 0.0;
	if (y0 <= -6.6e+141)
		tmp = b * (k * (z * y0));
	elseif (y0 <= 5.9e-248)
		tmp = y4 * (y2 * (t * -c));
	elseif (y0 <= 1.05e-20)
		tmp = j * (y1 * (x * i));
	elseif (y0 <= 1.26e+108)
		tmp = (j * y5) * (y0 * y3);
	else
		tmp = -j * (x * (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_] := If[LessEqual[y0, -6.6e+141], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.9e-248], N[(y4 * N[(y2 * N[(t * (-c)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.05e-20], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.26e+108], N[(N[(j * y5), $MachinePrecision] * N[(y0 * y3), $MachinePrecision]), $MachinePrecision], N[((-j) * N[(x * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y0 < -6.5999999999999993e141

   1. Initial program 18.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 37.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in z around -inf 45.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(z \cdot \left(a \cdot t - k \cdot y0\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 45.8%

         \[\leadsto \color{blue}{-b \cdot \left(z \cdot \left(a \cdot t - k \cdot y0\right)\right)} \]

      2. associate-*r* 40.8%

         \[\leadsto -\color{blue}{\left(b \cdot z\right) \cdot \left(a \cdot t - k \cdot y0\right)} \]

      3. *-commutative 40.8%

         \[\leadsto -\left(b \cdot z\right) \cdot \left(\color{blue}{t \cdot a} - k \cdot y0\right) \]

      4. *-commutative 40.8%

         \[\leadsto -\left(b \cdot z\right) \cdot \left(t \cdot a - \color{blue}{y0 \cdot k}\right) \]

   6. Simplified 40.8%

      \[\leadsto \color{blue}{-\left(b \cdot z\right) \cdot \left(t \cdot a - y0 \cdot k\right)} \]

   7. Taylor expanded in t around 0 48.0%

      \[\leadsto -\color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 48.0%

         \[\leadsto -\color{blue}{\left(-b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]

      2. *-commutative 48.0%

         \[\leadsto -\left(-\color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right) \cdot b}\right) \]

      3. distribute-rgt-neg-in 48.0%

         \[\leadsto -\color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right) \cdot \left(-b\right)} \]

   9. Simplified 48.0%

      \[\leadsto -\color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right) \cdot \left(-b\right)} \]

   if -6.5999999999999993e141 < y0 < 5.89999999999999986e-248

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 31.1%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 28.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 28.5%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 28.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around 0 25.6%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 25.6%

         \[\leadsto y4 \cdot \color{blue}{\left(-c \cdot \left(t \cdot y2\right)\right)} \]

      2. associate-*r* 27.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(c \cdot t\right) \cdot y2}\right) \]

      3. *-commutative 27.5%

         \[\leadsto y4 \cdot \left(-\color{blue}{\left(t \cdot c\right)} \cdot y2\right) \]

   9. Simplified 27.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-\left(t \cdot c\right) \cdot y2\right)} \]

   if 5.89999999999999986e-248 < y0 < 1.0499999999999999e-20

   1. Initial program 26.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 31.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 21.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 23.3%

      \[\leadsto j \cdot \color{blue}{\left(i \cdot \left(x \cdot y1\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 27.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   9. Simplified 27.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   if 1.0499999999999999e-20 < y0 < 1.2600000000000001e108

   1. Initial program 29.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 46.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 46.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 46.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 40.3%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 40.2%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 40.2%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 40.2%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around 0 33.7%

      \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]
   10. Step-by-step derivation

       1. neg-mul-1 33.7%

          \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

       2. distribute-rgt-neg-in 33.7%

          \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(y0 \cdot \left(-y3\right)\right)}\right) \]

   11. Simplified 33.7%

       \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \color{blue}{\left(y0 \cdot \left(-y3\right)\right)}\right) \]

   if 1.2600000000000001e108 < y0

   1. Initial program 21.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 42.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 42.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 42.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 42.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 45.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around 0 42.9%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 42.9%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(-b \cdot y0\right)}\right) \]

      2. distribute-rgt-neg-in 42.9%

         \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]

   9. Simplified 42.9%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(b \cdot \left(-y0\right)\right)}\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 33.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -6.6 \cdot 10^{+141}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 5.9 \cdot 10^{-248}:\\ \;\;\;\;y4 \cdot \left(y2 \cdot \left(t \cdot \left(-c\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 1.05 \cdot 10^{-20}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 1.26 \cdot 10^{+108}:\\ \;\;\;\;\left(j \cdot y5\right) \cdot \left(y0 \cdot y3\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-j\right) \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 34: 23.0% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{if}\;i \leq -1.65 \cdot 10^{+35}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;i \leq -7.5 \cdot 10^{-248}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;i \leq 1.5 \cdot 10^{-210}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 3.4 \cdot 10^{+59}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* x (* i y1)))))
   (if (<= i -1.65e+35)
     t_1
     (if (<= i -7.5e-248)
       (* a (* (* x y) b))
       (if (<= i 1.5e-210)
         (* a (* z (* y1 y3)))
         (if (<= i 3.4e+59) (* j (* y0 (* y3 y5))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (x * (i * y1));
	double tmp;
	if (i <= -1.65e+35) {
		tmp = t_1;
	} else if (i <= -7.5e-248) {
		tmp = a * ((x * y) * b);
	} else if (i <= 1.5e-210) {
		tmp = a * (z * (y1 * y3));
	} else if (i <= 3.4e+59) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (x * (i * y1))
    if (i <= (-1.65d+35)) then
        tmp = t_1
    else if (i <= (-7.5d-248)) then
        tmp = a * ((x * y) * b)
    else if (i <= 1.5d-210) then
        tmp = a * (z * (y1 * y3))
    else if (i <= 3.4d+59) then
        tmp = j * (y0 * (y3 * y5))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (x * (i * y1));
	double tmp;
	if (i <= -1.65e+35) {
		tmp = t_1;
	} else if (i <= -7.5e-248) {
		tmp = a * ((x * y) * b);
	} else if (i <= 1.5e-210) {
		tmp = a * (z * (y1 * y3));
	} else if (i <= 3.4e+59) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (x * (i * y1))
	tmp = 0
	if i <= -1.65e+35:
		tmp = t_1
	elif i <= -7.5e-248:
		tmp = a * ((x * y) * b)
	elif i <= 1.5e-210:
		tmp = a * (z * (y1 * y3))
	elif i <= 3.4e+59:
		tmp = j * (y0 * (y3 * y5))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(x * Float64(i * y1)))
	tmp = 0.0
	if (i <= -1.65e+35)
		tmp = t_1;
	elseif (i <= -7.5e-248)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (i <= 1.5e-210)
		tmp = Float64(a * Float64(z * Float64(y1 * y3)));
	elseif (i <= 3.4e+59)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (x * (i * y1));
	tmp = 0.0;
	if (i <= -1.65e+35)
		tmp = t_1;
	elseif (i <= -7.5e-248)
		tmp = a * ((x * y) * b);
	elseif (i <= 1.5e-210)
		tmp = a * (z * (y1 * y3));
	elseif (i <= 3.4e+59)
		tmp = j * (y0 * (y3 * y5));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(x * N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -1.65e+35], t$95$1, If[LessEqual[i, -7.5e-248], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.5e-210], N[(a * N[(z * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.4e+59], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if i < -1.6500000000000001e35 or 3.40000000000000006e59 < i

   1. Initial program 20.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 36.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 36.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 36.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 36.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 36.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 36.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 32.6%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 30.0%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(i \cdot y1\right)}\right) \]

   if -1.6500000000000001e35 < i < -7.4999999999999994e-248

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 46.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 38.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 28.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if -7.4999999999999994e-248 < i < 1.5000000000000001e-210

   1. Initial program 37.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 45.5%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 42.6%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 42.6%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 42.6%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 42.6%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 32.4%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto a \cdot \color{blue}{\left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   9. Simplified 32.5%

      \[\leadsto \color{blue}{a \cdot \left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   if 1.5000000000000001e-210 < i < 3.40000000000000006e59

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 53.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 53.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 53.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 53.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 53.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 53.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 32.9%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 32.7%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 32.7%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 32.7%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 32.7%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around 0 28.3%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 28.3%

          \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \]

   11. Simplified 28.3%

       \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y5 \cdot y3\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 29.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -1.65 \cdot 10^{+35}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -7.5 \cdot 10^{-248}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;i \leq 1.5 \cdot 10^{-210}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 3.4 \cdot 10^{+59}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 35: 23.2% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -2.3 \cdot 10^{+37}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -6.2 \cdot 10^{-246}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;i \leq 1.7 \cdot 10^{-210}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 2.4 \cdot 10^{+65}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -2.3e+37)
   (* j (* x (* i y1)))
   (if (<= i -6.2e-246)
     (* a (* (* x y) b))
     (if (<= i 1.7e-210)
       (* a (* z (* y1 y3)))
       (if (<= i 2.4e+65) (* j (* y0 (* y3 y5))) (* j (* y1 (* x i))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (i <= -2.3e+37) {
		tmp = j * (x * (i * y1));
	} else if (i <= -6.2e-246) {
		tmp = a * ((x * y) * b);
	} else if (i <= 1.7e-210) {
		tmp = a * (z * (y1 * y3));
	} else if (i <= 2.4e+65) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = j * (y1 * (x * i));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (i <= (-2.3d+37)) then
        tmp = j * (x * (i * y1))
    else if (i <= (-6.2d-246)) then
        tmp = a * ((x * y) * b)
    else if (i <= 1.7d-210) then
        tmp = a * (z * (y1 * y3))
    else if (i <= 2.4d+65) then
        tmp = j * (y0 * (y3 * y5))
    else
        tmp = j * (y1 * (x * i))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (i <= -2.3e+37) {
		tmp = j * (x * (i * y1));
	} else if (i <= -6.2e-246) {
		tmp = a * ((x * y) * b);
	} else if (i <= 1.7e-210) {
		tmp = a * (z * (y1 * y3));
	} else if (i <= 2.4e+65) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = j * (y1 * (x * i));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if i <= -2.3e+37:
		tmp = j * (x * (i * y1))
	elif i <= -6.2e-246:
		tmp = a * ((x * y) * b)
	elif i <= 1.7e-210:
		tmp = a * (z * (y1 * y3))
	elif i <= 2.4e+65:
		tmp = j * (y0 * (y3 * y5))
	else:
		tmp = j * (y1 * (x * i))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (i <= -2.3e+37)
		tmp = Float64(j * Float64(x * Float64(i * y1)));
	elseif (i <= -6.2e-246)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (i <= 1.7e-210)
		tmp = Float64(a * Float64(z * Float64(y1 * y3)));
	elseif (i <= 2.4e+65)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	else
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (i <= -2.3e+37)
		tmp = j * (x * (i * y1));
	elseif (i <= -6.2e-246)
		tmp = a * ((x * y) * b);
	elseif (i <= 1.7e-210)
		tmp = a * (z * (y1 * y3));
	elseif (i <= 2.4e+65)
		tmp = j * (y0 * (y3 * y5));
	else
		tmp = j * (y1 * (x * i));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[i, -2.3e+37], N[(j * N[(x * N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -6.2e-246], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.7e-210], N[(a * N[(z * N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2.4e+65], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if i < -2.30000000000000002e37

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 33.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 33.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 33.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 33.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 33.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 33.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 28.9%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 25.3%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(i \cdot y1\right)}\right) \]

   if -2.30000000000000002e37 < i < -6.2000000000000001e-246

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 46.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 38.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 28.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if -6.2000000000000001e-246 < i < 1.69999999999999987e-210

   1. Initial program 37.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 45.5%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 42.6%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 42.6%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 42.6%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 42.6%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 32.4%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto a \cdot \color{blue}{\left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   9. Simplified 32.5%

      \[\leadsto \color{blue}{a \cdot \left(\left(y1 \cdot y3\right) \cdot z\right)} \]

   if 1.69999999999999987e-210 < i < 2.4000000000000002e65

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 53.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 53.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 53.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 53.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 53.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 53.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in y5 around inf 32.9%

      \[\leadsto \color{blue}{j \cdot \left(y5 \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 32.7%

         \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(i \cdot t\right) - -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      2. distribute-lft-out-- 32.7%

         \[\leadsto \left(j \cdot y5\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot t - y0 \cdot y3\right)\right)} \]

      3. *-commutative 32.7%

         \[\leadsto \left(j \cdot y5\right) \cdot \left(-1 \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   8. Simplified 32.7%

      \[\leadsto \color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   9. Taylor expanded in t around 0 28.3%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   10. Step-by-step derivation

       1. *-commutative 28.3%

          \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \]

   11. Simplified 28.3%

       \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y5 \cdot y3\right)\right)} \]

   if 2.4000000000000002e65 < i

   1. Initial program 21.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 39.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 39.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   5. Simplified 39.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   6. Taylor expanded in x around inf 36.2%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   7. Taylor expanded in i around inf 31.7%

      \[\leadsto j \cdot \color{blue}{\left(i \cdot \left(x \cdot y1\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 36.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]

   9. Simplified 36.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot x\right) \cdot y1\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 30.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -2.3 \cdot 10^{+37}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -6.2 \cdot 10^{-246}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;i \leq 1.7 \cdot 10^{-210}:\\ \;\;\;\;a \cdot \left(z \cdot \left(y1 \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 2.4 \cdot 10^{+65}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 36: 22.0% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -4 \cdot 10^{-55} \lor \neg \left(y3 \leq 1.75 \cdot 10^{+118}\right):\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= y3 -4e-55) (not (<= y3 1.75e+118)))
   (* a (* y1 (* z y3)))
   (* 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 ((y3 <= -4e-55) || !(y3 <= 1.75e+118)) {
		tmp = a * (y1 * (z * y3));
	} 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 ((y3 <= (-4d-55)) .or. (.not. (y3 <= 1.75d+118))) then
        tmp = a * (y1 * (z * y3))
    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 ((y3 <= -4e-55) || !(y3 <= 1.75e+118)) {
		tmp = a * (y1 * (z * y3));
	} 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 (y3 <= -4e-55) or not (y3 <= 1.75e+118):
		tmp = a * (y1 * (z * y3))
	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 ((y3 <= -4e-55) || !(y3 <= 1.75e+118))
		tmp = Float64(a * Float64(y1 * Float64(z * y3)));
	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 ((y3 <= -4e-55) || ~((y3 <= 1.75e+118)))
		tmp = a * (y1 * (z * y3));
	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[y3, -4e-55], N[Not[LessEqual[y3, 1.75e+118]], $MachinePrecision]], N[(a * N[(y1 * N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y3 < -3.99999999999999998e-55 or 1.75000000000000008e118 < y3

   1. Initial program 29.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 40.5%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 34.0%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 34.0%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 34.0%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 34.0%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 33.1%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]

   if -3.99999999999999998e-55 < y3 < 1.75000000000000008e118

   1. Initial program 26.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 37.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 29.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 21.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 26.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -4 \cdot 10^{-55} \lor \neg \left(y3 \leq 1.75 \cdot 10^{+118}\right):\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 37: 22.5% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -7.8 \cdot 10^{+110}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y3 \leq 1.05 \cdot 10^{+118}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -7.8e+110)
   (* c (* y (* y3 y4)))
   (if (<= y3 1.05e+118) (* a (* (* x y) b)) (* a (* y1 (* z y3))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -7.8e+110) {
		tmp = c * (y * (y3 * y4));
	} else if (y3 <= 1.05e+118) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = a * (y1 * (z * y3));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y3 <= (-7.8d+110)) then
        tmp = c * (y * (y3 * y4))
    else if (y3 <= 1.05d+118) then
        tmp = a * ((x * y) * b)
    else
        tmp = a * (y1 * (z * y3))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y3 <= -7.8e+110) {
		tmp = c * (y * (y3 * y4));
	} else if (y3 <= 1.05e+118) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = a * (y1 * (z * y3));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y3 <= -7.8e+110:
		tmp = c * (y * (y3 * y4))
	elif y3 <= 1.05e+118:
		tmp = a * ((x * y) * b)
	else:
		tmp = a * (y1 * (z * y3))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y3 <= -7.8e+110)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	elseif (y3 <= 1.05e+118)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	else
		tmp = Float64(a * Float64(y1 * Float64(z * y3)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y3 <= -7.8e+110)
		tmp = c * (y * (y3 * y4));
	elseif (y3 <= 1.05e+118)
		tmp = a * ((x * y) * b);
	else
		tmp = a * (y1 * (z * y3));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y3, -7.8e+110], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.05e+118], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], N[(a * N[(y1 * N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if y3 < -7.8000000000000007e110

   1. Initial program 20.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 38.1%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 43.8%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.8%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   6. Simplified 43.8%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   7. Taylor expanded in y3 around inf 36.5%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 36.5%

         \[\leadsto c \cdot \left(y \cdot \color{blue}{\left(y4 \cdot y3\right)}\right) \]

   9. Simplified 36.5%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y4 \cdot y3\right)\right)} \]

   if -7.8000000000000007e110 < y3 < 1.05e118

   1. Initial program 29.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 37.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around inf 29.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   5. Taylor expanded in x around inf 21.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if 1.05e118 < y3

   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. Add Preprocessing

   3. Taylor expanded in y1 around inf 48.9%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   4. Taylor expanded in a around inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 39.6%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

      2. neg-mul-1 39.6%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) \]

   6. Simplified 39.6%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   7. Taylor expanded in x around 0 39.6%

      \[\leadsto \color{blue}{a \cdot \left(y1 \cdot \left(y3 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 26.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -7.8 \cdot 10^{+110}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y3 \leq 1.05 \cdot 10^{+118}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y1 \cdot \left(z \cdot y3\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 38: 16.9% 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 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. Add Preprocessing

3. Taylor expanded in b around inf 32.0%

   \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

4. Taylor expanded in a around inf 25.4%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

5. Taylor expanded in x around inf 18.3%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

6. Final simplification 18.3%

   \[\leadsto a \cdot \left(\left(x \cdot y\right) \cdot b\right) \]
7. Add Preprocessing

Developer target: 27.1% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t\_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t\_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t\_9\\ t_11 := t\_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t\_4 \cdot t\_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t\_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t\_3 \cdot t\_1 - t\_14\right)\right) + \left(t\_8 - \left(t\_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t\_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t\_13\right)\right) + \left(t\_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t\_10 - \left(y \cdot x - z \cdot t\right) \cdot t\_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t\_8 - \left(t\_11 - t\_6\right)\right) - \left(\frac{t\_3}{\frac{1}{t\_1}} - t\_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t\_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t\_2 - \left(t\_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t\_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t\_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t\_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t\_5\right) - t\_17 \cdot t\_1\right) + t\_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2024034 
(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)))))