Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.8% → 41.1%

Time: 1.8min

Alternatives: 35

Speedup: 3.5×

• 88.7% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 30.8% 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: 41.1% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := y2 \cdot t_1\\ t_3 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(t_2 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{if}\;k \leq -1.6 \cdot 10^{+152}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;k \leq -1.2 \cdot 10^{-262}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 2.85 \cdot 10^{-68}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 2.45 \cdot 10^{+125}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot t_1 + c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 1.75 \cdot 10^{+210}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(t_2 - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2 (* y2 t_1))
        (t_3
         (*
          k
          (+
           (* z (- (* b y0) (* i y1)))
           (+ t_2 (* y (- (* i y5) (* b y4))))))))
   (if (<= k -1.6e+152)
     t_3
     (if (<= k -1.2e-262)
       (*
        y5
        (+
         (* a (- (* t y2) (* y y3)))
         (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2))))))
       (if (<= k 2.85e-68)
         (*
          j
          (+
           (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
           (* x (- (* i y1) (* b y0)))))
         (if (<= k 2.45e+125)
           (+
            (* (- (* k y2) (* j y3)) t_1)
            (*
             c
             (+
              (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
              (* y4 (- (* y y3) (* t y2))))))
           (if (<= k 1.75e+210) t_3 (* k (- t_2 (* y4 (* 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 = (y1 * y4) - (y0 * y5);
	double t_2 = y2 * t_1;
	double t_3 = k * ((z * ((b * y0) - (i * y1))) + (t_2 + (y * ((i * y5) - (b * y4)))));
	double tmp;
	if (k <= -1.6e+152) {
		tmp = t_3;
	} else if (k <= -1.2e-262) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (k <= 2.85e-68) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 2.45e+125) {
		tmp = (((k * y2) - (j * y3)) * t_1) + (c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2)))));
	} else if (k <= 1.75e+210) {
		tmp = t_3;
	} else {
		tmp = k * (t_2 - (y4 * (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) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = y2 * t_1
    t_3 = k * ((z * ((b * y0) - (i * y1))) + (t_2 + (y * ((i * y5) - (b * y4)))))
    if (k <= (-1.6d+152)) then
        tmp = t_3
    else if (k <= (-1.2d-262)) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
    else if (k <= 2.85d-68) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
    else if (k <= 2.45d+125) then
        tmp = (((k * y2) - (j * y3)) * t_1) + (c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2)))))
    else if (k <= 1.75d+210) then
        tmp = t_3
    else
        tmp = k * (t_2 - (y4 * (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 = (y1 * y4) - (y0 * y5);
	double t_2 = y2 * t_1;
	double t_3 = k * ((z * ((b * y0) - (i * y1))) + (t_2 + (y * ((i * y5) - (b * y4)))));
	double tmp;
	if (k <= -1.6e+152) {
		tmp = t_3;
	} else if (k <= -1.2e-262) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (k <= 2.85e-68) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 2.45e+125) {
		tmp = (((k * y2) - (j * y3)) * t_1) + (c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2)))));
	} else if (k <= 1.75e+210) {
		tmp = t_3;
	} else {
		tmp = k * (t_2 - (y4 * (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 = (y1 * y4) - (y0 * y5)
	t_2 = y2 * t_1
	t_3 = k * ((z * ((b * y0) - (i * y1))) + (t_2 + (y * ((i * y5) - (b * y4)))))
	tmp = 0
	if k <= -1.6e+152:
		tmp = t_3
	elif k <= -1.2e-262:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
	elif k <= 2.85e-68:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
	elif k <= 2.45e+125:
		tmp = (((k * y2) - (j * y3)) * t_1) + (c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2)))))
	elif k <= 1.75e+210:
		tmp = t_3
	else:
		tmp = k * (t_2 - (y4 * (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(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(y2 * t_1)
	t_3 = Float64(k * Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) + Float64(t_2 + Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))))
	tmp = 0.0
	if (k <= -1.6e+152)
		tmp = t_3;
	elseif (k <= -1.2e-262)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (k <= 2.85e-68)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (k <= 2.45e+125)
		tmp = Float64(Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_1) + Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))))));
	elseif (k <= 1.75e+210)
		tmp = t_3;
	else
		tmp = Float64(k * Float64(t_2 - Float64(y4 * 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 = (y1 * y4) - (y0 * y5);
	t_2 = y2 * t_1;
	t_3 = k * ((z * ((b * y0) - (i * y1))) + (t_2 + (y * ((i * y5) - (b * y4)))));
	tmp = 0.0;
	if (k <= -1.6e+152)
		tmp = t_3;
	elseif (k <= -1.2e-262)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	elseif (k <= 2.85e-68)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	elseif (k <= 2.45e+125)
		tmp = (((k * y2) - (j * y3)) * t_1) + (c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2)))));
	elseif (k <= 1.75e+210)
		tmp = t_3;
	else
		tmp = k * (t_2 - (y4 * (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[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y2 * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(k * N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$2 + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -1.6e+152], t$95$3, If[LessEqual[k, -1.2e-262], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.85e-68], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.45e+125], N[(N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] + 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]), $MachinePrecision], If[LessEqual[k, 1.75e+210], t$95$3, N[(k * N[(t$95$2 - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if k < -1.60000000000000003e152 or 2.45000000000000008e125 < k < 1.75e210

   1. Initial program 19.1%

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

   2. Taylor expanded in k around -inf 61.1%

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

      1. mul-1-neg 61.1%

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

      2. *-commutative 61.1%

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

      3. distribute-rgt-neg-in 61.1%

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

      4. +-commutative 61.1%

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

      5. mul-1-neg 61.1%

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

      6. unsub-neg 61.1%

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

      7. *-commutative 61.1%

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

   4. Simplified 61.1%

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

   if -1.60000000000000003e152 < k < -1.2e-262

   1. Initial program 23.9%

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

   2. Taylor expanded in y5 around -inf 51.5%

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

   if -1.2e-262 < k < 2.8500000000000001e-68

   1. Initial program 27.7%

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

   2. Taylor expanded in j around inf 55.8%

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

      1. +-commutative 55.8%

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

      2. mul-1-neg 55.8%

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

      3. unsub-neg 55.8%

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

      4. *-commutative 55.8%

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

   4. Simplified 55.8%

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

   if 2.8500000000000001e-68 < k < 2.45000000000000008e125

   1. Initial program 40.6%

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

   2. Taylor expanded in c around inf 57.5%

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

      1. +-commutative 57.5%

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

      2. mul-1-neg 57.5%

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

      3. unsub-neg 57.5%

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

      4. *-commutative 57.5%

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

      5. *-commutative 57.5%

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

      6. *-commutative 57.5%

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

      7. *-commutative 57.5%

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

   4. Simplified 57.5%

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

   if 1.75e210 < k

   1. Initial program 12.3%

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

   2. Taylor expanded in k around -inf 52.6%

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

      1. mul-1-neg 52.6%

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

      2. *-commutative 52.6%

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

      3. distribute-rgt-neg-in 52.6%

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

      4. +-commutative 52.6%

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

      5. mul-1-neg 52.6%

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

      6. unsub-neg 52.6%

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

      7. *-commutative 52.6%

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

   4. Simplified 52.6%

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

   5. Taylor expanded in z around 0 56.7%

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

   6. Taylor expanded in b around inf 68.7%

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

      1. associate-*r* 68.7%

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

      2. *-commutative 68.7%

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

      3. *-commutative 68.7%

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

   8. Simplified 68.7%

      \[\leadsto \left(\color{blue}{y4 \cdot \left(y \cdot b\right)} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) \cdot \left(-k\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 57.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -1.6 \cdot 10^{+152}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -1.2 \cdot 10^{-262}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 2.85 \cdot 10^{-68}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 2.45 \cdot 10^{+125}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 1.75 \cdot 10^{+210}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \]

Alternative 2: 54.0% accurate, 0.5× speedup

Math

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

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2
         (+
          (+
           (+
            (+
             (+
              (* (- (* a b) (* c i)) (- (* x y) (* z t)))
              (* (- (* x j) (* z k)) (- (* i y1) (* b y0))))
             (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))))
            (* (- (* t j) (* y k)) (- (* b y4) (* i y5))))
           (* (- (* t y2) (* y y3)) (- (* a y5) (* c y4))))
          (* (- (* k y2) (* j y3)) t_1))))
   (if (<= t_2 INFINITY)
     t_2
     (* k (+ (* y2 t_1) (* y (- (* i y5) (* b 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 = (y1 * y4) - (y0 * y5);
	double t_2 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((x * y2) - (z * y3)) * ((c * y0) - (a * y1)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * t_1);
	double tmp;
	if (t_2 <= ((double) INFINITY)) {
		tmp = t_2;
	} else {
		tmp = k * ((y2 * t_1) + (y * ((i * y5) - (b * y4))));
	}
	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 = (y1 * y4) - (y0 * y5);
	double t_2 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((x * y2) - (z * y3)) * ((c * y0) - (a * y1)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * t_1);
	double tmp;
	if (t_2 <= Double.POSITIVE_INFINITY) {
		tmp = t_2;
	} else {
		tmp = k * ((y2 * t_1) + (y * ((i * y5) - (b * y4))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((x * y2) - (z * y3)) * ((c * y0) - (a * y1)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * t_1)
	tmp = 0
	if t_2 <= math.inf:
		tmp = t_2
	else:
		tmp = k * ((y2 * t_1) + (y * ((i * y5) - (b * y4))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t))) + Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(i * y1) - Float64(b * y0)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(a * y5) - Float64(c * y4)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_1))
	tmp = 0.0
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = Float64(k * Float64(Float64(y2 * t_1) + Float64(y * Float64(Float64(i * y5) - Float64(b * 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 = (y1 * y4) - (y0 * y5);
	t_2 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (((x * y2) - (z * y3)) * ((c * y0) - (a * y1)))) + (((t * j) - (y * k)) * ((b * y4) - (i * y5)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * t_1);
	tmp = 0.0;
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = k * ((y2 * t_1) + (y * ((i * y5) - (b * y4))));
	end
	tmp_2 = tmp;
end

Wolfram

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

Derivation

1. Split input into 2 regimes

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

   1. Initial program 91.9%

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

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

   1. Initial program 0.0%

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

   2. Taylor expanded in k around -inf 40.7%

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

      1. mul-1-neg 40.7%

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

      2. *-commutative 40.7%

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

      3. distribute-rgt-neg-in 40.7%

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

      4. +-commutative 40.7%

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

      5. mul-1-neg 40.7%

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

      6. unsub-neg 40.7%

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

      7. *-commutative 40.7%

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

   4. Simplified 40.7%

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

   5. Taylor expanded in z around 0 41.9%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]
3. Recombined 2 regimes into one program.

4. Final simplification 55.6%

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

Alternative 3: 37.9% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{if}\;k \leq -6.4 \cdot 10^{+197}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq -5.8 \cdot 10^{+40}:\\ \;\;\;\;k \cdot \left(t_1 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;k \leq -2 \cdot 10^{-51}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq -2.4 \cdot 10^{-233}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 1.1 \cdot 10^{-41}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 8.8 \cdot 10^{+144}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(t_1 - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y2 (- (* y1 y4) (* y0 y5)))))
   (if (<= k -6.4e+197)
     (* i (* k (- (* y y5) (* z y1))))
     (if (<= k -5.8e+40)
       (* k (+ t_1 (* y (- (* i y5) (* b y4)))))
       (if (<= k -2e-51)
         (* y0 (+ (* x (- (* c y2) (* b j))) (* y5 (- (* j y3) (* k y2)))))
         (if (<= k -2.4e-233)
           (* y1 (* x (- (* i j) (* a y2))))
           (if (<= k 1.1e-41)
             (*
              j
              (+
               (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
               (* x (- (* i y1) (* b y0)))))
             (if (<= k 8.8e+144)
               (*
                y1
                (+
                 (* i (- (* x j) (* z k)))
                 (- (* y4 (- (* k y2) (* j y3))) (* a (- (* x y2) (* z y3))))))
               (* k (- t_1 (* y4 (* 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 = y2 * ((y1 * y4) - (y0 * y5));
	double tmp;
	if (k <= -6.4e+197) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= -5.8e+40) {
		tmp = k * (t_1 + (y * ((i * y5) - (b * y4))));
	} else if (k <= -2e-51) {
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	} else if (k <= -2.4e-233) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (k <= 1.1e-41) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 8.8e+144) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	} else {
		tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5))
    if (k <= (-6.4d+197)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= (-5.8d+40)) then
        tmp = k * (t_1 + (y * ((i * y5) - (b * y4))))
    else if (k <= (-2d-51)) then
        tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
    else if (k <= (-2.4d-233)) then
        tmp = y1 * (x * ((i * j) - (a * y2)))
    else if (k <= 1.1d-41) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
    else if (k <= 8.8d+144) then
        tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))))
    else
        tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5));
	double tmp;
	if (k <= -6.4e+197) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= -5.8e+40) {
		tmp = k * (t_1 + (y * ((i * y5) - (b * y4))));
	} else if (k <= -2e-51) {
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	} else if (k <= -2.4e-233) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (k <= 1.1e-41) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 8.8e+144) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	} else {
		tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5))
	tmp = 0
	if k <= -6.4e+197:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= -5.8e+40:
		tmp = k * (t_1 + (y * ((i * y5) - (b * y4))))
	elif k <= -2e-51:
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
	elif k <= -2.4e-233:
		tmp = y1 * (x * ((i * j) - (a * y2)))
	elif k <= 1.1e-41:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
	elif k <= 8.8e+144:
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))))
	else:
		tmp = k * (t_1 - (y4 * (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(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))
	tmp = 0.0
	if (k <= -6.4e+197)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= -5.8e+40)
		tmp = Float64(k * Float64(t_1 + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))));
	elseif (k <= -2e-51)
		tmp = Float64(y0 * Float64(Float64(x * Float64(Float64(c * y2) - Float64(b * j))) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (k <= -2.4e-233)
		tmp = Float64(y1 * Float64(x * Float64(Float64(i * j) - Float64(a * y2))));
	elseif (k <= 1.1e-41)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (k <= 8.8e+144)
		tmp = Float64(y1 * Float64(Float64(i * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(a * Float64(Float64(x * y2) - Float64(z * y3))))));
	else
		tmp = Float64(k * Float64(t_1 - Float64(y4 * 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 = y2 * ((y1 * y4) - (y0 * y5));
	tmp = 0.0;
	if (k <= -6.4e+197)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= -5.8e+40)
		tmp = k * (t_1 + (y * ((i * y5) - (b * y4))));
	elseif (k <= -2e-51)
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	elseif (k <= -2.4e-233)
		tmp = y1 * (x * ((i * j) - (a * y2)));
	elseif (k <= 1.1e-41)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	elseif (k <= 8.8e+144)
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	else
		tmp = k * (t_1 - (y4 * (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[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -6.4e+197], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -5.8e+40], N[(k * N[(t$95$1 + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -2e-51], N[(y0 * N[(N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -2.4e-233], N[(y1 * N[(x * N[(N[(i * j), $MachinePrecision] - N[(a * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.1e-41], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 8.8e+144], N[(y1 * N[(N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(t$95$1 - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if k < -6.3999999999999997e197

   1. Initial program 20.0%

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

   2. Taylor expanded in k around -inf 55.0%

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

      1. mul-1-neg 55.0%

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

      2. *-commutative 55.0%

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

      3. distribute-rgt-neg-in 55.0%

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

      4. +-commutative 55.0%

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

      5. mul-1-neg 55.0%

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

      6. unsub-neg 55.0%

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

      7. *-commutative 55.0%

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

   4. Simplified 55.0%

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

   5. Taylor expanded in i around -inf 60.5%

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

   if -6.3999999999999997e197 < k < -5.80000000000000035e40

   1. Initial program 13.1%

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

   2. Taylor expanded in k around -inf 45.2%

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

      1. mul-1-neg 45.2%

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

      2. *-commutative 45.2%

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

      3. distribute-rgt-neg-in 45.2%

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

      4. +-commutative 45.2%

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

      5. mul-1-neg 45.2%

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

      6. unsub-neg 45.2%

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

      7. *-commutative 45.2%

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

   4. Simplified 45.2%

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

   5. Taylor expanded in z around 0 51.9%

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

   if -5.80000000000000035e40 < k < -2e-51

   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. Taylor expanded in x around inf 48.6%

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

   3. Taylor expanded in y0 around inf 58.5%

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

      1. +-commutative 58.5%

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

      2. mul-1-neg 58.5%

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

      3. unsub-neg 58.5%

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

      4. *-commutative 58.5%

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

   5. Simplified 58.5%

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

   if -2e-51 < k < -2.3999999999999999e-233

   1. Initial program 26.6%

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

   2. Taylor expanded in y1 around -inf 33.5%

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

      1. mul-1-neg 33.5%

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

      2. *-commutative 33.5%

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

      3. distribute-rgt-neg-in 33.5%

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

   4. Simplified 33.5%

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

   5. Taylor expanded in x around inf 45.0%

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

      1. *-commutative 45.0%

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

   7. Simplified 45.0%

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

   if -2.3999999999999999e-233 < k < 1.1e-41

   1. Initial program 28.8%

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

   2. Taylor expanded in j around inf 53.0%

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

      1. +-commutative 53.0%

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

      2. mul-1-neg 53.0%

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

      3. unsub-neg 53.0%

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

      4. *-commutative 53.0%

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

   4. Simplified 53.0%

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

   if 1.1e-41 < k < 8.79999999999999952e144

   1. Initial program 32.7%

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

   2. Taylor expanded in y1 around -inf 54.8%

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

      1. mul-1-neg 54.8%

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

      2. *-commutative 54.8%

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

      3. distribute-rgt-neg-in 54.8%

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

   4. Simplified 54.8%

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

   if 8.79999999999999952e144 < k

   1. Initial program 17.3%

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

   2. Taylor expanded in k around -inf 60.5%

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

      1. mul-1-neg 60.5%

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

      2. *-commutative 60.5%

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

      3. distribute-rgt-neg-in 60.5%

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

      4. +-commutative 60.5%

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

      5. mul-1-neg 60.5%

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

      6. unsub-neg 60.5%

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

      7. *-commutative 60.5%

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

   4. Simplified 60.5%

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

   5. Taylor expanded in z around 0 60.5%

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

   6. Taylor expanded in b around inf 60.6%

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

      1. associate-*r* 60.6%

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

      2. *-commutative 60.6%

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

      3. *-commutative 60.6%

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

   8. Simplified 60.6%

      \[\leadsto \left(\color{blue}{y4 \cdot \left(y \cdot b\right)} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) \cdot \left(-k\right) \]
3. Recombined 7 regimes into one program.

4. Final simplification 54.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -6.4 \cdot 10^{+197}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq -5.8 \cdot 10^{+40}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;k \leq -2 \cdot 10^{-51}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq -2.4 \cdot 10^{-233}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 1.1 \cdot 10^{-41}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 8.8 \cdot 10^{+144}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \]

Alternative 4: 36.6% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ t_2 := y1 \cdot y4 - y0 \cdot y5\\ t_3 := y2 \cdot t_2\\ \mathbf{if}\;k \leq -2.5 \cdot 10^{+189}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq -2.6 \cdot 10^{+42}:\\ \;\;\;\;k \cdot \left(t_3 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;k \leq -4.8 \cdot 10^{-47}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;k \leq -1.15 \cdot 10^{-232}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 9.5 \cdot 10^{-41}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 1.95 \cdot 10^{+18}:\\ \;\;\;\;y1 \cdot \left(a \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 9 \cdot 10^{+62}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;k \leq 3.2 \cdot 10^{+130}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot t_2 - a \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 2.15 \cdot 10^{+163}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(t_3 - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (* y0 (+ (* x (- (* c y2) (* b j))) (* y5 (- (* j y3) (* k y2))))))
        (t_2 (- (* y1 y4) (* y0 y5)))
        (t_3 (* y2 t_2)))
   (if (<= k -2.5e+189)
     (* i (* k (- (* y y5) (* z y1))))
     (if (<= k -2.6e+42)
       (* k (+ t_3 (* y (- (* i y5) (* b y4)))))
       (if (<= k -4.8e-47)
         t_1
         (if (<= k -1.15e-232)
           (* y1 (* x (- (* i j) (* a y2))))
           (if (<= k 9.5e-41)
             (*
              j
              (+
               (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
               (* x (- (* i y1) (* b y0)))))
             (if (<= k 1.95e+18)
               (* y1 (* a (- (* z y3) (* x y2))))
               (if (<= k 9e+62)
                 (* (* b j) (- (* t y4) (* x y0)))
                 (if (<= k 3.2e+130)
                   (- (* (- (* k y2) (* j y3)) t_2) (* a (* x (* y1 y2))))
                   (if (<= k 2.15e+163)
                     t_1
                     (* k (- t_3 (* y4 (* 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 = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = y2 * t_2;
	double tmp;
	if (k <= -2.5e+189) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= -2.6e+42) {
		tmp = k * (t_3 + (y * ((i * y5) - (b * y4))));
	} else if (k <= -4.8e-47) {
		tmp = t_1;
	} else if (k <= -1.15e-232) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (k <= 9.5e-41) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 1.95e+18) {
		tmp = y1 * (a * ((z * y3) - (x * y2)));
	} else if (k <= 9e+62) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (k <= 3.2e+130) {
		tmp = (((k * y2) - (j * y3)) * t_2) - (a * (x * (y1 * y2)));
	} else if (k <= 2.15e+163) {
		tmp = t_1;
	} else {
		tmp = k * (t_3 - (y4 * (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) :: tmp
    t_1 = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
    t_2 = (y1 * y4) - (y0 * y5)
    t_3 = y2 * t_2
    if (k <= (-2.5d+189)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= (-2.6d+42)) then
        tmp = k * (t_3 + (y * ((i * y5) - (b * y4))))
    else if (k <= (-4.8d-47)) then
        tmp = t_1
    else if (k <= (-1.15d-232)) then
        tmp = y1 * (x * ((i * j) - (a * y2)))
    else if (k <= 9.5d-41) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
    else if (k <= 1.95d+18) then
        tmp = y1 * (a * ((z * y3) - (x * y2)))
    else if (k <= 9d+62) then
        tmp = (b * j) * ((t * y4) - (x * y0))
    else if (k <= 3.2d+130) then
        tmp = (((k * y2) - (j * y3)) * t_2) - (a * (x * (y1 * y2)))
    else if (k <= 2.15d+163) then
        tmp = t_1
    else
        tmp = k * (t_3 - (y4 * (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 = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = y2 * t_2;
	double tmp;
	if (k <= -2.5e+189) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= -2.6e+42) {
		tmp = k * (t_3 + (y * ((i * y5) - (b * y4))));
	} else if (k <= -4.8e-47) {
		tmp = t_1;
	} else if (k <= -1.15e-232) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (k <= 9.5e-41) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 1.95e+18) {
		tmp = y1 * (a * ((z * y3) - (x * y2)));
	} else if (k <= 9e+62) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (k <= 3.2e+130) {
		tmp = (((k * y2) - (j * y3)) * t_2) - (a * (x * (y1 * y2)));
	} else if (k <= 2.15e+163) {
		tmp = t_1;
	} else {
		tmp = k * (t_3 - (y4 * (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 = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
	t_2 = (y1 * y4) - (y0 * y5)
	t_3 = y2 * t_2
	tmp = 0
	if k <= -2.5e+189:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= -2.6e+42:
		tmp = k * (t_3 + (y * ((i * y5) - (b * y4))))
	elif k <= -4.8e-47:
		tmp = t_1
	elif k <= -1.15e-232:
		tmp = y1 * (x * ((i * j) - (a * y2)))
	elif k <= 9.5e-41:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
	elif k <= 1.95e+18:
		tmp = y1 * (a * ((z * y3) - (x * y2)))
	elif k <= 9e+62:
		tmp = (b * j) * ((t * y4) - (x * y0))
	elif k <= 3.2e+130:
		tmp = (((k * y2) - (j * y3)) * t_2) - (a * (x * (y1 * y2)))
	elif k <= 2.15e+163:
		tmp = t_1
	else:
		tmp = k * (t_3 - (y4 * (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(y0 * Float64(Float64(x * Float64(Float64(c * y2) - Float64(b * j))) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))))
	t_2 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_3 = Float64(y2 * t_2)
	tmp = 0.0
	if (k <= -2.5e+189)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= -2.6e+42)
		tmp = Float64(k * Float64(t_3 + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))));
	elseif (k <= -4.8e-47)
		tmp = t_1;
	elseif (k <= -1.15e-232)
		tmp = Float64(y1 * Float64(x * Float64(Float64(i * j) - Float64(a * y2))));
	elseif (k <= 9.5e-41)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (k <= 1.95e+18)
		tmp = Float64(y1 * Float64(a * Float64(Float64(z * y3) - Float64(x * y2))));
	elseif (k <= 9e+62)
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	elseif (k <= 3.2e+130)
		tmp = Float64(Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_2) - Float64(a * Float64(x * Float64(y1 * y2))));
	elseif (k <= 2.15e+163)
		tmp = t_1;
	else
		tmp = Float64(k * Float64(t_3 - Float64(y4 * 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 = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	t_2 = (y1 * y4) - (y0 * y5);
	t_3 = y2 * t_2;
	tmp = 0.0;
	if (k <= -2.5e+189)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= -2.6e+42)
		tmp = k * (t_3 + (y * ((i * y5) - (b * y4))));
	elseif (k <= -4.8e-47)
		tmp = t_1;
	elseif (k <= -1.15e-232)
		tmp = y1 * (x * ((i * j) - (a * y2)));
	elseif (k <= 9.5e-41)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	elseif (k <= 1.95e+18)
		tmp = y1 * (a * ((z * y3) - (x * y2)));
	elseif (k <= 9e+62)
		tmp = (b * j) * ((t * y4) - (x * y0));
	elseif (k <= 3.2e+130)
		tmp = (((k * y2) - (j * y3)) * t_2) - (a * (x * (y1 * y2)));
	elseif (k <= 2.15e+163)
		tmp = t_1;
	else
		tmp = k * (t_3 - (y4 * (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[(y0 * N[(N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y2 * t$95$2), $MachinePrecision]}, If[LessEqual[k, -2.5e+189], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -2.6e+42], N[(k * N[(t$95$3 + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -4.8e-47], t$95$1, If[LessEqual[k, -1.15e-232], N[(y1 * N[(x * N[(N[(i * j), $MachinePrecision] - N[(a * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 9.5e-41], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.95e+18], N[(y1 * N[(a * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 9e+62], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 3.2e+130], N[(N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(a * N[(x * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.15e+163], t$95$1, N[(k * N[(t$95$3 - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if k < -2.5000000000000002e189

   1. Initial program 20.0%

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

   2. Taylor expanded in k around -inf 55.0%

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

      1. mul-1-neg 55.0%

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

      2. *-commutative 55.0%

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

      3. distribute-rgt-neg-in 55.0%

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

      4. +-commutative 55.0%

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

      5. mul-1-neg 55.0%

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

      6. unsub-neg 55.0%

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

      7. *-commutative 55.0%

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

   4. Simplified 55.0%

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

   5. Taylor expanded in i around -inf 60.5%

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

   if -2.5000000000000002e189 < k < -2.5999999999999999e42

   1. Initial program 13.1%

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

   2. Taylor expanded in k around -inf 45.2%

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

      1. mul-1-neg 45.2%

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

      2. *-commutative 45.2%

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

      3. distribute-rgt-neg-in 45.2%

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

      4. +-commutative 45.2%

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

      5. mul-1-neg 45.2%

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

      6. unsub-neg 45.2%

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

      7. *-commutative 45.2%

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

   4. Simplified 45.2%

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

   5. Taylor expanded in z around 0 51.9%

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

   if -2.5999999999999999e42 < k < -4.7999999999999999e-47 or 3.2e130 < k < 2.1500000000000001e163

   1. Initial program 29.0%

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

   2. Taylor expanded in x around inf 49.1%

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

   3. Taylor expanded in y0 around inf 64.9%

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

      1. +-commutative 64.9%

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

      2. mul-1-neg 64.9%

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

      3. unsub-neg 64.9%

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

      4. *-commutative 64.9%

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

   5. Simplified 64.9%

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

   if -4.7999999999999999e-47 < k < -1.15e-232

   1. Initial program 26.6%

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

   2. Taylor expanded in y1 around -inf 33.5%

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

      1. mul-1-neg 33.5%

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

      2. *-commutative 33.5%

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

      3. distribute-rgt-neg-in 33.5%

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

   4. Simplified 33.5%

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

   5. Taylor expanded in x around inf 45.0%

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

      1. *-commutative 45.0%

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

   7. Simplified 45.0%

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

   if -1.15e-232 < k < 9.4999999999999997e-41

   1. Initial program 28.8%

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

   2. Taylor expanded in j around inf 53.0%

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

      1. +-commutative 53.0%

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

      2. mul-1-neg 53.0%

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

      3. unsub-neg 53.0%

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

      4. *-commutative 53.0%

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

   4. Simplified 53.0%

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

   if 9.4999999999999997e-41 < k < 1.95e18

   1. Initial program 43.8%

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

   2. Taylor expanded in y1 around -inf 51.2%

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

      1. mul-1-neg 51.2%

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

      2. *-commutative 51.2%

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

      3. distribute-rgt-neg-in 51.2%

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

   4. Simplified 51.2%

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

   5. Taylor expanded in a around inf 57.1%

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

      1. *-commutative 57.1%

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

      2. *-commutative 57.1%

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

   7. Simplified 57.1%

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

   if 1.95e18 < k < 8.99999999999999997e62

   1. Initial program 10.0%

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

   2. Taylor expanded in j around inf 30.7%

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

      1. +-commutative 30.7%

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

      2. mul-1-neg 30.7%

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

      3. unsub-neg 30.7%

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

      4. *-commutative 30.7%

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

   4. Simplified 30.7%

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

   5. Taylor expanded in b around inf 42.7%

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

      1. associate-*r* 51.5%

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

      2. *-commutative 51.5%

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

      3. *-commutative 51.5%

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

   7. Simplified 51.5%

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

   if 8.99999999999999997e62 < k < 3.2e130

   1. Initial program 43.2%

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

   2. Taylor expanded in y2 around inf 42.9%

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

      1. *-commutative 42.9%

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

   4. Simplified 42.9%

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

   5. Taylor expanded in y1 around inf 71.5%

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

      1. associate-*r* 71.5%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. neg-mul-1 71.5%

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

      3. *-commutative 71.5%

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

   7. Simplified 71.5%

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

   if 2.1500000000000001e163 < k

   1. Initial program 17.4%

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

   2. Taylor expanded in k around -inf 57.1%

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

      1. mul-1-neg 57.1%

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

      2. *-commutative 57.1%

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

      3. distribute-rgt-neg-in 57.1%

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

      4. +-commutative 57.1%

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

      5. mul-1-neg 57.1%

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

      6. unsub-neg 57.1%

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

      7. *-commutative 57.1%

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

   4. Simplified 57.1%

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

   5. Taylor expanded in z around 0 59.6%

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

   6. Taylor expanded in b around inf 64.5%

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

      1. associate-*r* 64.5%

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

      2. *-commutative 64.5%

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

      3. *-commutative 64.5%

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

   8. Simplified 64.5%

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

4. Final simplification 56.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -2.5 \cdot 10^{+189}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq -2.6 \cdot 10^{+42}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;k \leq -4.8 \cdot 10^{-47}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq -1.15 \cdot 10^{-232}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 9.5 \cdot 10^{-41}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 1.95 \cdot 10^{+18}:\\ \;\;\;\;y1 \cdot \left(a \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 9 \cdot 10^{+62}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;k \leq 3.2 \cdot 10^{+130}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - a \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 2.15 \cdot 10^{+163}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \]

Alternative 5: 39.5% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ t_2 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(t_1 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{if}\;k \leq -7.5 \cdot 10^{+76}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;k \leq -1.26 \cdot 10^{-232}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 7.5 \cdot 10^{-42}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 2.55 \cdot 10^{+128}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 4 \cdot 10^{+210}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(t_1 - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y2 (- (* y1 y4) (* y0 y5))))
        (t_2
         (*
          k
          (+
           (* z (- (* b y0) (* i y1)))
           (+ t_1 (* y (- (* i y5) (* b y4))))))))
   (if (<= k -7.5e+76)
     t_2
     (if (<= k -1.26e-232)
       (* y1 (* x (- (* i j) (* a y2))))
       (if (<= k 7.5e-42)
         (*
          j
          (+
           (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
           (* x (- (* i y1) (* b y0)))))
         (if (<= k 2.55e+128)
           (*
            y1
            (+
             (* i (- (* x j) (* z k)))
             (- (* y4 (- (* k y2) (* j y3))) (* a (- (* x y2) (* z y3))))))
           (if (<= k 4e+210) t_2 (* k (- t_1 (* y4 (* 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 = y2 * ((y1 * y4) - (y0 * y5));
	double t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))));
	double tmp;
	if (k <= -7.5e+76) {
		tmp = t_2;
	} else if (k <= -1.26e-232) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (k <= 7.5e-42) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 2.55e+128) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	} else if (k <= 4e+210) {
		tmp = t_2;
	} else {
		tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5))
    t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))))
    if (k <= (-7.5d+76)) then
        tmp = t_2
    else if (k <= (-1.26d-232)) then
        tmp = y1 * (x * ((i * j) - (a * y2)))
    else if (k <= 7.5d-42) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
    else if (k <= 2.55d+128) then
        tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))))
    else if (k <= 4d+210) then
        tmp = t_2
    else
        tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5));
	double t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))));
	double tmp;
	if (k <= -7.5e+76) {
		tmp = t_2;
	} else if (k <= -1.26e-232) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (k <= 7.5e-42) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 2.55e+128) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	} else if (k <= 4e+210) {
		tmp = t_2;
	} else {
		tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5))
	t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))))
	tmp = 0
	if k <= -7.5e+76:
		tmp = t_2
	elif k <= -1.26e-232:
		tmp = y1 * (x * ((i * j) - (a * y2)))
	elif k <= 7.5e-42:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
	elif k <= 2.55e+128:
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))))
	elif k <= 4e+210:
		tmp = t_2
	else:
		tmp = k * (t_1 - (y4 * (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(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))
	t_2 = Float64(k * Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) + Float64(t_1 + Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))))
	tmp = 0.0
	if (k <= -7.5e+76)
		tmp = t_2;
	elseif (k <= -1.26e-232)
		tmp = Float64(y1 * Float64(x * Float64(Float64(i * j) - Float64(a * y2))));
	elseif (k <= 7.5e-42)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (k <= 2.55e+128)
		tmp = Float64(y1 * Float64(Float64(i * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(a * Float64(Float64(x * y2) - Float64(z * y3))))));
	elseif (k <= 4e+210)
		tmp = t_2;
	else
		tmp = Float64(k * Float64(t_1 - Float64(y4 * 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 = y2 * ((y1 * y4) - (y0 * y5));
	t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))));
	tmp = 0.0;
	if (k <= -7.5e+76)
		tmp = t_2;
	elseif (k <= -1.26e-232)
		tmp = y1 * (x * ((i * j) - (a * y2)));
	elseif (k <= 7.5e-42)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	elseif (k <= 2.55e+128)
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	elseif (k <= 4e+210)
		tmp = t_2;
	else
		tmp = k * (t_1 - (y4 * (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[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -7.5e+76], t$95$2, If[LessEqual[k, -1.26e-232], N[(y1 * N[(x * N[(N[(i * j), $MachinePrecision] - N[(a * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 7.5e-42], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.55e+128], N[(y1 * N[(N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4e+210], t$95$2, N[(k * N[(t$95$1 - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if k < -7.4999999999999995e76 or 2.5499999999999999e128 < k < 3.99999999999999971e210

   1. Initial program 17.2%

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

   2. Taylor expanded in k around -inf 60.7%

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

      1. mul-1-neg 60.7%

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

      2. *-commutative 60.7%

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

      3. distribute-rgt-neg-in 60.7%

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

      4. +-commutative 60.7%

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

      5. mul-1-neg 60.7%

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

      6. unsub-neg 60.7%

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

      7. *-commutative 60.7%

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

   4. Simplified 60.7%

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

   if -7.4999999999999995e76 < k < -1.25999999999999991e-232

   1. Initial program 29.2%

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

   2. Taylor expanded in y1 around -inf 33.3%

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

      1. mul-1-neg 33.3%

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

      2. *-commutative 33.3%

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

      3. distribute-rgt-neg-in 33.3%

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

   4. Simplified 33.3%

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

   5. Taylor expanded in x around inf 46.2%

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

      1. *-commutative 46.2%

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

   7. Simplified 46.2%

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

   if -1.25999999999999991e-232 < k < 7.49999999999999972e-42

   1. Initial program 28.8%

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

   2. Taylor expanded in j around inf 53.0%

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

      1. +-commutative 53.0%

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

      2. mul-1-neg 53.0%

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

      3. unsub-neg 53.0%

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

      4. *-commutative 53.0%

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

   4. Simplified 53.0%

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

   if 7.49999999999999972e-42 < k < 2.5499999999999999e128

   1. Initial program 35.1%

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

   2. Taylor expanded in y1 around -inf 53.0%

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

      1. mul-1-neg 53.0%

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

      2. *-commutative 53.0%

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

      3. distribute-rgt-neg-in 53.0%

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

   4. Simplified 53.0%

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

   if 3.99999999999999971e210 < k

   1. Initial program 12.3%

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

   2. Taylor expanded in k around -inf 52.6%

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

      1. mul-1-neg 52.6%

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

      2. *-commutative 52.6%

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

      3. distribute-rgt-neg-in 52.6%

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

      4. +-commutative 52.6%

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

      5. mul-1-neg 52.6%

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

      6. unsub-neg 52.6%

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

      7. *-commutative 52.6%

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

   4. Simplified 52.6%

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

   5. Taylor expanded in z around 0 56.7%

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

   6. Taylor expanded in b around inf 68.7%

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

      1. associate-*r* 68.7%

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

      2. *-commutative 68.7%

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

      3. *-commutative 68.7%

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

   8. Simplified 68.7%

      \[\leadsto \left(\color{blue}{y4 \cdot \left(y \cdot b\right)} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) \cdot \left(-k\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 55.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -7.5 \cdot 10^{+76}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -1.26 \cdot 10^{-232}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 7.5 \cdot 10^{-42}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 2.55 \cdot 10^{+128}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 4 \cdot 10^{+210}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \]

Alternative 6: 40.8% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ t_2 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(t_1 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{if}\;k \leq -5.2 \cdot 10^{+154}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;k \leq -2.2 \cdot 10^{-261}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 6.8 \cdot 10^{-41}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 1.48 \cdot 10^{+128}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 1.6 \cdot 10^{+210}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(t_1 - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y2 (- (* y1 y4) (* y0 y5))))
        (t_2
         (*
          k
          (+
           (* z (- (* b y0) (* i y1)))
           (+ t_1 (* y (- (* i y5) (* b y4))))))))
   (if (<= k -5.2e+154)
     t_2
     (if (<= k -2.2e-261)
       (*
        y5
        (+
         (* a (- (* t y2) (* y y3)))
         (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2))))))
       (if (<= k 6.8e-41)
         (*
          j
          (+
           (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
           (* x (- (* i y1) (* b y0)))))
         (if (<= k 1.48e+128)
           (*
            y1
            (+
             (* i (- (* x j) (* z k)))
             (- (* y4 (- (* k y2) (* j y3))) (* a (- (* x y2) (* z y3))))))
           (if (<= k 1.6e+210) t_2 (* k (- t_1 (* y4 (* 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 = y2 * ((y1 * y4) - (y0 * y5));
	double t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))));
	double tmp;
	if (k <= -5.2e+154) {
		tmp = t_2;
	} else if (k <= -2.2e-261) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (k <= 6.8e-41) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 1.48e+128) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	} else if (k <= 1.6e+210) {
		tmp = t_2;
	} else {
		tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5))
    t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))))
    if (k <= (-5.2d+154)) then
        tmp = t_2
    else if (k <= (-2.2d-261)) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
    else if (k <= 6.8d-41) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
    else if (k <= 1.48d+128) then
        tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))))
    else if (k <= 1.6d+210) then
        tmp = t_2
    else
        tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5));
	double t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))));
	double tmp;
	if (k <= -5.2e+154) {
		tmp = t_2;
	} else if (k <= -2.2e-261) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (k <= 6.8e-41) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	} else if (k <= 1.48e+128) {
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	} else if (k <= 1.6e+210) {
		tmp = t_2;
	} else {
		tmp = k * (t_1 - (y4 * (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 = y2 * ((y1 * y4) - (y0 * y5))
	t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))))
	tmp = 0
	if k <= -5.2e+154:
		tmp = t_2
	elif k <= -2.2e-261:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
	elif k <= 6.8e-41:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))))
	elif k <= 1.48e+128:
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))))
	elif k <= 1.6e+210:
		tmp = t_2
	else:
		tmp = k * (t_1 - (y4 * (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(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))
	t_2 = Float64(k * Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) + Float64(t_1 + Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))))
	tmp = 0.0
	if (k <= -5.2e+154)
		tmp = t_2;
	elseif (k <= -2.2e-261)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (k <= 6.8e-41)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (k <= 1.48e+128)
		tmp = Float64(y1 * Float64(Float64(i * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))) - Float64(a * Float64(Float64(x * y2) - Float64(z * y3))))));
	elseif (k <= 1.6e+210)
		tmp = t_2;
	else
		tmp = Float64(k * Float64(t_1 - Float64(y4 * 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 = y2 * ((y1 * y4) - (y0 * y5));
	t_2 = k * ((z * ((b * y0) - (i * y1))) + (t_1 + (y * ((i * y5) - (b * y4)))));
	tmp = 0.0;
	if (k <= -5.2e+154)
		tmp = t_2;
	elseif (k <= -2.2e-261)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	elseif (k <= 6.8e-41)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) + (x * ((i * y1) - (b * y0))));
	elseif (k <= 1.48e+128)
		tmp = y1 * ((i * ((x * j) - (z * k))) + ((y4 * ((k * y2) - (j * y3))) - (a * ((x * y2) - (z * y3)))));
	elseif (k <= 1.6e+210)
		tmp = t_2;
	else
		tmp = k * (t_1 - (y4 * (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[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -5.2e+154], t$95$2, If[LessEqual[k, -2.2e-261], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 6.8e-41], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.48e+128], N[(y1 * N[(N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.6e+210], t$95$2, N[(k * N[(t$95$1 - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if k < -5.19999999999999978e154 or 1.47999999999999992e128 < k < 1.6000000000000001e210

   1. Initial program 19.8%

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

   2. Taylor expanded in k around -inf 63.3%

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

      1. mul-1-neg 63.3%

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

      2. *-commutative 63.3%

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

      3. distribute-rgt-neg-in 63.3%

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

      4. +-commutative 63.3%

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

      5. mul-1-neg 63.3%

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

      6. unsub-neg 63.3%

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

      7. *-commutative 63.3%

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

   4. Simplified 63.3%

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

   if -5.19999999999999978e154 < k < -2.2000000000000002e-261

   1. Initial program 23.9%

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

   2. Taylor expanded in y5 around -inf 51.5%

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

   if -2.2000000000000002e-261 < k < 6.7999999999999997e-41

   1. Initial program 31.4%

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

   2. Taylor expanded in j around inf 53.5%

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

      1. +-commutative 53.5%

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

      2. mul-1-neg 53.5%

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

      3. unsub-neg 53.5%

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

      4. *-commutative 53.5%

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

   4. Simplified 53.5%

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

   if 6.7999999999999997e-41 < k < 1.47999999999999992e128

   1. Initial program 35.1%

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

   2. Taylor expanded in y1 around -inf 53.0%

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

      1. mul-1-neg 53.0%

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

      2. *-commutative 53.0%

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

      3. distribute-rgt-neg-in 53.0%

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

   4. Simplified 53.0%

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

   if 1.6000000000000001e210 < k

   1. Initial program 12.3%

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

   2. Taylor expanded in k around -inf 52.6%

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

      1. mul-1-neg 52.6%

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

      2. *-commutative 52.6%

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

      3. distribute-rgt-neg-in 52.6%

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

      4. +-commutative 52.6%

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

      5. mul-1-neg 52.6%

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

      6. unsub-neg 52.6%

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

      7. *-commutative 52.6%

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

   4. Simplified 52.6%

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

   5. Taylor expanded in z around 0 56.7%

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

   6. Taylor expanded in b around inf 68.7%

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

      1. associate-*r* 68.7%

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

      2. *-commutative 68.7%

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

      3. *-commutative 68.7%

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

   8. Simplified 68.7%

      \[\leadsto \left(\color{blue}{y4 \cdot \left(y \cdot b\right)} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) \cdot \left(-k\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 56.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -5.2 \cdot 10^{+154}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -2.2 \cdot 10^{-261}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 6.8 \cdot 10^{-41}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 1.48 \cdot 10^{+128}:\\ \;\;\;\;y1 \cdot \left(i \cdot \left(x \cdot j - z \cdot k\right) + \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right) - a \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 1.6 \cdot 10^{+210}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \end{array} \]

Alternative 7: 35.3% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{if}\;x \leq -1.12 \cdot 10^{+170}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -4.5 \cdot 10^{-11}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -1.1 \cdot 10^{-201}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -7 \cdot 10^{-293}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq 1.35 \cdot 10^{-266}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq 1.75 \cdot 10^{+26}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq 3.6 \cdot 10^{+95}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq 3.6 \cdot 10^{+135}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (* k (+ (* y2 (- (* y1 y4) (* y0 y5))) (* y (- (* i y5) (* b y4)))))))
   (if (<= x -1.12e+170)
     (* a (* x (- (* y b) (* y1 y2))))
     (if (<= x -4.5e-11)
       t_1
       (if (<= x -1.1e-201)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= x -7e-293)
           t_1
           (if (<= x 1.35e-266)
             (* t (* y2 (- (* a y5) (* c y4))))
             (if (<= x 1.75e+26)
               t_1
               (if (<= x 3.6e+95)
                 (*
                  y0
                  (+ (* x (- (* c y2) (* b j))) (* y5 (- (* j y3) (* k y2)))))
                 (if (<= x 3.6e+135)
                   t_1
                   (* x (* y2 (- (* c y0) (* a y1))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4))));
	double tmp;
	if (x <= -1.12e+170) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (x <= -4.5e-11) {
		tmp = t_1;
	} else if (x <= -1.1e-201) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (x <= -7e-293) {
		tmp = t_1;
	} else if (x <= 1.35e-266) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (x <= 1.75e+26) {
		tmp = t_1;
	} else if (x <= 3.6e+95) {
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	} else if (x <= 3.6e+135) {
		tmp = t_1;
	} else {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4))))
    if (x <= (-1.12d+170)) then
        tmp = a * (x * ((y * b) - (y1 * y2)))
    else if (x <= (-4.5d-11)) then
        tmp = t_1
    else if (x <= (-1.1d-201)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (x <= (-7d-293)) then
        tmp = t_1
    else if (x <= 1.35d-266) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (x <= 1.75d+26) then
        tmp = t_1
    else if (x <= 3.6d+95) then
        tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
    else if (x <= 3.6d+135) then
        tmp = t_1
    else
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4))));
	double tmp;
	if (x <= -1.12e+170) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (x <= -4.5e-11) {
		tmp = t_1;
	} else if (x <= -1.1e-201) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (x <= -7e-293) {
		tmp = t_1;
	} else if (x <= 1.35e-266) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (x <= 1.75e+26) {
		tmp = t_1;
	} else if (x <= 3.6e+95) {
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	} else if (x <= 3.6e+135) {
		tmp = t_1;
	} else {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4))))
	tmp = 0
	if x <= -1.12e+170:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	elif x <= -4.5e-11:
		tmp = t_1
	elif x <= -1.1e-201:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif x <= -7e-293:
		tmp = t_1
	elif x <= 1.35e-266:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif x <= 1.75e+26:
		tmp = t_1
	elif x <= 3.6e+95:
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
	elif x <= 3.6e+135:
		tmp = t_1
	else:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4)))))
	tmp = 0.0
	if (x <= -1.12e+170)
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	elseif (x <= -4.5e-11)
		tmp = t_1;
	elseif (x <= -1.1e-201)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (x <= -7e-293)
		tmp = t_1;
	elseif (x <= 1.35e-266)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (x <= 1.75e+26)
		tmp = t_1;
	elseif (x <= 3.6e+95)
		tmp = Float64(y0 * Float64(Float64(x * Float64(Float64(c * y2) - Float64(b * j))) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (x <= 3.6e+135)
		tmp = t_1;
	else
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) + (y * ((i * y5) - (b * y4))));
	tmp = 0.0;
	if (x <= -1.12e+170)
		tmp = a * (x * ((y * b) - (y1 * y2)));
	elseif (x <= -4.5e-11)
		tmp = t_1;
	elseif (x <= -1.1e-201)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (x <= -7e-293)
		tmp = t_1;
	elseif (x <= 1.35e-266)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (x <= 1.75e+26)
		tmp = t_1;
	elseif (x <= 3.6e+95)
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	elseif (x <= 3.6e+135)
		tmp = t_1;
	else
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.12e+170], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -4.5e-11], t$95$1, If[LessEqual[x, -1.1e-201], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -7e-293], t$95$1, If[LessEqual[x, 1.35e-266], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.75e+26], t$95$1, If[LessEqual[x, 3.6e+95], N[(y0 * N[(N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.6e+135], t$95$1, N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if x < -1.1200000000000001e170

   1. Initial program 14.7%

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

   2. Taylor expanded in x around inf 41.4%

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

   3. Taylor expanded in a around inf 54.9%

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

      1. *-commutative 54.9%

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

      2. +-commutative 54.9%

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

      3. mul-1-neg 54.9%

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

      4. sub-neg 54.9%

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

      5. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if -1.1200000000000001e170 < x < -4.5e-11 or -1.1e-201 < x < -7.0000000000000004e-293 or 1.34999999999999998e-266 < x < 1.75e26 or 3.59999999999999978e95 < x < 3.5999999999999998e135

   1. Initial program 25.7%

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

   2. Taylor expanded in k around -inf 50.4%

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

      1. mul-1-neg 50.4%

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

      2. *-commutative 50.4%

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

      3. distribute-rgt-neg-in 50.4%

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

      4. +-commutative 50.4%

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

      5. mul-1-neg 50.4%

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

      6. unsub-neg 50.4%

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

      7. *-commutative 50.4%

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

   4. Simplified 50.4%

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

   5. Taylor expanded in z around 0 53.5%

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

   if -4.5e-11 < x < -1.1e-201

   1. Initial program 33.6%

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

   2. Taylor expanded in j around inf 57.1%

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

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

   4. Simplified 57.1%

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

   5. Taylor expanded in t around inf 47.4%

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

      1. *-commutative 47.4%

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

      2. *-commutative 47.4%

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

   7. Simplified 47.4%

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

   if -7.0000000000000004e-293 < x < 1.34999999999999998e-266

   1. Initial program 33.3%

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

   2. Taylor expanded in y2 around inf 22.5%

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

      1. *-commutative 22.5%

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

   4. Simplified 22.5%

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

   5. Taylor expanded in t around inf 56.9%

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

   if 1.75e26 < x < 3.59999999999999978e95

   1. Initial program 33.3%

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

   2. Taylor expanded in x around inf 44.5%

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

   3. Taylor expanded in y0 around inf 56.2%

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

      1. +-commutative 56.2%

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

      2. mul-1-neg 56.2%

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

      3. unsub-neg 56.2%

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

      4. *-commutative 56.2%

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

   5. Simplified 56.2%

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

   if 3.5999999999999998e135 < x

   1. Initial program 18.1%

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

   2. Taylor expanded in y2 around inf 25.8%

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

      1. *-commutative 25.8%

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

   4. Simplified 25.8%

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

   5. Taylor expanded in x around inf 58.1%

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

4. Final simplification 53.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.12 \cdot 10^{+170}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -4.5 \cdot 10^{-11}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq -1.1 \cdot 10^{-201}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq -7 \cdot 10^{-293}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq 1.35 \cdot 10^{-266}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq 1.75 \cdot 10^{+26}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq 3.6 \cdot 10^{+95}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq 3.6 \cdot 10^{+135}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \end{array} \]

Alternative 8: 31.7% accurate, 2.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ t_2 := \left(k \cdot y5\right) \cdot \left(y \cdot i - y0 \cdot y2\right)\\ t_3 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ t_4 := i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{if}\;t \leq -4.5 \cdot 10^{+106}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{+68}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -6 \cdot 10^{+17}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq -8 \cdot 10^{-76}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -1.08 \cdot 10^{-106}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-284}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{-123}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{-72}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 6500000000000:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{+102}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{+146} \lor \neg \left(t \leq 1.7 \cdot 10^{+188}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (- (* b y4) (* i y5)))))
        (t_2 (* (* k y5) (- (* y i) (* y0 y2))))
        (t_3 (* x (* y2 (- (* c y0) (* a y1)))))
        (t_4 (* i (* k (- (* y y5) (* z y1))))))
   (if (<= t -4.5e+106)
     t_1
     (if (<= t -3.4e+68)
       (* c (* y4 (* t (- y2))))
       (if (<= t -6e+17)
         t_4
         (if (<= t -8e-76)
           t_2
           (if (<= t -1.08e-106)
             (* y1 (* y4 (- (* k y2) (* j y3))))
             (if (<= t -1.1e-284)
               t_3
               (if (<= t 2.75e-123)
                 t_4
                 (if (<= t 1.15e-72)
                   t_3
                   (if (<= t 6500000000000.0)
                     (* (* k y4) (- (* y1 y2) (* y b)))
                     (if (<= t 1.9e+102)
                       (* j (* y0 (- (* y3 y5) (* x b))))
                       (if (or (<= t 3.6e+146) (not (<= t 1.7e+188)))
                         t_1
                         t_2)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double t_2 = (k * y5) * ((y * i) - (y0 * y2));
	double t_3 = x * (y2 * ((c * y0) - (a * y1)));
	double t_4 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (t <= -4.5e+106) {
		tmp = t_1;
	} else if (t <= -3.4e+68) {
		tmp = c * (y4 * (t * -y2));
	} else if (t <= -6e+17) {
		tmp = t_4;
	} else if (t <= -8e-76) {
		tmp = t_2;
	} else if (t <= -1.08e-106) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (t <= -1.1e-284) {
		tmp = t_3;
	} else if (t <= 2.75e-123) {
		tmp = t_4;
	} else if (t <= 1.15e-72) {
		tmp = t_3;
	} else if (t <= 6500000000000.0) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.9e+102) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if ((t <= 3.6e+146) || !(t <= 1.7e+188)) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = j * (t * ((b * y4) - (i * y5)))
    t_2 = (k * y5) * ((y * i) - (y0 * y2))
    t_3 = x * (y2 * ((c * y0) - (a * y1)))
    t_4 = i * (k * ((y * y5) - (z * y1)))
    if (t <= (-4.5d+106)) then
        tmp = t_1
    else if (t <= (-3.4d+68)) then
        tmp = c * (y4 * (t * -y2))
    else if (t <= (-6d+17)) then
        tmp = t_4
    else if (t <= (-8d-76)) then
        tmp = t_2
    else if (t <= (-1.08d-106)) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (t <= (-1.1d-284)) then
        tmp = t_3
    else if (t <= 2.75d-123) then
        tmp = t_4
    else if (t <= 1.15d-72) then
        tmp = t_3
    else if (t <= 6500000000000.0d0) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (t <= 1.9d+102) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if ((t <= 3.6d+146) .or. (.not. (t <= 1.7d+188))) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double t_2 = (k * y5) * ((y * i) - (y0 * y2));
	double t_3 = x * (y2 * ((c * y0) - (a * y1)));
	double t_4 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (t <= -4.5e+106) {
		tmp = t_1;
	} else if (t <= -3.4e+68) {
		tmp = c * (y4 * (t * -y2));
	} else if (t <= -6e+17) {
		tmp = t_4;
	} else if (t <= -8e-76) {
		tmp = t_2;
	} else if (t <= -1.08e-106) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (t <= -1.1e-284) {
		tmp = t_3;
	} else if (t <= 2.75e-123) {
		tmp = t_4;
	} else if (t <= 1.15e-72) {
		tmp = t_3;
	} else if (t <= 6500000000000.0) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.9e+102) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if ((t <= 3.6e+146) || !(t <= 1.7e+188)) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (t * ((b * y4) - (i * y5)))
	t_2 = (k * y5) * ((y * i) - (y0 * y2))
	t_3 = x * (y2 * ((c * y0) - (a * y1)))
	t_4 = i * (k * ((y * y5) - (z * y1)))
	tmp = 0
	if t <= -4.5e+106:
		tmp = t_1
	elif t <= -3.4e+68:
		tmp = c * (y4 * (t * -y2))
	elif t <= -6e+17:
		tmp = t_4
	elif t <= -8e-76:
		tmp = t_2
	elif t <= -1.08e-106:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif t <= -1.1e-284:
		tmp = t_3
	elif t <= 2.75e-123:
		tmp = t_4
	elif t <= 1.15e-72:
		tmp = t_3
	elif t <= 6500000000000.0:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif t <= 1.9e+102:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif (t <= 3.6e+146) or not (t <= 1.7e+188):
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))))
	t_2 = Float64(Float64(k * y5) * Float64(Float64(y * i) - Float64(y0 * y2)))
	t_3 = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	t_4 = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))))
	tmp = 0.0
	if (t <= -4.5e+106)
		tmp = t_1;
	elseif (t <= -3.4e+68)
		tmp = Float64(c * Float64(y4 * Float64(t * Float64(-y2))));
	elseif (t <= -6e+17)
		tmp = t_4;
	elseif (t <= -8e-76)
		tmp = t_2;
	elseif (t <= -1.08e-106)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (t <= -1.1e-284)
		tmp = t_3;
	elseif (t <= 2.75e-123)
		tmp = t_4;
	elseif (t <= 1.15e-72)
		tmp = t_3;
	elseif (t <= 6500000000000.0)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (t <= 1.9e+102)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif ((t <= 3.6e+146) || !(t <= 1.7e+188))
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (t * ((b * y4) - (i * y5)));
	t_2 = (k * y5) * ((y * i) - (y0 * y2));
	t_3 = x * (y2 * ((c * y0) - (a * y1)));
	t_4 = i * (k * ((y * y5) - (z * y1)));
	tmp = 0.0;
	if (t <= -4.5e+106)
		tmp = t_1;
	elseif (t <= -3.4e+68)
		tmp = c * (y4 * (t * -y2));
	elseif (t <= -6e+17)
		tmp = t_4;
	elseif (t <= -8e-76)
		tmp = t_2;
	elseif (t <= -1.08e-106)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (t <= -1.1e-284)
		tmp = t_3;
	elseif (t <= 2.75e-123)
		tmp = t_4;
	elseif (t <= 1.15e-72)
		tmp = t_3;
	elseif (t <= 6500000000000.0)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (t <= 1.9e+102)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif ((t <= 3.6e+146) || ~((t <= 1.7e+188)))
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(k * y5), $MachinePrecision] * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -4.5e+106], t$95$1, If[LessEqual[t, -3.4e+68], N[(c * N[(y4 * N[(t * (-y2)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -6e+17], t$95$4, If[LessEqual[t, -8e-76], t$95$2, If[LessEqual[t, -1.08e-106], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.1e-284], t$95$3, If[LessEqual[t, 2.75e-123], t$95$4, If[LessEqual[t, 1.15e-72], t$95$3, If[LessEqual[t, 6500000000000.0], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.9e+102], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[t, 3.6e+146], N[Not[LessEqual[t, 1.7e+188]], $MachinePrecision]], t$95$1, t$95$2]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -4.4999999999999997e106 or 1.89999999999999989e102 < t < 3.5999999999999998e146 or 1.69999999999999998e188 < t

   1. Initial program 19.2%

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

   2. Taylor expanded in j around inf 51.0%

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

      1. +-commutative 51.0%

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

      2. mul-1-neg 51.0%

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

      3. unsub-neg 51.0%

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

      4. *-commutative 51.0%

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

   4. Simplified 51.0%

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

   5. Taylor expanded in t around inf 51.1%

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

      1. *-commutative 51.1%

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

      2. *-commutative 51.1%

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

   7. Simplified 51.1%

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

   if -4.4999999999999997e106 < t < -3.40000000000000015e68

   1. Initial program 30.8%

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

   2. Taylor expanded in y2 around inf 15.8%

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

      1. *-commutative 15.8%

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

   4. Simplified 15.8%

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

   5. Taylor expanded in t around inf 31.8%

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

   6. Taylor expanded in a around 0 55.0%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 55.0%

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

      2. distribute-rgt-neg-in 55.0%

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

      3. associate-*r* 62.2%

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

      4. *-commutative 62.2%

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

      5. *-commutative 62.2%

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

   8. Simplified 62.2%

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

   if -3.40000000000000015e68 < t < -6e17 or -1.1e-284 < t < 2.75e-123

   1. Initial program 33.4%

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

   2. Taylor expanded in k around -inf 44.7%

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

      1. mul-1-neg 44.7%

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

      2. *-commutative 44.7%

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

      3. distribute-rgt-neg-in 44.7%

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

      4. +-commutative 44.7%

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

      5. mul-1-neg 44.7%

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

      6. unsub-neg 44.7%

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

      7. *-commutative 44.7%

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

   4. Simplified 44.7%

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

   5. Taylor expanded in i around -inf 49.1%

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

   if -6e17 < t < -7.99999999999999942e-76 or 3.5999999999999998e146 < t < 1.69999999999999998e188

   1. Initial program 17.2%

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

   2. Taylor expanded in k around -inf 45.6%

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

      1. mul-1-neg 45.6%

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

      2. *-commutative 45.6%

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

      3. distribute-rgt-neg-in 45.6%

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

      4. +-commutative 45.6%

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

      5. mul-1-neg 45.6%

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

      6. unsub-neg 45.6%

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

      7. *-commutative 45.6%

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

   4. Simplified 45.6%

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

   5. Taylor expanded in y5 around -inf 56.7%

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

      1. associate-*r* 59.7%

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

      2. *-commutative 59.7%

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

   7. Simplified 59.7%

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

   if -7.99999999999999942e-76 < t < -1.08e-106

   1. Initial program 25.0%

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

   2. Taylor expanded in y1 around -inf 26.3%

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

      1. mul-1-neg 26.3%

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

      2. *-commutative 26.3%

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

      3. distribute-rgt-neg-in 26.3%

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

   4. Simplified 26.3%

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

   5. Taylor expanded in y4 around -inf 51.0%

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

   if -1.08e-106 < t < -1.1e-284 or 2.75e-123 < t < 1.14999999999999997e-72

   1. Initial program 25.3%

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

   2. Taylor expanded in y2 around inf 37.2%

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

      1. *-commutative 37.2%

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

   4. Simplified 37.2%

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

   5. Taylor expanded in x around inf 56.5%

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

   if 1.14999999999999997e-72 < t < 6.5e12

   1. Initial program 26.7%

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

   2. Taylor expanded in k around -inf 46.7%

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

      1. mul-1-neg 46.7%

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

      2. *-commutative 46.7%

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

      3. distribute-rgt-neg-in 46.7%

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

      4. +-commutative 46.7%

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

      5. mul-1-neg 46.7%

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

      6. unsub-neg 46.7%

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

      7. *-commutative 46.7%

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

   4. Simplified 46.7%

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

   5. Taylor expanded in y4 around -inf 60.8%

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

      1. associate-*r* 60.6%

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

      2. associate-*r* 60.6%

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

      3. neg-mul-1 60.6%

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

      4. cancel-sign-sub 60.6%

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

      5. +-commutative 60.6%

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

      6. mul-1-neg 60.6%

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

      7. unsub-neg 60.6%

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

      8. *-commutative 60.6%

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

   7. Simplified 60.6%

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

   if 6.5e12 < t < 1.89999999999999989e102

   1. Initial program 31.2%

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

   2. Taylor expanded in j around inf 39.0%

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

      1. +-commutative 39.0%

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

      2. mul-1-neg 39.0%

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

      3. unsub-neg 39.0%

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

      4. *-commutative 39.0%

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

   4. Simplified 39.0%

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

   5. Taylor expanded in y0 around -inf 39.5%

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

      1. +-commutative 39.5%

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

      2. mul-1-neg 39.5%

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

      3. unsub-neg 39.5%

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

      4. *-commutative 39.5%

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

   7. Simplified 39.5%

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

4. Final simplification 52.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -4.5 \cdot 10^{+106}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{+68}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;t \leq -6 \cdot 10^{+17}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -8 \cdot 10^{-76}:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i - y0 \cdot y2\right)\\ \mathbf{elif}\;t \leq -1.08 \cdot 10^{-106}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-284}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{-123}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{-72}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 6500000000000:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{+102}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{+146} \lor \neg \left(t \leq 1.7 \cdot 10^{+188}\right):\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i - y0 \cdot y2\right)\\ \end{array} \]

Alternative 9: 32.1% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ t_2 := \left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{if}\;j \leq -8.8 \cdot 10^{+141}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -2.35 \cdot 10^{+48}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -6000000:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.4 \cdot 10^{-49}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -1.55 \cdot 10^{-232}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 1.65 \cdot 10^{-290}:\\ \;\;\;\;y0 \cdot \left(k \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 3.45 \cdot 10^{-13}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq 0.0116:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 3 \cdot 10^{+230}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (- (* y2 (- (* y1 y4) (* y0 y5))) (* y4 (* y b)))))
        (t_2 (* (* b j) (- (* t y4) (* x y0)))))
   (if (<= j -8.8e+141)
     (* y0 (+ (* x (- (* c y2) (* b j))) (* y5 (- (* j y3) (* k y2)))))
     (if (<= j -2.35e+48)
       (* t (* y2 (- (* a y5) (* c y4))))
       (if (<= j -6000000.0)
         (* x (* y (- (* a b) (* c i))))
         (if (<= j -1.4e-49)
           (* j (* x (- (* i y1) (* b y0))))
           (if (<= j -1.55e-232)
             t_1
             (if (<= j 1.65e-290)
               (* y0 (* k (- (* z b) (* y2 y5))))
               (if (<= j 5e-44)
                 t_1
                 (if (<= j 3.45e-13)
                   t_2
                   (if (<= j 0.0116)
                     (* b (* k (* y (- y4))))
                     (if (<= j 3e+230)
                       (* y1 (* x (- (* i j) (* a y2))))
                       t_2))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)));
	double t_2 = (b * j) * ((t * y4) - (x * y0));
	double tmp;
	if (j <= -8.8e+141) {
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	} else if (j <= -2.35e+48) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= -6000000.0) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -1.4e-49) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (j <= -1.55e-232) {
		tmp = t_1;
	} else if (j <= 1.65e-290) {
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	} else if (j <= 5e-44) {
		tmp = t_1;
	} else if (j <= 3.45e-13) {
		tmp = t_2;
	} else if (j <= 0.0116) {
		tmp = b * (k * (y * -y4));
	} else if (j <= 3e+230) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)))
    t_2 = (b * j) * ((t * y4) - (x * y0))
    if (j <= (-8.8d+141)) then
        tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
    else if (j <= (-2.35d+48)) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (j <= (-6000000.0d0)) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (j <= (-1.4d-49)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (j <= (-1.55d-232)) then
        tmp = t_1
    else if (j <= 1.65d-290) then
        tmp = y0 * (k * ((z * b) - (y2 * y5)))
    else if (j <= 5d-44) then
        tmp = t_1
    else if (j <= 3.45d-13) then
        tmp = t_2
    else if (j <= 0.0116d0) then
        tmp = b * (k * (y * -y4))
    else if (j <= 3d+230) then
        tmp = y1 * (x * ((i * j) - (a * y2)))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)));
	double t_2 = (b * j) * ((t * y4) - (x * y0));
	double tmp;
	if (j <= -8.8e+141) {
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	} else if (j <= -2.35e+48) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (j <= -6000000.0) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (j <= -1.4e-49) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (j <= -1.55e-232) {
		tmp = t_1;
	} else if (j <= 1.65e-290) {
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	} else if (j <= 5e-44) {
		tmp = t_1;
	} else if (j <= 3.45e-13) {
		tmp = t_2;
	} else if (j <= 0.0116) {
		tmp = b * (k * (y * -y4));
	} else if (j <= 3e+230) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)))
	t_2 = (b * j) * ((t * y4) - (x * y0))
	tmp = 0
	if j <= -8.8e+141:
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))))
	elif j <= -2.35e+48:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif j <= -6000000.0:
		tmp = x * (y * ((a * b) - (c * i)))
	elif j <= -1.4e-49:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif j <= -1.55e-232:
		tmp = t_1
	elif j <= 1.65e-290:
		tmp = y0 * (k * ((z * b) - (y2 * y5)))
	elif j <= 5e-44:
		tmp = t_1
	elif j <= 3.45e-13:
		tmp = t_2
	elif j <= 0.0116:
		tmp = b * (k * (y * -y4))
	elif j <= 3e+230:
		tmp = y1 * (x * ((i * j) - (a * y2)))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) - Float64(y4 * Float64(y * b))))
	t_2 = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)))
	tmp = 0.0
	if (j <= -8.8e+141)
		tmp = Float64(y0 * Float64(Float64(x * Float64(Float64(c * y2) - Float64(b * j))) + Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2)))));
	elseif (j <= -2.35e+48)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (j <= -6000000.0)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (j <= -1.4e-49)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (j <= -1.55e-232)
		tmp = t_1;
	elseif (j <= 1.65e-290)
		tmp = Float64(y0 * Float64(k * Float64(Float64(z * b) - Float64(y2 * y5))));
	elseif (j <= 5e-44)
		tmp = t_1;
	elseif (j <= 3.45e-13)
		tmp = t_2;
	elseif (j <= 0.0116)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (j <= 3e+230)
		tmp = Float64(y1 * Float64(x * Float64(Float64(i * j) - Float64(a * y2))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)));
	t_2 = (b * j) * ((t * y4) - (x * y0));
	tmp = 0.0;
	if (j <= -8.8e+141)
		tmp = y0 * ((x * ((c * y2) - (b * j))) + (y5 * ((j * y3) - (k * y2))));
	elseif (j <= -2.35e+48)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (j <= -6000000.0)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (j <= -1.4e-49)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (j <= -1.55e-232)
		tmp = t_1;
	elseif (j <= 1.65e-290)
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	elseif (j <= 5e-44)
		tmp = t_1;
	elseif (j <= 3.45e-13)
		tmp = t_2;
	elseif (j <= 0.0116)
		tmp = b * (k * (y * -y4));
	elseif (j <= 3e+230)
		tmp = y1 * (x * ((i * j) - (a * y2)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -8.8e+141], N[(y0 * N[(N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.35e+48], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -6000000.0], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.4e-49], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.55e-232], t$95$1, If[LessEqual[j, 1.65e-290], N[(y0 * N[(k * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5e-44], t$95$1, If[LessEqual[j, 3.45e-13], t$95$2, If[LessEqual[j, 0.0116], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3e+230], N[(y1 * N[(x * N[(N[(i * j), $MachinePrecision] - N[(a * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if j < -8.8e141

   1. Initial program 20.2%

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

   2. Taylor expanded in x around inf 48.9%

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

   3. Taylor expanded in y0 around inf 53.8%

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

      1. +-commutative 53.8%

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

      2. mul-1-neg 53.8%

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

      3. unsub-neg 53.8%

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

      4. *-commutative 53.8%

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

   5. Simplified 53.8%

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

   if -8.8e141 < j < -2.35000000000000006e48

   1. Initial program 22.2%

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

   2. Taylor expanded in y2 around inf 33.5%

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

      1. *-commutative 33.5%

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

   4. Simplified 33.5%

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

   5. Taylor expanded in t around inf 51.9%

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

   if -2.35000000000000006e48 < j < -6e6

   1. Initial program 42.9%

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

   2. Taylor expanded in x around inf 72.4%

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

   3. Taylor expanded in y around inf 72.2%

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

   if -6e6 < j < -1.39999999999999999e-49

   1. Initial program 34.1%

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

   2. Taylor expanded in j around inf 67.1%

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

      1. +-commutative 67.1%

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

      2. mul-1-neg 67.1%

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

      3. unsub-neg 67.1%

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

      4. *-commutative 67.1%

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

   4. Simplified 67.1%

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

   5. Taylor expanded in x around inf 56.7%

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

   if -1.39999999999999999e-49 < j < -1.5499999999999999e-232 or 1.64999999999999993e-290 < j < 5.00000000000000039e-44

   1. Initial program 29.5%

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

   2. Taylor expanded in k around -inf 45.7%

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

      1. mul-1-neg 45.7%

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

      2. *-commutative 45.7%

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

      3. distribute-rgt-neg-in 45.7%

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

      4. +-commutative 45.7%

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

      5. mul-1-neg 45.7%

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

      6. unsub-neg 45.7%

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

      7. *-commutative 45.7%

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

   4. Simplified 45.7%

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

   5. Taylor expanded in z around 0 48.1%

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

   6. Taylor expanded in b around inf 45.7%

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

      1. associate-*r* 49.1%

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

      2. *-commutative 49.1%

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

      3. *-commutative 49.1%

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

   8. Simplified 49.1%

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

   if -1.5499999999999999e-232 < j < 1.64999999999999993e-290

   1. Initial program 31.8%

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

   2. Taylor expanded in k around -inf 55.9%

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

      1. mul-1-neg 55.9%

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

      2. *-commutative 55.9%

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

      3. distribute-rgt-neg-in 55.9%

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

      4. +-commutative 55.9%

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

      5. mul-1-neg 55.9%

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

      6. unsub-neg 55.9%

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

      7. *-commutative 55.9%

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

   4. Simplified 55.9%

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

   5. Taylor expanded in y0 around -inf 56.5%

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

      1. +-commutative 56.5%

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

      2. mul-1-neg 56.5%

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

      3. unsub-neg 56.5%

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

      4. *-commutative 56.5%

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

      5. *-commutative 56.5%

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

   7. Simplified 56.5%

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

   8. Taylor expanded in y0 around 0 56.5%

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

      1. mul-1-neg 56.5%

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

      2. *-commutative 56.5%

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

      3. *-commutative 56.5%

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

      4. sub-neg 56.5%

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

      5. sub-neg 56.5%

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

      6. distribute-rgt-neg-in 56.5%

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

      7. associate-*r* 69.2%

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

   10. Simplified 69.2%

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

   if 5.00000000000000039e-44 < j < 3.44999999999999994e-13 or 3.00000000000000008e230 < j

   1. Initial program 12.8%

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

   2. Taylor expanded in j around inf 47.1%

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

      1. +-commutative 47.1%

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

      2. mul-1-neg 47.1%

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

      3. unsub-neg 47.1%

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

      4. *-commutative 47.1%

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

   4. Simplified 47.1%

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

   5. Taylor expanded in b around inf 53.9%

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

      1. associate-*r* 54.0%

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

      2. *-commutative 54.0%

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

      3. *-commutative 54.0%

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

   7. Simplified 54.0%

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

   if 3.44999999999999994e-13 < j < 0.0116

   1. Initial program 25.0%

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

   2. Taylor expanded in k around -inf 50.0%

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

      1. mul-1-neg 50.0%

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

      2. *-commutative 50.0%

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

      3. distribute-rgt-neg-in 50.0%

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

      4. +-commutative 50.0%

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

      5. mul-1-neg 50.0%

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

      6. unsub-neg 50.0%

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

      7. *-commutative 50.0%

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

   4. Simplified 50.0%

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

   5. Taylor expanded in z around 0 50.0%

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

   6. Taylor expanded in b around inf 100.0%

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

      1. mul-1-neg 100.0%

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

      2. distribute-rgt-neg-in 100.0%

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

      3. *-commutative 100.0%

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

   8. Simplified 100.0%

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

   if 0.0116 < j < 3.00000000000000008e230

   1. Initial program 22.7%

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

   2. Taylor expanded in y1 around -inf 61.8%

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

      1. mul-1-neg 61.8%

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

      2. *-commutative 61.8%

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

      3. distribute-rgt-neg-in 61.8%

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

   4. Simplified 61.8%

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

   5. Taylor expanded in x around inf 60.0%

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

      1. *-commutative 60.0%

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

   7. Simplified 60.0%

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

4. Final simplification 55.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -8.8 \cdot 10^{+141}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right) + y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -2.35 \cdot 10^{+48}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -6000000:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;j \leq -1.4 \cdot 10^{-49}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -1.55 \cdot 10^{-232}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \mathbf{elif}\;j \leq 1.65 \cdot 10^{-290}:\\ \;\;\;\;y0 \cdot \left(k \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-44}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \mathbf{elif}\;j \leq 3.45 \cdot 10^{-13}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;j \leq 0.0116:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 3 \cdot 10^{+230}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \end{array} \]

Alternative 10: 32.1% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ t_2 := j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{if}\;i \leq -8.2 \cdot 10^{+191}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq -1.12 \cdot 10^{+104}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -1 \cdot 10^{+43}:\\ \;\;\;\;t_2 - j \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -7.3 \cdot 10^{-19}:\\ \;\;\;\;y0 \cdot \left(k \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq -3.6 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq -5.2 \cdot 10^{-85}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 4.4 \cdot 10^{+20}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \mathbf{elif}\;i \leq 8.5 \cdot 10^{+188}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (- (* b y4) (* i y5))))) (t_2 (* j (* y1 (* x i)))))
   (if (<= i -8.2e+191)
     (* y1 (* x (- (* i j) (* a y2))))
     (if (<= i -1.12e+104)
       (* i (* k (- (* y y5) (* z y1))))
       (if (<= i -1e+43)
         (- t_2 (* j (* x (* b y0))))
         (if (<= i -7.3e-19)
           (* y0 (* k (- (* z b) (* y2 y5))))
           (if (<= i -3.6e-32)
             t_1
             (if (<= i -5.2e-85)
               (* j (* y3 (- (* y0 y5) (* y1 y4))))
               (if (<= i 4.4e+20)
                 (* k (- (* y2 (- (* y1 y4) (* y0 y5))) (* y4 (* y b))))
                 (if (<= i 8.5e+188) t_1 t_2))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double t_2 = j * (y1 * (x * i));
	double tmp;
	if (i <= -8.2e+191) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (i <= -1.12e+104) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -1e+43) {
		tmp = t_2 - (j * (x * (b * y0)));
	} else if (i <= -7.3e-19) {
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	} else if (i <= -3.6e-32) {
		tmp = t_1;
	} else if (i <= -5.2e-85) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 4.4e+20) {
		tmp = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)));
	} else if (i <= 8.5e+188) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (t * ((b * y4) - (i * y5)))
    t_2 = j * (y1 * (x * i))
    if (i <= (-8.2d+191)) then
        tmp = y1 * (x * ((i * j) - (a * y2)))
    else if (i <= (-1.12d+104)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (i <= (-1d+43)) then
        tmp = t_2 - (j * (x * (b * y0)))
    else if (i <= (-7.3d-19)) then
        tmp = y0 * (k * ((z * b) - (y2 * y5)))
    else if (i <= (-3.6d-32)) then
        tmp = t_1
    else if (i <= (-5.2d-85)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 4.4d+20) then
        tmp = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)))
    else if (i <= 8.5d+188) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double t_2 = j * (y1 * (x * i));
	double tmp;
	if (i <= -8.2e+191) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else if (i <= -1.12e+104) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -1e+43) {
		tmp = t_2 - (j * (x * (b * y0)));
	} else if (i <= -7.3e-19) {
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	} else if (i <= -3.6e-32) {
		tmp = t_1;
	} else if (i <= -5.2e-85) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 4.4e+20) {
		tmp = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)));
	} else if (i <= 8.5e+188) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (t * ((b * y4) - (i * y5)))
	t_2 = j * (y1 * (x * i))
	tmp = 0
	if i <= -8.2e+191:
		tmp = y1 * (x * ((i * j) - (a * y2)))
	elif i <= -1.12e+104:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif i <= -1e+43:
		tmp = t_2 - (j * (x * (b * y0)))
	elif i <= -7.3e-19:
		tmp = y0 * (k * ((z * b) - (y2 * y5)))
	elif i <= -3.6e-32:
		tmp = t_1
	elif i <= -5.2e-85:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 4.4e+20:
		tmp = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)))
	elif i <= 8.5e+188:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))))
	t_2 = Float64(j * Float64(y1 * Float64(x * i)))
	tmp = 0.0
	if (i <= -8.2e+191)
		tmp = Float64(y1 * Float64(x * Float64(Float64(i * j) - Float64(a * y2))));
	elseif (i <= -1.12e+104)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (i <= -1e+43)
		tmp = Float64(t_2 - Float64(j * Float64(x * Float64(b * y0))));
	elseif (i <= -7.3e-19)
		tmp = Float64(y0 * Float64(k * Float64(Float64(z * b) - Float64(y2 * y5))));
	elseif (i <= -3.6e-32)
		tmp = t_1;
	elseif (i <= -5.2e-85)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 4.4e+20)
		tmp = Float64(k * Float64(Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))) - Float64(y4 * Float64(y * b))));
	elseif (i <= 8.5e+188)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (t * ((b * y4) - (i * y5)));
	t_2 = j * (y1 * (x * i));
	tmp = 0.0;
	if (i <= -8.2e+191)
		tmp = y1 * (x * ((i * j) - (a * y2)));
	elseif (i <= -1.12e+104)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (i <= -1e+43)
		tmp = t_2 - (j * (x * (b * y0)));
	elseif (i <= -7.3e-19)
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	elseif (i <= -3.6e-32)
		tmp = t_1;
	elseif (i <= -5.2e-85)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 4.4e+20)
		tmp = k * ((y2 * ((y1 * y4) - (y0 * y5))) - (y4 * (y * b)));
	elseif (i <= 8.5e+188)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -8.2e+191], N[(y1 * N[(x * N[(N[(i * j), $MachinePrecision] - N[(a * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.12e+104], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1e+43], N[(t$95$2 - N[(j * N[(x * N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -7.3e-19], N[(y0 * N[(k * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -3.6e-32], t$95$1, If[LessEqual[i, -5.2e-85], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 4.4e+20], N[(k * N[(N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y4 * N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 8.5e+188], t$95$1, t$95$2]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if i < -8.1999999999999998e191

   1. Initial program 18.2%

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

   2. Taylor expanded in y1 around -inf 50.4%

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

      1. mul-1-neg 50.4%

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

      2. *-commutative 50.4%

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

      3. distribute-rgt-neg-in 50.4%

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

   4. Simplified 50.4%

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

   5. Taylor expanded in x around inf 68.5%

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

      1. *-commutative 68.5%

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

   7. Simplified 68.5%

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

   if -8.1999999999999998e191 < i < -1.12000000000000003e104

   1. Initial program 20.0%

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

   2. Taylor expanded in k around -inf 51.6%

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

      1. mul-1-neg 51.6%

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

      2. *-commutative 51.6%

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

      3. distribute-rgt-neg-in 51.6%

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

      4. +-commutative 51.6%

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

      5. mul-1-neg 51.6%

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

      6. unsub-neg 51.6%

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

      7. *-commutative 51.6%

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

   4. Simplified 51.6%

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

   5. Taylor expanded in i around -inf 56.6%

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

   if -1.12000000000000003e104 < i < -1.00000000000000001e43

   1. Initial program 35.7%

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

   2. Taylor expanded in j around inf 72.2%

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

      1. +-commutative 72.2%

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

      2. mul-1-neg 72.2%

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

      3. unsub-neg 72.2%

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

      4. *-commutative 72.2%

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

   4. Simplified 72.2%

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

   5. Taylor expanded in x around inf 57.9%

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

   6. Taylor expanded in i around 0 37.1%

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

      1. +-commutative 37.1%

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

      2. mul-1-neg 37.1%

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

      3. unsub-neg 37.1%

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

      4. *-commutative 37.1%

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

      5. associate-*l* 37.1%

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

      6. *-commutative 37.1%

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

      7. associate-*l* 37.1%

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

      8. *-commutative 37.1%

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

      9. *-commutative 37.1%

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

      10. associate-*l* 51.0%

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

      11. associate-*l* 57.9%

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

      12. *-commutative 57.9%

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

   8. Simplified 57.9%

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

   if -1.00000000000000001e43 < i < -7.2999999999999997e-19

   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. Taylor expanded in k around -inf 64.2%

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

      1. mul-1-neg 64.2%

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

      2. *-commutative 64.2%

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

      3. distribute-rgt-neg-in 64.2%

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

      4. +-commutative 64.2%

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

      5. mul-1-neg 64.2%

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

      6. unsub-neg 64.2%

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

      7. *-commutative 64.2%

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

   4. Simplified 64.2%

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

   5. Taylor expanded in y0 around -inf 38.6%

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

      1. +-commutative 38.6%

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

      2. mul-1-neg 38.6%

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

      3. unsub-neg 38.6%

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

      4. *-commutative 38.6%

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

      5. *-commutative 38.6%

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

   7. Simplified 38.6%

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

   8. Taylor expanded in y0 around 0 38.6%

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

      1. mul-1-neg 38.6%

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

      2. *-commutative 38.6%

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

      3. *-commutative 38.6%

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

      4. sub-neg 38.6%

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

      5. sub-neg 38.6%

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

      6. distribute-rgt-neg-in 38.6%

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

      7. associate-*r* 55.3%

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

   10. Simplified 55.3%

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

   if -7.2999999999999997e-19 < i < -3.59999999999999993e-32 or 4.4e20 < i < 8.49999999999999958e188

   1. Initial program 21.7%

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

   2. Taylor expanded in j around inf 52.0%

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

      1. +-commutative 52.0%

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

      2. mul-1-neg 52.0%

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

      3. unsub-neg 52.0%

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

      4. *-commutative 52.0%

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

   4. Simplified 52.0%

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

   5. Taylor expanded in t around inf 58.0%

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

      1. *-commutative 58.0%

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

      2. *-commutative 58.0%

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

   7. Simplified 58.0%

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

   if -3.59999999999999993e-32 < i < -5.20000000000000023e-85

   1. Initial program 33.3%

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

   2. Taylor expanded in j around inf 44.8%

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

      1. +-commutative 44.8%

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

      2. mul-1-neg 44.8%

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

      3. unsub-neg 44.8%

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

      4. *-commutative 44.8%

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

   4. Simplified 44.8%

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

   5. Taylor expanded in y3 around inf 67.6%

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

      1. *-commutative 67.6%

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

      2. *-commutative 67.6%

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

   7. Simplified 67.6%

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

   if -5.20000000000000023e-85 < i < 4.4e20

   1. Initial program 28.0%

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

   2. Taylor expanded in k around -inf 41.1%

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

      1. mul-1-neg 41.1%

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

      2. *-commutative 41.1%

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

      3. distribute-rgt-neg-in 41.1%

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

      4. +-commutative 41.1%

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

      5. mul-1-neg 41.1%

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

      6. unsub-neg 41.1%

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

      7. *-commutative 41.1%

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

   4. Simplified 41.1%

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

   5. Taylor expanded in z around 0 42.9%

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

   6. Taylor expanded in b around inf 41.1%

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

      1. associate-*r* 44.5%

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

      2. *-commutative 44.5%

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

      3. *-commutative 44.5%

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

   8. Simplified 44.5%

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

   if 8.49999999999999958e188 < i

   1. Initial program 12.5%

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

   2. Taylor expanded in j around inf 25.0%

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

      1. +-commutative 25.0%

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

      2. mul-1-neg 25.0%

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

      3. unsub-neg 25.0%

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

      4. *-commutative 25.0%

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

   4. Simplified 25.0%

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

   5. Taylor expanded in x around inf 44.4%

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

   6. Taylor expanded in i around inf 41.7%

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

      1. *-commutative 41.7%

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

      2. associate-*l* 47.6%

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

      3. *-commutative 47.6%

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

      4. associate-*l* 59.5%

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

      5. *-commutative 59.5%

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

   8. Simplified 59.5%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 53.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -8.2 \cdot 10^{+191}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq -1.12 \cdot 10^{+104}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -1 \cdot 10^{+43}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right) - j \cdot \left(x \cdot \left(b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -7.3 \cdot 10^{-19}:\\ \;\;\;\;y0 \cdot \left(k \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq -3.6 \cdot 10^{-32}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq -5.2 \cdot 10^{-85}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 4.4 \cdot 10^{+20}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) - y4 \cdot \left(y \cdot b\right)\right)\\ \mathbf{elif}\;i \leq 8.5 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 11: 28.0% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -8.5 \cdot 10^{+191}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;i \leq -1.75 \cdot 10^{-41}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.05 \cdot 10^{-110}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 6.5 \cdot 10^{-306}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 2.75 \cdot 10^{-279}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 2 \cdot 10^{-243}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;i \leq 2 \cdot 10^{-120}:\\ \;\;\;\;y0 \cdot \left(k \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 1.35:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 3.6 \cdot 10^{+189}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -8.5e+191)
   (* (* b j) (- (* t y4) (* x y0)))
   (if (<= i -1.75e-41)
     (* i (* k (- (* y y5) (* z y1))))
     (if (<= i -2.05e-110)
       (* j (* y3 (- (* y0 y5) (* y1 y4))))
       (if (<= i 6.5e-306)
         (* x (* y2 (- (* c y0) (* a y1))))
         (if (<= i 2.75e-279)
           (* y1 (* y4 (- (* k y2) (* j y3))))
           (if (<= i 2e-243)
             (* a (* b (* x y)))
             (if (<= i 2e-120)
               (* y0 (* k (- (* z b) (* y2 y5))))
               (if (<= i 1.35)
                 (* a (* x (- (* y b) (* y1 y2))))
                 (if (<= i 3.6e+189)
                   (* j (* t (- (* b y4) (* i 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 <= -8.5e+191) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (i <= -1.75e-41) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -2.05e-110) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 6.5e-306) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (i <= 2.75e-279) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 2e-243) {
		tmp = a * (b * (x * y));
	} else if (i <= 2e-120) {
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	} else if (i <= 1.35) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (i <= 3.6e+189) {
		tmp = j * (t * ((b * y4) - (i * 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 <= (-8.5d+191)) then
        tmp = (b * j) * ((t * y4) - (x * y0))
    else if (i <= (-1.75d-41)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (i <= (-2.05d-110)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 6.5d-306) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (i <= 2.75d-279) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (i <= 2d-243) then
        tmp = a * (b * (x * y))
    else if (i <= 2d-120) then
        tmp = y0 * (k * ((z * b) - (y2 * y5)))
    else if (i <= 1.35d0) then
        tmp = a * (x * ((y * b) - (y1 * y2)))
    else if (i <= 3.6d+189) then
        tmp = j * (t * ((b * y4) - (i * 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 <= -8.5e+191) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (i <= -1.75e-41) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -2.05e-110) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 6.5e-306) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (i <= 2.75e-279) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 2e-243) {
		tmp = a * (b * (x * y));
	} else if (i <= 2e-120) {
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	} else if (i <= 1.35) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (i <= 3.6e+189) {
		tmp = j * (t * ((b * y4) - (i * 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 <= -8.5e+191:
		tmp = (b * j) * ((t * y4) - (x * y0))
	elif i <= -1.75e-41:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif i <= -2.05e-110:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 6.5e-306:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif i <= 2.75e-279:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif i <= 2e-243:
		tmp = a * (b * (x * y))
	elif i <= 2e-120:
		tmp = y0 * (k * ((z * b) - (y2 * y5)))
	elif i <= 1.35:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	elif i <= 3.6e+189:
		tmp = j * (t * ((b * y4) - (i * 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 <= -8.5e+191)
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	elseif (i <= -1.75e-41)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (i <= -2.05e-110)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 6.5e-306)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (i <= 2.75e-279)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (i <= 2e-243)
		tmp = Float64(a * Float64(b * Float64(x * y)));
	elseif (i <= 2e-120)
		tmp = Float64(y0 * Float64(k * Float64(Float64(z * b) - Float64(y2 * y5))));
	elseif (i <= 1.35)
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	elseif (i <= 3.6e+189)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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 <= -8.5e+191)
		tmp = (b * j) * ((t * y4) - (x * y0));
	elseif (i <= -1.75e-41)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (i <= -2.05e-110)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 6.5e-306)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (i <= 2.75e-279)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (i <= 2e-243)
		tmp = a * (b * (x * y));
	elseif (i <= 2e-120)
		tmp = y0 * (k * ((z * b) - (y2 * y5)));
	elseif (i <= 1.35)
		tmp = a * (x * ((y * b) - (y1 * y2)));
	elseif (i <= 3.6e+189)
		tmp = j * (t * ((b * y4) - (i * 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, -8.5e+191], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.75e-41], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -2.05e-110], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 6.5e-306], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2.75e-279], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2e-243], N[(a * N[(b * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2e-120], N[(y0 * N[(k * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.35], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.6e+189], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if i < -8.4999999999999999e191

   1. Initial program 18.2%

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

   2. Taylor expanded in j around inf 45.7%

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

      1. +-commutative 45.7%

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

      2. mul-1-neg 45.7%

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

      3. unsub-neg 45.7%

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

      4. *-commutative 45.7%

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

   4. Simplified 45.7%

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

   5. Taylor expanded in b around inf 46.5%

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

      1. associate-*r* 50.8%

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

      2. *-commutative 50.8%

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

      3. *-commutative 50.8%

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

   7. Simplified 50.8%

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

   if -8.4999999999999999e191 < i < -1.75e-41

   1. Initial program 33.5%

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

   2. Taylor expanded in k around -inf 57.9%

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

      1. mul-1-neg 57.9%

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

      2. *-commutative 57.9%

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

      3. distribute-rgt-neg-in 57.9%

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

      4. +-commutative 57.9%

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

      5. mul-1-neg 57.9%

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

      6. unsub-neg 57.9%

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

      7. *-commutative 57.9%

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

   4. Simplified 57.9%

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

   5. Taylor expanded in i around -inf 46.7%

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

   if -1.75e-41 < i < -2.04999999999999991e-110

   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. Taylor expanded in j around inf 39.0%

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

      1. +-commutative 39.0%

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

      2. mul-1-neg 39.0%

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

      3. unsub-neg 39.0%

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

      4. *-commutative 39.0%

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

   4. Simplified 39.0%

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

   5. Taylor expanded in y3 around inf 54.8%

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

      1. *-commutative 54.8%

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

      2. *-commutative 54.8%

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

   7. Simplified 54.8%

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

   if -2.04999999999999991e-110 < i < 6.5000000000000004e-306

   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. Taylor expanded in y2 around inf 19.7%

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

      1. *-commutative 19.7%

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

   4. Simplified 19.7%

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

   5. Taylor expanded in x around inf 39.5%

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

   if 6.5000000000000004e-306 < i < 2.7500000000000001e-279

   1. Initial program 42.9%

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

   2. Taylor expanded in y1 around -inf 43.4%

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

      1. mul-1-neg 43.4%

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

      2. *-commutative 43.4%

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

      3. distribute-rgt-neg-in 43.4%

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

   4. Simplified 43.4%

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

   5. Taylor expanded in y4 around -inf 57.7%

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

   if 2.7500000000000001e-279 < i < 1.99999999999999999e-243

   1. Initial program 12.5%

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

   2. Taylor expanded in x around inf 25.7%

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

   3. Taylor expanded in a around inf 37.9%

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

      1. *-commutative 37.9%

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

      2. +-commutative 37.9%

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

      3. mul-1-neg 37.9%

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

      4. sub-neg 37.9%

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

      5. *-commutative 37.9%

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

   5. Simplified 37.9%

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

   6. Taylor expanded in y around inf 50.6%

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

      1. *-commutative 50.6%

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

   8. Simplified 50.6%

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

   if 1.99999999999999999e-243 < i < 1.99999999999999996e-120

   1. Initial program 29.6%

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

   2. Taylor expanded in k around -inf 63.9%

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

      1. mul-1-neg 63.9%

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

      2. *-commutative 63.9%

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

      3. distribute-rgt-neg-in 63.9%

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

      4. +-commutative 63.9%

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

      5. mul-1-neg 63.9%

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

      6. unsub-neg 63.9%

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

      7. *-commutative 63.9%

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

   4. Simplified 63.9%

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

   5. Taylor expanded in y0 around -inf 52.9%

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

      1. +-commutative 52.9%

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

      2. mul-1-neg 52.9%

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

      3. unsub-neg 52.9%

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

      4. *-commutative 52.9%

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

      5. *-commutative 52.9%

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

   7. Simplified 52.9%

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

   8. Taylor expanded in y0 around 0 52.9%

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

      1. mul-1-neg 52.9%

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

      2. *-commutative 52.9%

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

      3. *-commutative 52.9%

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

      4. sub-neg 52.9%

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

      5. sub-neg 52.9%

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

      6. distribute-rgt-neg-in 52.9%

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

      7. associate-*r* 56.4%

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

   10. Simplified 56.4%

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

   if 1.99999999999999996e-120 < i < 1.3500000000000001

   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. Taylor expanded in x around inf 44.6%

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

   3. Taylor expanded in a around inf 51.1%

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

      1. *-commutative 51.1%

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

      2. +-commutative 51.1%

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

      3. mul-1-neg 51.1%

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

      4. sub-neg 51.1%

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

      5. *-commutative 51.1%

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

   5. Simplified 51.1%

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

   if 1.3500000000000001 < i < 3.60000000000000008e189

   1. Initial program 25.9%

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

   2. Taylor expanded in j around inf 54.9%

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

      1. +-commutative 54.9%

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

      2. mul-1-neg 54.9%

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

      3. unsub-neg 54.9%

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

      4. *-commutative 54.9%

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

   4. Simplified 54.9%

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

   5. Taylor expanded in t around inf 51.9%

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

      1. *-commutative 51.9%

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

      2. *-commutative 51.9%

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

   7. Simplified 51.9%

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

   if 3.60000000000000008e189 < i

   1. Initial program 12.5%

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

   2. Taylor expanded in j around inf 25.0%

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

      1. +-commutative 25.0%

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

      2. mul-1-neg 25.0%

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

      3. unsub-neg 25.0%

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

      4. *-commutative 25.0%

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

   4. Simplified 25.0%

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

   5. Taylor expanded in x around inf 44.4%

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

   6. Taylor expanded in i around inf 41.7%

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

      1. *-commutative 41.7%

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

      2. associate-*l* 47.6%

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

      3. *-commutative 47.6%

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

      4. associate-*l* 59.5%

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

      5. *-commutative 59.5%

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

   8. Simplified 59.5%

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

4. Final simplification 50.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -8.5 \cdot 10^{+191}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;i \leq -1.75 \cdot 10^{-41}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.05 \cdot 10^{-110}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 6.5 \cdot 10^{-306}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 2.75 \cdot 10^{-279}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 2 \cdot 10^{-243}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;i \leq 2 \cdot 10^{-120}:\\ \;\;\;\;y0 \cdot \left(k \cdot \left(z \cdot b - y2 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 1.35:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 3.6 \cdot 10^{+189}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 12: 31.3% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{if}\;x \leq -8 \cdot 10^{+172}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -2.6 \cdot 10^{+60}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.05 \cdot 10^{-10}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.9 \cdot 10^{-139}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq 6 \cdot 10^{-219}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 48:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq 3 \cdot 10^{+65}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq 1.62 \cdot 10^{+71}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (- (* b y4) (* i y5))))))
   (if (<= x -8e+172)
     (* a (* x (- (* y b) (* y1 y2))))
     (if (<= x -2.6e+60)
       (* c (* y2 (* x y0)))
       (if (<= x -1.05e-10)
         (* b (* k (* z y0)))
         (if (<= x -1.9e-139)
           t_1
           (if (<= x 6e-219)
             (* i (* k (- (* y y5) (* z y1))))
             (if (<= x 48.0)
               t_1
               (if (<= x 3e+65)
                 (* j (* y3 (- (* y0 y5) (* y1 y4))))
                 (if (<= x 1.62e+71)
                   t_1
                   (* 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 * (t * ((b * y4) - (i * y5)));
	double tmp;
	if (x <= -8e+172) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (x <= -2.6e+60) {
		tmp = c * (y2 * (x * y0));
	} else if (x <= -1.05e-10) {
		tmp = b * (k * (z * y0));
	} else if (x <= -1.9e-139) {
		tmp = t_1;
	} else if (x <= 6e-219) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (x <= 48.0) {
		tmp = t_1;
	} else if (x <= 3e+65) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (x <= 1.62e+71) {
		tmp = t_1;
	} 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 = j * (t * ((b * y4) - (i * y5)))
    if (x <= (-8d+172)) then
        tmp = a * (x * ((y * b) - (y1 * y2)))
    else if (x <= (-2.6d+60)) then
        tmp = c * (y2 * (x * y0))
    else if (x <= (-1.05d-10)) then
        tmp = b * (k * (z * y0))
    else if (x <= (-1.9d-139)) then
        tmp = t_1
    else if (x <= 6d-219) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (x <= 48.0d0) then
        tmp = t_1
    else if (x <= 3d+65) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (x <= 1.62d+71) then
        tmp = t_1
    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 * (t * ((b * y4) - (i * y5)));
	double tmp;
	if (x <= -8e+172) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (x <= -2.6e+60) {
		tmp = c * (y2 * (x * y0));
	} else if (x <= -1.05e-10) {
		tmp = b * (k * (z * y0));
	} else if (x <= -1.9e-139) {
		tmp = t_1;
	} else if (x <= 6e-219) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (x <= 48.0) {
		tmp = t_1;
	} else if (x <= 3e+65) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (x <= 1.62e+71) {
		tmp = t_1;
	} 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 * (t * ((b * y4) - (i * y5)))
	tmp = 0
	if x <= -8e+172:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	elif x <= -2.6e+60:
		tmp = c * (y2 * (x * y0))
	elif x <= -1.05e-10:
		tmp = b * (k * (z * y0))
	elif x <= -1.9e-139:
		tmp = t_1
	elif x <= 6e-219:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif x <= 48.0:
		tmp = t_1
	elif x <= 3e+65:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif x <= 1.62e+71:
		tmp = t_1
	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(t * Float64(Float64(b * y4) - Float64(i * y5))))
	tmp = 0.0
	if (x <= -8e+172)
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	elseif (x <= -2.6e+60)
		tmp = Float64(c * Float64(y2 * Float64(x * y0)));
	elseif (x <= -1.05e-10)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (x <= -1.9e-139)
		tmp = t_1;
	elseif (x <= 6e-219)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (x <= 48.0)
		tmp = t_1;
	elseif (x <= 3e+65)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (x <= 1.62e+71)
		tmp = t_1;
	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 * (t * ((b * y4) - (i * y5)));
	tmp = 0.0;
	if (x <= -8e+172)
		tmp = a * (x * ((y * b) - (y1 * y2)));
	elseif (x <= -2.6e+60)
		tmp = c * (y2 * (x * y0));
	elseif (x <= -1.05e-10)
		tmp = b * (k * (z * y0));
	elseif (x <= -1.9e-139)
		tmp = t_1;
	elseif (x <= 6e-219)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (x <= 48.0)
		tmp = t_1;
	elseif (x <= 3e+65)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (x <= 1.62e+71)
		tmp = t_1;
	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[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -8e+172], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -2.6e+60], N[(c * N[(y2 * N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.05e-10], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.9e-139], t$95$1, If[LessEqual[x, 6e-219], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 48.0], t$95$1, If[LessEqual[x, 3e+65], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.62e+71], t$95$1, N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if x < -8.0000000000000007e172

   1. Initial program 15.6%

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

   2. Taylor expanded in x around inf 44.0%

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

   3. Taylor expanded in a around inf 55.2%

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

      1. *-commutative 55.2%

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

      2. +-commutative 55.2%

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

      3. mul-1-neg 55.2%

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

      4. sub-neg 55.2%

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

      5. *-commutative 55.2%

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

   5. Simplified 55.2%

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

   if -8.0000000000000007e172 < x < -2.60000000000000008e60

   1. Initial program 9.7%

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

   2. Taylor expanded in y2 around inf 26.0%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 26.0%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 26.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 39.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 50.1%

         \[\leadsto c \cdot \color{blue}{\left(\left(x \cdot y0\right) \cdot y2\right)} \]

   8. Simplified 50.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(x \cdot y0\right) \cdot y2\right)} \]

   if -2.60000000000000008e60 < x < -1.05e-10

   1. Initial program 23.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 59.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 59.0%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 59.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 59.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 59.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 59.0%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 59.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 59.0%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 59.0%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 59.2%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 59.2%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 59.2%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 59.2%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 59.2%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 59.2%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 59.2%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 48.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if -1.05e-10 < x < -1.90000000000000004e-139 or 6.0000000000000002e-219 < x < 48 or 3.0000000000000002e65 < x < 1.62e71

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 54.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 54.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 54.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 54.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 54.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 54.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 47.3%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 47.3%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 47.3%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 47.3%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if -1.90000000000000004e-139 < x < 6.0000000000000002e-219

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 46.1%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 46.1%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 46.1%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 46.1%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 46.1%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 46.1%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 46.1%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 46.1%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 46.1%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 38.9%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 48 < x < 3.0000000000000002e65

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 27.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 27.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 27.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 27.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 27.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 27.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around inf 47.7%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 47.7%

         \[\leadsto j \cdot \color{blue}{\left(\left(y0 \cdot y5 - y1 \cdot y4\right) \cdot y3\right)} \]

      2. *-commutative 47.7%

         \[\leadsto j \cdot \left(\left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right) \cdot y3\right) \]

   7. Simplified 47.7%

      \[\leadsto j \cdot \color{blue}{\left(\left(y5 \cdot y0 - y1 \cdot y4\right) \cdot y3\right)} \]

   if 1.62e71 < x

   1. Initial program 19.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 38.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 38.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 38.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 38.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 38.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 38.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 49.6%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 47.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -8 \cdot 10^{+172}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -2.6 \cdot 10^{+60}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.05 \cdot 10^{-10}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.9 \cdot 10^{-139}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 6 \cdot 10^{-219}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 48:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;x \leq 3 \cdot 10^{+65}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;x \leq 1.62 \cdot 10^{+71}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]

Alternative 13: 28.8% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{if}\;i \leq -7.2 \cdot 10^{+190}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -6 \cdot 10^{-41}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -3.4 \cdot 10^{-108}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq -5.3 \cdot 10^{-194}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 1.6 \cdot 10^{-141}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 6.5 \cdot 10^{-7}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 3.2 \cdot 10^{+20}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 1.22 \cdot 10^{+190}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y3 (- (* y0 y5) (* y1 y4))))))
   (if (<= i -7.2e+190)
     (* j (* x (- (* i y1) (* b y0))))
     (if (<= i -6e-41)
       (* i (* k (- (* y y5) (* z y1))))
       (if (<= i -3.4e-108)
         t_1
         (if (<= i -5.3e-194)
           (* k (* y4 (* y1 y2)))
           (if (<= i 1.6e-141)
             (* k (* y2 (- (* y1 y4) (* y0 y5))))
             (if (<= i 6.5e-7)
               (* a (* x (- (* y b) (* y1 y2))))
               (if (<= i 3.2e+20)
                 t_1
                 (if (<= i 1.22e+190)
                   (* j (* t (- (* b y4) (* i 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 t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	double tmp;
	if (i <= -7.2e+190) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (i <= -6e-41) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -3.4e-108) {
		tmp = t_1;
	} else if (i <= -5.3e-194) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 1.6e-141) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 6.5e-7) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (i <= 3.2e+20) {
		tmp = t_1;
	} else if (i <= 1.22e+190) {
		tmp = j * (t * ((b * y4) - (i * 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) :: t_1
    real(8) :: tmp
    t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)))
    if (i <= (-7.2d+190)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (i <= (-6d-41)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (i <= (-3.4d-108)) then
        tmp = t_1
    else if (i <= (-5.3d-194)) then
        tmp = k * (y4 * (y1 * y2))
    else if (i <= 1.6d-141) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (i <= 6.5d-7) then
        tmp = a * (x * ((y * b) - (y1 * y2)))
    else if (i <= 3.2d+20) then
        tmp = t_1
    else if (i <= 1.22d+190) then
        tmp = j * (t * ((b * y4) - (i * 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 t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	double tmp;
	if (i <= -7.2e+190) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (i <= -6e-41) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -3.4e-108) {
		tmp = t_1;
	} else if (i <= -5.3e-194) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 1.6e-141) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (i <= 6.5e-7) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (i <= 3.2e+20) {
		tmp = t_1;
	} else if (i <= 1.22e+190) {
		tmp = j * (t * ((b * y4) - (i * 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):
	t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)))
	tmp = 0
	if i <= -7.2e+190:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif i <= -6e-41:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif i <= -3.4e-108:
		tmp = t_1
	elif i <= -5.3e-194:
		tmp = k * (y4 * (y1 * y2))
	elif i <= 1.6e-141:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif i <= 6.5e-7:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	elif i <= 3.2e+20:
		tmp = t_1
	elif i <= 1.22e+190:
		tmp = j * (t * ((b * y4) - (i * 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)
	t_1 = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))))
	tmp = 0.0
	if (i <= -7.2e+190)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (i <= -6e-41)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (i <= -3.4e-108)
		tmp = t_1;
	elseif (i <= -5.3e-194)
		tmp = Float64(k * Float64(y4 * Float64(y1 * y2)));
	elseif (i <= 1.6e-141)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (i <= 6.5e-7)
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	elseif (i <= 3.2e+20)
		tmp = t_1;
	elseif (i <= 1.22e+190)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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)
	t_1 = j * (y3 * ((y0 * y5) - (y1 * y4)));
	tmp = 0.0;
	if (i <= -7.2e+190)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (i <= -6e-41)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (i <= -3.4e-108)
		tmp = t_1;
	elseif (i <= -5.3e-194)
		tmp = k * (y4 * (y1 * y2));
	elseif (i <= 1.6e-141)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (i <= 6.5e-7)
		tmp = a * (x * ((y * b) - (y1 * y2)));
	elseif (i <= 3.2e+20)
		tmp = t_1;
	elseif (i <= 1.22e+190)
		tmp = j * (t * ((b * y4) - (i * 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_] := Block[{t$95$1 = N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -7.2e+190], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -6e-41], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -3.4e-108], t$95$1, If[LessEqual[i, -5.3e-194], N[(k * N[(y4 * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.6e-141], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 6.5e-7], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.2e+20], t$95$1, If[LessEqual[i, 1.22e+190], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if i < -7.19999999999999957e190

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if -7.19999999999999957e190 < i < -5.99999999999999978e-41

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 57.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 57.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 57.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 57.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 57.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 57.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 57.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 46.7%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -5.99999999999999978e-41 < i < -3.40000000000000002e-108 or 6.50000000000000024e-7 < i < 3.2e20

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 42.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 42.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 42.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 42.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 42.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 42.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around inf 53.6%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 53.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(y0 \cdot y5 - y1 \cdot y4\right) \cdot y3\right)} \]

      2. *-commutative 53.6%

         \[\leadsto j \cdot \left(\left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right) \cdot y3\right) \]

   7. Simplified 53.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(y5 \cdot y0 - y1 \cdot y4\right) \cdot y3\right)} \]

   if -3.40000000000000002e-108 < i < -5.3000000000000002e-194

   1. Initial program 18.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 37.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 37.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 37.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 37.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 37.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 37.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 37.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 37.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 37.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 50.5%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in y1 around inf 40.7%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 48.8%

         \[\leadsto k \cdot \color{blue}{\left(\left(y1 \cdot y2\right) \cdot y4\right)} \]

      2. *-commutative 48.8%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot y1\right)} \cdot y4\right) \]

      3. *-commutative 48.8%

         \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   8. Simplified 48.8%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   if -5.3000000000000002e-194 < i < 1.6000000000000001e-141

   1. Initial program 30.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 46.7%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 46.7%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 46.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 46.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 46.7%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 46.7%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 46.7%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 46.7%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 46.7%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y2 around -inf 33.2%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 33.2%

         \[\leadsto k \cdot \left(y2 \cdot \left(y1 \cdot y4 - \color{blue}{y5 \cdot y0}\right)\right) \]

   7. Simplified 33.2%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y5 \cdot y0\right)\right)} \]

   if 1.6000000000000001e-141 < i < 6.50000000000000024e-7

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 52.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 53.1%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 53.1%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 53.1%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 53.1%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 53.1%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 53.1%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 53.1%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   if 3.2e20 < i < 1.21999999999999995e190

   1. Initial program 20.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 52.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 52.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 52.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 52.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 52.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 52.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 55.7%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 55.7%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 55.7%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 55.7%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if 1.21999999999999995e190 < i

   1. Initial program 12.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 41.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 41.7%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.6%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 59.5%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 59.5%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 59.5%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 47.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -7.2 \cdot 10^{+190}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -6 \cdot 10^{-41}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -3.4 \cdot 10^{-108}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq -5.3 \cdot 10^{-194}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 1.6 \cdot 10^{-141}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 6.5 \cdot 10^{-7}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 3.2 \cdot 10^{+20}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.22 \cdot 10^{+190}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 14: 29.4% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ t_2 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{if}\;i \leq -2.65 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -5.6 \cdot 10^{-45}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.5 \cdot 10^{-111}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 10^{-305}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;i \leq 4.5 \cdot 10^{-158}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 1.22 \cdot 10^{-31}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;i \leq 3.65 \cdot 10^{+18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 1.6 \cdot 10^{+189}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y2 (- (* y1 y4) (* y0 y5)))))
        (t_2 (* x (* y2 (- (* c y0) (* a y1))))))
   (if (<= i -2.65e+188)
     (* j (* x (- (* i y1) (* b y0))))
     (if (<= i -5.6e-45)
       (* i (* k (- (* y y5) (* z y1))))
       (if (<= i -2.5e-111)
         (* j (* y3 (- (* y0 y5) (* y1 y4))))
         (if (<= i 1e-305)
           t_2
           (if (<= i 4.5e-158)
             t_1
             (if (<= i 1.22e-31)
               t_2
               (if (<= i 3.65e+18)
                 t_1
                 (if (<= i 1.6e+189)
                   (* j (* t (- (* b y4) (* i 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 t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double t_2 = x * (y2 * ((c * y0) - (a * y1)));
	double tmp;
	if (i <= -2.65e+188) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (i <= -5.6e-45) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -2.5e-111) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1e-305) {
		tmp = t_2;
	} else if (i <= 4.5e-158) {
		tmp = t_1;
	} else if (i <= 1.22e-31) {
		tmp = t_2;
	} else if (i <= 3.65e+18) {
		tmp = t_1;
	} else if (i <= 1.6e+189) {
		tmp = j * (t * ((b * y4) - (i * 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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
    t_2 = x * (y2 * ((c * y0) - (a * y1)))
    if (i <= (-2.65d+188)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (i <= (-5.6d-45)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (i <= (-2.5d-111)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 1d-305) then
        tmp = t_2
    else if (i <= 4.5d-158) then
        tmp = t_1
    else if (i <= 1.22d-31) then
        tmp = t_2
    else if (i <= 3.65d+18) then
        tmp = t_1
    else if (i <= 1.6d+189) then
        tmp = j * (t * ((b * y4) - (i * 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 t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	double t_2 = x * (y2 * ((c * y0) - (a * y1)));
	double tmp;
	if (i <= -2.65e+188) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (i <= -5.6e-45) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -2.5e-111) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1e-305) {
		tmp = t_2;
	} else if (i <= 4.5e-158) {
		tmp = t_1;
	} else if (i <= 1.22e-31) {
		tmp = t_2;
	} else if (i <= 3.65e+18) {
		tmp = t_1;
	} else if (i <= 1.6e+189) {
		tmp = j * (t * ((b * y4) - (i * 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):
	t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)))
	t_2 = x * (y2 * ((c * y0) - (a * y1)))
	tmp = 0
	if i <= -2.65e+188:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif i <= -5.6e-45:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif i <= -2.5e-111:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 1e-305:
		tmp = t_2
	elif i <= 4.5e-158:
		tmp = t_1
	elif i <= 1.22e-31:
		tmp = t_2
	elif i <= 3.65e+18:
		tmp = t_1
	elif i <= 1.6e+189:
		tmp = j * (t * ((b * y4) - (i * 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)
	t_1 = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	t_2 = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	tmp = 0.0
	if (i <= -2.65e+188)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (i <= -5.6e-45)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (i <= -2.5e-111)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 1e-305)
		tmp = t_2;
	elseif (i <= 4.5e-158)
		tmp = t_1;
	elseif (i <= 1.22e-31)
		tmp = t_2;
	elseif (i <= 3.65e+18)
		tmp = t_1;
	elseif (i <= 1.6e+189)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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)
	t_1 = k * (y2 * ((y1 * y4) - (y0 * y5)));
	t_2 = x * (y2 * ((c * y0) - (a * y1)));
	tmp = 0.0;
	if (i <= -2.65e+188)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (i <= -5.6e-45)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (i <= -2.5e-111)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 1e-305)
		tmp = t_2;
	elseif (i <= 4.5e-158)
		tmp = t_1;
	elseif (i <= 1.22e-31)
		tmp = t_2;
	elseif (i <= 3.65e+18)
		tmp = t_1;
	elseif (i <= 1.6e+189)
		tmp = j * (t * ((b * y4) - (i * 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_] := Block[{t$95$1 = N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -2.65e+188], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -5.6e-45], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -2.5e-111], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1e-305], t$95$2, If[LessEqual[i, 4.5e-158], t$95$1, If[LessEqual[i, 1.22e-31], t$95$2, If[LessEqual[i, 3.65e+18], t$95$1, If[LessEqual[i, 1.6e+189], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if i < -2.64999999999999994e188

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if -2.64999999999999994e188 < i < -5.6000000000000003e-45

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 57.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 57.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 57.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 57.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 57.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 57.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 57.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 46.7%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -5.6000000000000003e-45 < i < -2.5000000000000001e-111

   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. Taylor expanded in j around inf 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around inf 54.8%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 54.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(y0 \cdot y5 - y1 \cdot y4\right) \cdot y3\right)} \]

      2. *-commutative 54.8%

         \[\leadsto j \cdot \left(\left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right) \cdot y3\right) \]

   7. Simplified 54.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(y5 \cdot y0 - y1 \cdot y4\right) \cdot y3\right)} \]

   if -2.5000000000000001e-111 < i < 9.99999999999999996e-306 or 4.5e-158 < i < 1.21999999999999992e-31

   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. Taylor expanded in y2 around inf 27.0%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 27.0%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 27.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in x around inf 43.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 9.99999999999999996e-306 < i < 4.5e-158 or 1.21999999999999992e-31 < i < 3.65e18

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 51.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 51.0%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 51.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 51.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 51.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 51.0%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 51.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 51.0%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 51.0%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y2 around -inf 44.2%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 44.2%

         \[\leadsto k \cdot \left(y2 \cdot \left(y1 \cdot y4 - \color{blue}{y5 \cdot y0}\right)\right) \]

   7. Simplified 44.2%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y5 \cdot y0\right)\right)} \]

   if 3.65e18 < i < 1.6e189

   1. Initial program 20.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 52.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 52.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 52.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 52.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 52.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 52.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 55.7%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 55.7%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 55.7%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 55.7%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if 1.6e189 < i

   1. Initial program 12.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 41.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 41.7%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.6%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 59.5%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 59.5%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 59.5%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -2.65 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -5.6 \cdot 10^{-45}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.5 \cdot 10^{-111}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 10^{-305}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 4.5 \cdot 10^{-158}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 1.22 \cdot 10^{-31}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 3.65 \cdot 10^{+18}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;i \leq 1.6 \cdot 10^{+189}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 15: 28.2% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y1 \leq -1.18 \cdot 10^{+249}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y1 \leq -2.6 \cdot 10^{-32}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq -5.8 \cdot 10^{-61}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;y1 \leq -4.2 \cdot 10^{-137}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y1 \leq -4.7 \cdot 10^{-228}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq 9.2 \cdot 10^{-248}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;y1 \leq 1.95 \cdot 10^{-11}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y1 \leq 9.2 \cdot 10^{+268}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y1 -1.18e+249)
   (* k (* y2 (- (* y1 y4) (* y0 y5))))
   (if (<= y1 -2.6e-32)
     (* j (* x (- (* i y1) (* b y0))))
     (if (<= y1 -5.8e-61)
       (* i (* y5 (* y k)))
       (if (<= y1 -4.2e-137)
         (* x (* y2 (- (* c y0) (* a y1))))
         (if (<= y1 -4.7e-228)
           (* j (* y3 (- (* y0 y5) (* y1 y4))))
           (if (<= y1 9.2e-248)
             (* (* k y0) (- (* z b) (* y2 y5)))
             (if (<= y1 1.95e-11)
               (* x (* y (- (* a b) (* c i))))
               (if (<= y1 9.2e+268)
                 (* y1 (* y4 (- (* k y2) (* j y3))))
                 (* (* b j) (- (* t y4) (* x y0))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y1 <= -1.18e+249) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (y1 <= -2.6e-32) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y1 <= -5.8e-61) {
		tmp = i * (y5 * (y * k));
	} else if (y1 <= -4.2e-137) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y1 <= -4.7e-228) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (y1 <= 9.2e-248) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (y1 <= 1.95e-11) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y1 <= 9.2e+268) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else {
		tmp = (b * j) * ((t * y4) - (x * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y1 <= (-1.18d+249)) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (y1 <= (-2.6d-32)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y1 <= (-5.8d-61)) then
        tmp = i * (y5 * (y * k))
    else if (y1 <= (-4.2d-137)) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y1 <= (-4.7d-228)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (y1 <= 9.2d-248) then
        tmp = (k * y0) * ((z * b) - (y2 * y5))
    else if (y1 <= 1.95d-11) then
        tmp = x * (y * ((a * b) - (c * i)))
    else if (y1 <= 9.2d+268) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else
        tmp = (b * j) * ((t * y4) - (x * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y1 <= -1.18e+249) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (y1 <= -2.6e-32) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y1 <= -5.8e-61) {
		tmp = i * (y5 * (y * k));
	} else if (y1 <= -4.2e-137) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y1 <= -4.7e-228) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (y1 <= 9.2e-248) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (y1 <= 1.95e-11) {
		tmp = x * (y * ((a * b) - (c * i)));
	} else if (y1 <= 9.2e+268) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else {
		tmp = (b * j) * ((t * y4) - (x * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y1 <= -1.18e+249:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif y1 <= -2.6e-32:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y1 <= -5.8e-61:
		tmp = i * (y5 * (y * k))
	elif y1 <= -4.2e-137:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y1 <= -4.7e-228:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif y1 <= 9.2e-248:
		tmp = (k * y0) * ((z * b) - (y2 * y5))
	elif y1 <= 1.95e-11:
		tmp = x * (y * ((a * b) - (c * i)))
	elif y1 <= 9.2e+268:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	else:
		tmp = (b * j) * ((t * y4) - (x * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y1 <= -1.18e+249)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (y1 <= -2.6e-32)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y1 <= -5.8e-61)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (y1 <= -4.2e-137)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y1 <= -4.7e-228)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (y1 <= 9.2e-248)
		tmp = Float64(Float64(k * y0) * Float64(Float64(z * b) - Float64(y2 * y5)));
	elseif (y1 <= 1.95e-11)
		tmp = Float64(x * Float64(y * Float64(Float64(a * b) - Float64(c * i))));
	elseif (y1 <= 9.2e+268)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	else
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y1 <= -1.18e+249)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (y1 <= -2.6e-32)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y1 <= -5.8e-61)
		tmp = i * (y5 * (y * k));
	elseif (y1 <= -4.2e-137)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y1 <= -4.7e-228)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (y1 <= 9.2e-248)
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	elseif (y1 <= 1.95e-11)
		tmp = x * (y * ((a * b) - (c * i)));
	elseif (y1 <= 9.2e+268)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	else
		tmp = (b * j) * ((t * y4) - (x * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y1, -1.18e+249], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -2.6e-32], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -5.8e-61], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -4.2e-137], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, -4.7e-228], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 9.2e-248], N[(N[(k * y0), $MachinePrecision] * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 1.95e-11], N[(x * N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y1, 9.2e+268], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y1 < -1.17999999999999995e249

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 52.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 52.6%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 52.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 52.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 52.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 52.6%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 52.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 52.6%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 52.6%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y2 around -inf 62.0%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 62.0%

         \[\leadsto k \cdot \left(y2 \cdot \left(y1 \cdot y4 - \color{blue}{y5 \cdot y0}\right)\right) \]

   7. Simplified 62.0%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y5 \cdot y0\right)\right)} \]

   if -1.17999999999999995e249 < y1 < -2.5999999999999997e-32

   1. Initial program 14.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 35.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 35.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 35.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 35.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 35.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 35.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 39.7%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if -2.5999999999999997e-32 < y1 < -5.7999999999999999e-61

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 40.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 40.4%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 40.4%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 40.4%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 40.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 40.4%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 40.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 40.4%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 40.4%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 41.2%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 41.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 50.8%

         \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   8. Simplified 50.8%

      \[\leadsto \color{blue}{i \cdot \left(\left(k \cdot y\right) \cdot y5\right)} \]

   if -5.7999999999999999e-61 < y1 < -4.19999999999999983e-137

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 45.9%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 45.9%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 45.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in x around inf 46.7%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if -4.19999999999999983e-137 < y1 < -4.7000000000000002e-228

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 47.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 47.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 47.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 47.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 47.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 47.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around inf 54.6%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 54.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(y0 \cdot y5 - y1 \cdot y4\right) \cdot y3\right)} \]

      2. *-commutative 54.6%

         \[\leadsto j \cdot \left(\left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right) \cdot y3\right) \]

   7. Simplified 54.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(y5 \cdot y0 - y1 \cdot y4\right) \cdot y3\right)} \]

   if -4.7000000000000002e-228 < y1 < 9.2000000000000001e-248

   1. Initial program 29.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 51.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 51.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 51.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 51.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 51.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 51.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 51.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 51.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 51.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around inf 40.0%

      \[\leadsto \color{blue}{k \cdot \left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) + b \cdot z\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 39.9%

         \[\leadsto \color{blue}{\left(k \cdot y0\right) \cdot \left(-1 \cdot \left(y2 \cdot y5\right) + b \cdot z\right)} \]

      2. +-commutative 39.9%

         \[\leadsto \left(k \cdot y0\right) \cdot \color{blue}{\left(b \cdot z + -1 \cdot \left(y2 \cdot y5\right)\right)} \]

      3. mul-1-neg 39.9%

         \[\leadsto \left(k \cdot y0\right) \cdot \left(b \cdot z + \color{blue}{\left(-y2 \cdot y5\right)}\right) \]

      4. unsub-neg 39.9%

         \[\leadsto \left(k \cdot y0\right) \cdot \color{blue}{\left(b \cdot z - y2 \cdot y5\right)} \]

      5. *-commutative 39.9%

         \[\leadsto \left(k \cdot y0\right) \cdot \left(\color{blue}{z \cdot b} - y2 \cdot y5\right) \]

      6. *-commutative 39.9%

         \[\leadsto \left(k \cdot y0\right) \cdot \left(z \cdot b - \color{blue}{y5 \cdot y2}\right) \]

   7. Simplified 39.9%

      \[\leadsto \color{blue}{\left(k \cdot y0\right) \cdot \left(z \cdot b - y5 \cdot y2\right)} \]

   if 9.2000000000000001e-248 < y1 < 1.95000000000000005e-11

   1. Initial program 36.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 40.7%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in y around inf 43.3%

      \[\leadsto \color{blue}{x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)} \]

   if 1.95000000000000005e-11 < y1 < 9.20000000000000049e268

   1. Initial program 20.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y1 around -inf 55.3%

      \[\leadsto \color{blue}{-1 \cdot \left(y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 55.3%

         \[\leadsto \color{blue}{-y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. *-commutative 55.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot y1} \]

      3. distribute-rgt-neg-in 55.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot \left(-y1\right)} \]

   4. Simplified 55.3%

      \[\leadsto \color{blue}{\left(\left(a \cdot \left(y2 \cdot x - z \cdot y3\right) - y4 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - i \cdot \left(j \cdot x - z \cdot k\right)\right) \cdot \left(-y1\right)} \]

   5. Taylor expanded in y4 around -inf 46.4%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 9.20000000000000049e268 < y1

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in b around inf 73.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 81.9%

         \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)} \]

      2. *-commutative 81.9%

         \[\leadsto \left(b \cdot j\right) \cdot \left(\color{blue}{y4 \cdot t} - x \cdot y0\right) \]

      3. *-commutative 81.9%

         \[\leadsto \left(b \cdot j\right) \cdot \left(y4 \cdot t - \color{blue}{y0 \cdot x}\right) \]

   7. Simplified 81.9%

      \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(y4 \cdot t - y0 \cdot x\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 47.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y1 \leq -1.18 \cdot 10^{+249}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y1 \leq -2.6 \cdot 10^{-32}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y1 \leq -5.8 \cdot 10^{-61}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;y1 \leq -4.2 \cdot 10^{-137}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y1 \leq -4.7 \cdot 10^{-228}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;y1 \leq 9.2 \cdot 10^{-248}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;y1 \leq 1.95 \cdot 10^{-11}:\\ \;\;\;\;x \cdot \left(y \cdot \left(a \cdot b - c \cdot i\right)\right)\\ \mathbf{elif}\;y1 \leq 9.2 \cdot 10^{+268}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \end{array} \]

Alternative 16: 28.4% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -3.4 \cdot 10^{+78}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y \leq -1.25 \cdot 10^{-209}:\\ \;\;\;\;y1 \cdot \left(a \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;y \leq 2 \cdot 10^{-132}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 0.002:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y \leq 1.45 \cdot 10^{+39}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+69}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3.1 \cdot 10^{+153}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;y \leq 9.5 \cdot 10^{+230}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -3.4e+78)
   (* b (* k (* y (- y4))))
   (if (<= y -1.25e-209)
     (* y1 (* a (- (* z y3) (* x y2))))
     (if (<= y 2e-132)
       (* j (* t (- (* b y4) (* i y5))))
       (if (<= y 0.002)
         (* x (* y2 (- (* c y0) (* a y1))))
         (if (<= y 1.45e+39)
           (* k (* y2 (- (* y1 y4) (* y0 y5))))
           (if (<= y 2.3e+69)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= y 3.1e+153)
               (* (* k y4) (- (* y1 y2) (* y b)))
               (if (<= y 9.5e+230)
                 (* y1 (* x (- (* i j) (* a y2))))
                 (* i (* k (* y y5))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -3.4e+78) {
		tmp = b * (k * (y * -y4));
	} else if (y <= -1.25e-209) {
		tmp = y1 * (a * ((z * y3) - (x * y2)));
	} else if (y <= 2e-132) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 0.002) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y <= 1.45e+39) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (y <= 2.3e+69) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3.1e+153) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (y <= 9.5e+230) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else {
		tmp = i * (k * (y * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y <= (-3.4d+78)) then
        tmp = b * (k * (y * -y4))
    else if (y <= (-1.25d-209)) then
        tmp = y1 * (a * ((z * y3) - (x * y2)))
    else if (y <= 2d-132) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y <= 0.002d0) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y <= 1.45d+39) then
        tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
    else if (y <= 2.3d+69) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y <= 3.1d+153) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (y <= 9.5d+230) then
        tmp = y1 * (x * ((i * j) - (a * y2)))
    else
        tmp = i * (k * (y * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -3.4e+78) {
		tmp = b * (k * (y * -y4));
	} else if (y <= -1.25e-209) {
		tmp = y1 * (a * ((z * y3) - (x * y2)));
	} else if (y <= 2e-132) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 0.002) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y <= 1.45e+39) {
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	} else if (y <= 2.3e+69) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y <= 3.1e+153) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (y <= 9.5e+230) {
		tmp = y1 * (x * ((i * j) - (a * y2)));
	} else {
		tmp = i * (k * (y * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y <= -3.4e+78:
		tmp = b * (k * (y * -y4))
	elif y <= -1.25e-209:
		tmp = y1 * (a * ((z * y3) - (x * y2)))
	elif y <= 2e-132:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y <= 0.002:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y <= 1.45e+39:
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)))
	elif y <= 2.3e+69:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y <= 3.1e+153:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif y <= 9.5e+230:
		tmp = y1 * (x * ((i * j) - (a * y2)))
	else:
		tmp = i * (k * (y * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y <= -3.4e+78)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (y <= -1.25e-209)
		tmp = Float64(y1 * Float64(a * Float64(Float64(z * y3) - Float64(x * y2))));
	elseif (y <= 2e-132)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y <= 0.002)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y <= 1.45e+39)
		tmp = Float64(k * Float64(y2 * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (y <= 2.3e+69)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y <= 3.1e+153)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (y <= 9.5e+230)
		tmp = Float64(y1 * Float64(x * Float64(Float64(i * j) - Float64(a * y2))));
	else
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y <= -3.4e+78)
		tmp = b * (k * (y * -y4));
	elseif (y <= -1.25e-209)
		tmp = y1 * (a * ((z * y3) - (x * y2)));
	elseif (y <= 2e-132)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y <= 0.002)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y <= 1.45e+39)
		tmp = k * (y2 * ((y1 * y4) - (y0 * y5)));
	elseif (y <= 2.3e+69)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y <= 3.1e+153)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (y <= 9.5e+230)
		tmp = y1 * (x * ((i * j) - (a * y2)));
	else
		tmp = i * (k * (y * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y, -3.4e+78], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.25e-209], N[(y1 * N[(a * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2e-132], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 0.002], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.45e+39], N[(k * N[(y2 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.3e+69], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3.1e+153], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 9.5e+230], N[(y1 * N[(x * N[(N[(i * j), $MachinePrecision] - N[(a * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y < -3.40000000000000007e78

   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. Taylor expanded in k around -inf 35.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 35.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 35.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 35.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 35.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 35.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 35.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 35.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 35.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 44.3%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in b around inf 41.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 41.8%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 41.8%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} \]

      3. *-commutative 41.8%

         \[\leadsto b \cdot \left(-k \cdot \color{blue}{\left(y4 \cdot y\right)}\right) \]

   8. Simplified 41.8%

      \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y4 \cdot y\right)\right)} \]

   if -3.40000000000000007e78 < y < -1.2500000000000001e-209

   1. Initial program 22.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y1 around -inf 33.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 33.0%

         \[\leadsto \color{blue}{-y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. *-commutative 33.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot y1} \]

      3. distribute-rgt-neg-in 33.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot \left(-y1\right)} \]

   4. Simplified 33.0%

      \[\leadsto \color{blue}{\left(\left(a \cdot \left(y2 \cdot x - z \cdot y3\right) - y4 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - i \cdot \left(j \cdot x - z \cdot k\right)\right) \cdot \left(-y1\right)} \]

   5. Taylor expanded in a around inf 37.7%

      \[\leadsto \color{blue}{\left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \cdot \left(-y1\right) \]
   6. Step-by-step derivation

      1. *-commutative 37.7%

         \[\leadsto \left(a \cdot \left(\color{blue}{y2 \cdot x} - y3 \cdot z\right)\right) \cdot \left(-y1\right) \]

      2. *-commutative 37.7%

         \[\leadsto \left(a \cdot \left(y2 \cdot x - \color{blue}{z \cdot y3}\right)\right) \cdot \left(-y1\right) \]

   7. Simplified 37.7%

      \[\leadsto \color{blue}{\left(a \cdot \left(y2 \cdot x - z \cdot y3\right)\right)} \cdot \left(-y1\right) \]

   if -1.2500000000000001e-209 < y < 2e-132

   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. Taylor expanded in j around inf 53.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 53.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 53.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 53.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 53.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 53.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 48.0%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 48.0%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 48.0%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 48.0%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if 2e-132 < y < 2e-3

   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. Taylor expanded in y2 around inf 32.0%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 32.0%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 32.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in x around inf 50.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 2e-3 < y < 1.45000000000000015e39

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 48.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 48.0%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 48.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 48.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 48.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 48.0%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 48.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 48.0%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 48.0%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y2 around -inf 54.5%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 54.5%

         \[\leadsto k \cdot \left(y2 \cdot \left(y1 \cdot y4 - \color{blue}{y5 \cdot y0}\right)\right) \]

   7. Simplified 54.5%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y5 \cdot y0\right)\right)} \]

   if 1.45000000000000015e39 < y < 2.30000000000000017e69

   1. Initial program 20.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 40.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 40.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 40.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 40.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 40.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 40.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 2.30000000000000017e69 < y < 3.1e153

   1. Initial program 23.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 69.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 69.6%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 69.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 69.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 69.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 69.6%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 69.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 69.6%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 69.6%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y4 around -inf 61.7%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) - -1 \cdot \left(y1 \cdot y2\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 61.7%

         \[\leadsto \color{blue}{\left(k \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot y\right) - -1 \cdot \left(y1 \cdot y2\right)\right)} \]

      2. associate-*r* 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot y\right) - \color{blue}{\left(-1 \cdot y1\right) \cdot y2}\right) \]

      3. neg-mul-1 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot y\right) - \color{blue}{\left(-y1\right)} \cdot y2\right) \]

      4. cancel-sign-sub 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \color{blue}{\left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)} \]

      5. +-commutative 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)} \]

      6. mul-1-neg 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right) \]

      7. unsub-neg 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)} \]

      8. *-commutative 61.7%

         \[\leadsto \left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - \color{blue}{y \cdot b}\right) \]

   7. Simplified 61.7%

      \[\leadsto \color{blue}{\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)} \]

   if 3.1e153 < y < 9.5000000000000002e230

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y1 around -inf 32.0%

      \[\leadsto \color{blue}{-1 \cdot \left(y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 32.0%

         \[\leadsto \color{blue}{-y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. *-commutative 32.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot y1} \]

      3. distribute-rgt-neg-in 32.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot \left(-y1\right)} \]

   4. Simplified 32.0%

      \[\leadsto \color{blue}{\left(\left(a \cdot \left(y2 \cdot x - z \cdot y3\right) - y4 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - i \cdot \left(j \cdot x - z \cdot k\right)\right) \cdot \left(-y1\right)} \]

   5. Taylor expanded in x around inf 51.1%

      \[\leadsto \color{blue}{\left(x \cdot \left(a \cdot y2 - i \cdot j\right)\right)} \cdot \left(-y1\right) \]
   6. Step-by-step derivation

      1. *-commutative 51.1%

         \[\leadsto \left(x \cdot \left(\color{blue}{y2 \cdot a} - i \cdot j\right)\right) \cdot \left(-y1\right) \]

   7. Simplified 51.1%

      \[\leadsto \color{blue}{\left(x \cdot \left(y2 \cdot a - i \cdot j\right)\right)} \cdot \left(-y1\right) \]

   if 9.5000000000000002e230 < y

   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. Taylor expanded in k around -inf 36.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 36.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 36.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 36.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 36.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 36.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 36.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 36.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 36.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 58.0%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 74.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 48.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -3.4 \cdot 10^{+78}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y \leq -1.25 \cdot 10^{-209}:\\ \;\;\;\;y1 \cdot \left(a \cdot \left(z \cdot y3 - x \cdot y2\right)\right)\\ \mathbf{elif}\;y \leq 2 \cdot 10^{-132}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 0.002:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y \leq 1.45 \cdot 10^{+39}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+69}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 3.1 \cdot 10^{+153}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;y \leq 9.5 \cdot 10^{+230}:\\ \;\;\;\;y1 \cdot \left(x \cdot \left(i \cdot j - a \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \end{array} \]

Alternative 17: 29.7% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{if}\;i \leq -4.6 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -3 \cdot 10^{-45}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -1.02 \cdot 10^{-110}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.02 \cdot 10^{-305}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 1.4 \cdot 10^{-149}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 1.2 \cdot 10^{-30}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 2.95 \cdot 10^{+187}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y2 (- (* c y0) (* a y1))))))
   (if (<= i -4.6e+188)
     (* j (* x (- (* i y1) (* b y0))))
     (if (<= i -3e-45)
       (* i (* k (- (* y y5) (* z y1))))
       (if (<= i -1.02e-110)
         (* j (* y3 (- (* y0 y5) (* y1 y4))))
         (if (<= i 1.02e-305)
           t_1
           (if (<= i 1.4e-149)
             (* y1 (* y4 (- (* k y2) (* j y3))))
             (if (<= i 1.2e-30)
               t_1
               (if (<= i 2.95e+187)
                 (* j (* t (- (* b y4) (* i 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 t_1 = x * (y2 * ((c * y0) - (a * y1)));
	double tmp;
	if (i <= -4.6e+188) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (i <= -3e-45) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -1.02e-110) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1.02e-305) {
		tmp = t_1;
	} else if (i <= 1.4e-149) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 1.2e-30) {
		tmp = t_1;
	} else if (i <= 2.95e+187) {
		tmp = j * (t * ((b * y4) - (i * 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) :: t_1
    real(8) :: tmp
    t_1 = x * (y2 * ((c * y0) - (a * y1)))
    if (i <= (-4.6d+188)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (i <= (-3d-45)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (i <= (-1.02d-110)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 1.02d-305) then
        tmp = t_1
    else if (i <= 1.4d-149) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (i <= 1.2d-30) then
        tmp = t_1
    else if (i <= 2.95d+187) then
        tmp = j * (t * ((b * y4) - (i * 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 t_1 = x * (y2 * ((c * y0) - (a * y1)));
	double tmp;
	if (i <= -4.6e+188) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (i <= -3e-45) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -1.02e-110) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 1.02e-305) {
		tmp = t_1;
	} else if (i <= 1.4e-149) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 1.2e-30) {
		tmp = t_1;
	} else if (i <= 2.95e+187) {
		tmp = j * (t * ((b * y4) - (i * 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):
	t_1 = x * (y2 * ((c * y0) - (a * y1)))
	tmp = 0
	if i <= -4.6e+188:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif i <= -3e-45:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif i <= -1.02e-110:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 1.02e-305:
		tmp = t_1
	elif i <= 1.4e-149:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif i <= 1.2e-30:
		tmp = t_1
	elif i <= 2.95e+187:
		tmp = j * (t * ((b * y4) - (i * 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)
	t_1 = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	tmp = 0.0
	if (i <= -4.6e+188)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (i <= -3e-45)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (i <= -1.02e-110)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 1.02e-305)
		tmp = t_1;
	elseif (i <= 1.4e-149)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (i <= 1.2e-30)
		tmp = t_1;
	elseif (i <= 2.95e+187)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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)
	t_1 = x * (y2 * ((c * y0) - (a * y1)));
	tmp = 0.0;
	if (i <= -4.6e+188)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (i <= -3e-45)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (i <= -1.02e-110)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 1.02e-305)
		tmp = t_1;
	elseif (i <= 1.4e-149)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (i <= 1.2e-30)
		tmp = t_1;
	elseif (i <= 2.95e+187)
		tmp = j * (t * ((b * y4) - (i * 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_] := Block[{t$95$1 = N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -4.6e+188], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -3e-45], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.02e-110], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.02e-305], t$95$1, If[LessEqual[i, 1.4e-149], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.2e-30], t$95$1, If[LessEqual[i, 2.95e+187], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if i < -4.60000000000000023e188

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if -4.60000000000000023e188 < i < -3.00000000000000011e-45

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 57.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 57.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 57.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 57.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 57.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 57.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 57.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 46.7%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -3.00000000000000011e-45 < i < -1.02000000000000006e-110

   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. Taylor expanded in j around inf 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around inf 54.8%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 54.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(y0 \cdot y5 - y1 \cdot y4\right) \cdot y3\right)} \]

      2. *-commutative 54.8%

         \[\leadsto j \cdot \left(\left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right) \cdot y3\right) \]

   7. Simplified 54.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(y5 \cdot y0 - y1 \cdot y4\right) \cdot y3\right)} \]

   if -1.02000000000000006e-110 < i < 1.01999999999999994e-305 or 1.3999999999999999e-149 < i < 1.19999999999999992e-30

   1. Initial program 25.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 25.9%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 25.9%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 25.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in x around inf 43.9%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 1.01999999999999994e-305 < i < 1.3999999999999999e-149

   1. Initial program 30.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y1 around -inf 36.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 36.6%

         \[\leadsto \color{blue}{-y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. *-commutative 36.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot y1} \]

      3. distribute-rgt-neg-in 36.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot \left(-y1\right)} \]

   4. Simplified 36.6%

      \[\leadsto \color{blue}{\left(\left(a \cdot \left(y2 \cdot x - z \cdot y3\right) - y4 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - i \cdot \left(j \cdot x - z \cdot k\right)\right) \cdot \left(-y1\right)} \]

   5. Taylor expanded in y4 around -inf 42.8%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 1.19999999999999992e-30 < i < 2.95e187

   1. Initial program 27.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 47.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 47.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 47.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 47.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 47.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 47.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 49.3%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 49.3%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 49.3%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 49.3%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if 2.95e187 < i

   1. Initial program 12.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 41.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 41.7%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.6%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 59.5%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 59.5%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 59.5%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -4.6 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq -3 \cdot 10^{-45}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -1.02 \cdot 10^{-110}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 1.02 \cdot 10^{-305}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 1.4 \cdot 10^{-149}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 1.2 \cdot 10^{-30}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 2.95 \cdot 10^{+187}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 18: 28.4% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{if}\;i \leq -6 \cdot 10^{+191}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;i \leq -1.45 \cdot 10^{-44}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.9 \cdot 10^{-111}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 7.5 \cdot 10^{-306}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 6.2 \cdot 10^{-150}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 3.4 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;i \leq 1.55 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* x (* y2 (- (* c y0) (* a y1))))))
   (if (<= i -6e+191)
     (* (* b j) (- (* t y4) (* x y0)))
     (if (<= i -1.45e-44)
       (* i (* k (- (* y y5) (* z y1))))
       (if (<= i -2.9e-111)
         (* j (* y3 (- (* y0 y5) (* y1 y4))))
         (if (<= i 7.5e-306)
           t_1
           (if (<= i 6.2e-150)
             (* y1 (* y4 (- (* k y2) (* j y3))))
             (if (<= i 3.4e-32)
               t_1
               (if (<= i 1.55e+188)
                 (* j (* t (- (* b y4) (* i 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 t_1 = x * (y2 * ((c * y0) - (a * y1)));
	double tmp;
	if (i <= -6e+191) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (i <= -1.45e-44) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -2.9e-111) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 7.5e-306) {
		tmp = t_1;
	} else if (i <= 6.2e-150) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 3.4e-32) {
		tmp = t_1;
	} else if (i <= 1.55e+188) {
		tmp = j * (t * ((b * y4) - (i * 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) :: t_1
    real(8) :: tmp
    t_1 = x * (y2 * ((c * y0) - (a * y1)))
    if (i <= (-6d+191)) then
        tmp = (b * j) * ((t * y4) - (x * y0))
    else if (i <= (-1.45d-44)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (i <= (-2.9d-111)) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (i <= 7.5d-306) then
        tmp = t_1
    else if (i <= 6.2d-150) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (i <= 3.4d-32) then
        tmp = t_1
    else if (i <= 1.55d+188) then
        tmp = j * (t * ((b * y4) - (i * 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 t_1 = x * (y2 * ((c * y0) - (a * y1)));
	double tmp;
	if (i <= -6e+191) {
		tmp = (b * j) * ((t * y4) - (x * y0));
	} else if (i <= -1.45e-44) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (i <= -2.9e-111) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (i <= 7.5e-306) {
		tmp = t_1;
	} else if (i <= 6.2e-150) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (i <= 3.4e-32) {
		tmp = t_1;
	} else if (i <= 1.55e+188) {
		tmp = j * (t * ((b * y4) - (i * 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):
	t_1 = x * (y2 * ((c * y0) - (a * y1)))
	tmp = 0
	if i <= -6e+191:
		tmp = (b * j) * ((t * y4) - (x * y0))
	elif i <= -1.45e-44:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif i <= -2.9e-111:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif i <= 7.5e-306:
		tmp = t_1
	elif i <= 6.2e-150:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif i <= 3.4e-32:
		tmp = t_1
	elif i <= 1.55e+188:
		tmp = j * (t * ((b * y4) - (i * 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)
	t_1 = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))))
	tmp = 0.0
	if (i <= -6e+191)
		tmp = Float64(Float64(b * j) * Float64(Float64(t * y4) - Float64(x * y0)));
	elseif (i <= -1.45e-44)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (i <= -2.9e-111)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (i <= 7.5e-306)
		tmp = t_1;
	elseif (i <= 6.2e-150)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (i <= 3.4e-32)
		tmp = t_1;
	elseif (i <= 1.55e+188)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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)
	t_1 = x * (y2 * ((c * y0) - (a * y1)));
	tmp = 0.0;
	if (i <= -6e+191)
		tmp = (b * j) * ((t * y4) - (x * y0));
	elseif (i <= -1.45e-44)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (i <= -2.9e-111)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (i <= 7.5e-306)
		tmp = t_1;
	elseif (i <= 6.2e-150)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (i <= 3.4e-32)
		tmp = t_1;
	elseif (i <= 1.55e+188)
		tmp = j * (t * ((b * y4) - (i * 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_] := Block[{t$95$1 = N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -6e+191], N[(N[(b * j), $MachinePrecision] * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.45e-44], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -2.9e-111], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 7.5e-306], t$95$1, If[LessEqual[i, 6.2e-150], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.4e-32], t$95$1, If[LessEqual[i, 1.55e+188], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if i < -5.9999999999999995e191

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in b around inf 46.5%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 50.8%

         \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)} \]

      2. *-commutative 50.8%

         \[\leadsto \left(b \cdot j\right) \cdot \left(\color{blue}{y4 \cdot t} - x \cdot y0\right) \]

      3. *-commutative 50.8%

         \[\leadsto \left(b \cdot j\right) \cdot \left(y4 \cdot t - \color{blue}{y0 \cdot x}\right) \]

   7. Simplified 50.8%

      \[\leadsto \color{blue}{\left(b \cdot j\right) \cdot \left(y4 \cdot t - y0 \cdot x\right)} \]

   if -5.9999999999999995e191 < i < -1.4500000000000001e-44

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 57.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 57.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 57.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 57.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 57.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 57.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 57.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 46.7%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if -1.4500000000000001e-44 < i < -2.90000000000000002e-111

   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. Taylor expanded in j around inf 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y3 around inf 54.8%

      \[\leadsto j \cdot \color{blue}{\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 54.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(y0 \cdot y5 - y1 \cdot y4\right) \cdot y3\right)} \]

      2. *-commutative 54.8%

         \[\leadsto j \cdot \left(\left(\color{blue}{y5 \cdot y0} - y1 \cdot y4\right) \cdot y3\right) \]

   7. Simplified 54.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(y5 \cdot y0 - y1 \cdot y4\right) \cdot y3\right)} \]

   if -2.90000000000000002e-111 < i < 7.5000000000000003e-306 or 6.19999999999999996e-150 < i < 3.39999999999999978e-32

   1. Initial program 25.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 25.9%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 25.9%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 25.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in x around inf 43.9%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 7.5000000000000003e-306 < i < 6.19999999999999996e-150

   1. Initial program 30.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y1 around -inf 36.6%

      \[\leadsto \color{blue}{-1 \cdot \left(y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 36.6%

         \[\leadsto \color{blue}{-y1 \cdot \left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

      2. *-commutative 36.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot y1} \]

      3. distribute-rgt-neg-in 36.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - i \cdot \left(j \cdot x - k \cdot z\right)\right) \cdot \left(-y1\right)} \]

   4. Simplified 36.6%

      \[\leadsto \color{blue}{\left(\left(a \cdot \left(y2 \cdot x - z \cdot y3\right) - y4 \cdot \left(k \cdot y2 - y3 \cdot j\right)\right) - i \cdot \left(j \cdot x - z \cdot k\right)\right) \cdot \left(-y1\right)} \]

   5. Taylor expanded in y4 around -inf 42.8%

      \[\leadsto \color{blue}{y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]

   if 3.39999999999999978e-32 < i < 1.5500000000000001e188

   1. Initial program 27.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 47.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 47.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 47.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 47.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 47.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 47.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 49.3%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 49.3%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 49.3%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 49.3%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if 1.5500000000000001e188 < i

   1. Initial program 12.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 25.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 25.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 25.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 41.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 41.7%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.6%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 59.5%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 59.5%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 59.5%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 48.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -6 \cdot 10^{+191}:\\ \;\;\;\;\left(b \cdot j\right) \cdot \left(t \cdot y4 - x \cdot y0\right)\\ \mathbf{elif}\;i \leq -1.45 \cdot 10^{-44}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.9 \cdot 10^{-111}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 7.5 \cdot 10^{-306}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 6.2 \cdot 10^{-150}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;i \leq 3.4 \cdot 10^{-32}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 1.55 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 19: 28.1% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{if}\;x \leq -1.65 \cdot 10^{+174}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq -2.9 \cdot 10^{+60}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.9 \cdot 10^{-137}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;x \leq 7 \cdot 10^{-207}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 5.1 \cdot 10^{-110}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;x \leq 2.1 \cdot 10^{+65}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* x (- (* y b) (* y1 y2))))))
   (if (<= x -1.65e+174)
     t_1
     (if (<= x -2.9e+60)
       (* c (* y2 (* x y0)))
       (if (<= x -1.9e-137)
         (* c (* y4 (* t (- y2))))
         (if (<= x 7e-207)
           (* i (* k (- (* y y5) (* z y1))))
           (if (<= x 5.1e-110)
             (* b (* k (* y (- y4))))
             (if (<= x 2.1e+65) (* i (* k (* y y5))) t_1))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (x * ((y * b) - (y1 * y2)));
	double tmp;
	if (x <= -1.65e+174) {
		tmp = t_1;
	} else if (x <= -2.9e+60) {
		tmp = c * (y2 * (x * y0));
	} else if (x <= -1.9e-137) {
		tmp = c * (y4 * (t * -y2));
	} else if (x <= 7e-207) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (x <= 5.1e-110) {
		tmp = b * (k * (y * -y4));
	} else if (x <= 2.1e+65) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (x * ((y * b) - (y1 * y2)))
    if (x <= (-1.65d+174)) then
        tmp = t_1
    else if (x <= (-2.9d+60)) then
        tmp = c * (y2 * (x * y0))
    else if (x <= (-1.9d-137)) then
        tmp = c * (y4 * (t * -y2))
    else if (x <= 7d-207) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (x <= 5.1d-110) then
        tmp = b * (k * (y * -y4))
    else if (x <= 2.1d+65) then
        tmp = i * (k * (y * y5))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (x * ((y * b) - (y1 * y2)));
	double tmp;
	if (x <= -1.65e+174) {
		tmp = t_1;
	} else if (x <= -2.9e+60) {
		tmp = c * (y2 * (x * y0));
	} else if (x <= -1.9e-137) {
		tmp = c * (y4 * (t * -y2));
	} else if (x <= 7e-207) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (x <= 5.1e-110) {
		tmp = b * (k * (y * -y4));
	} else if (x <= 2.1e+65) {
		tmp = i * (k * (y * y5));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (x * ((y * b) - (y1 * y2)))
	tmp = 0
	if x <= -1.65e+174:
		tmp = t_1
	elif x <= -2.9e+60:
		tmp = c * (y2 * (x * y0))
	elif x <= -1.9e-137:
		tmp = c * (y4 * (t * -y2))
	elif x <= 7e-207:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif x <= 5.1e-110:
		tmp = b * (k * (y * -y4))
	elif x <= 2.1e+65:
		tmp = i * (k * (y * y5))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))))
	tmp = 0.0
	if (x <= -1.65e+174)
		tmp = t_1;
	elseif (x <= -2.9e+60)
		tmp = Float64(c * Float64(y2 * Float64(x * y0)));
	elseif (x <= -1.9e-137)
		tmp = Float64(c * Float64(y4 * Float64(t * Float64(-y2))));
	elseif (x <= 7e-207)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (x <= 5.1e-110)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (x <= 2.1e+65)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (x * ((y * b) - (y1 * y2)));
	tmp = 0.0;
	if (x <= -1.65e+174)
		tmp = t_1;
	elseif (x <= -2.9e+60)
		tmp = c * (y2 * (x * y0));
	elseif (x <= -1.9e-137)
		tmp = c * (y4 * (t * -y2));
	elseif (x <= 7e-207)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (x <= 5.1e-110)
		tmp = b * (k * (y * -y4));
	elseif (x <= 2.1e+65)
		tmp = i * (k * (y * y5));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.65e+174], t$95$1, If[LessEqual[x, -2.9e+60], N[(c * N[(y2 * N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1.9e-137], N[(c * N[(y4 * N[(t * (-y2)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 7e-207], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 5.1e-110], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 2.1e+65], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 6 regimes

2. if x < -1.65e174 or 2.09999999999999991e65 < x

   1. Initial program 17.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 45.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 50.2%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 50.2%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 50.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 50.2%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 50.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 50.2%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 50.2%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   if -1.65e174 < x < -2.9e60

   1. Initial program 9.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 26.0%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 26.0%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 26.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 39.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 50.1%

         \[\leadsto c \cdot \color{blue}{\left(\left(x \cdot y0\right) \cdot y2\right)} \]

   8. Simplified 50.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(x \cdot y0\right) \cdot y2\right)} \]

   if -2.9e60 < x < -1.89999999999999999e-137

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 40.2%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 40.2%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 40.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 28.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 31.5%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 31.5%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

      3. associate-*r* 34.4%

         \[\leadsto c \cdot \left(-\color{blue}{\left(t \cdot y2\right) \cdot y4}\right) \]

      4. *-commutative 34.4%

         \[\leadsto c \cdot \left(-\color{blue}{y4 \cdot \left(t \cdot y2\right)}\right) \]

      5. *-commutative 34.4%

         \[\leadsto c \cdot \left(-y4 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   8. Simplified 34.4%

      \[\leadsto \color{blue}{c \cdot \left(-y4 \cdot \left(y2 \cdot t\right)\right)} \]

   if -1.89999999999999999e-137 < x < 7.0000000000000003e-207

   1. Initial program 34.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 47.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 47.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 47.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 47.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 47.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 47.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 47.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 47.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 47.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 37.5%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 7.0000000000000003e-207 < x < 5.1000000000000002e-110

   1. Initial program 22.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 40.5%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 40.5%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 40.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 40.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 40.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 40.5%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 40.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 40.5%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 40.5%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 40.7%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in b around inf 35.2%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 35.2%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 35.2%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} \]

      3. *-commutative 35.2%

         \[\leadsto b \cdot \left(-k \cdot \color{blue}{\left(y4 \cdot y\right)}\right) \]

   8. Simplified 35.2%

      \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y4 \cdot y\right)\right)} \]

   if 5.1000000000000002e-110 < x < 2.09999999999999991e65

   1. Initial program 41.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 42.5%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.5%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 42.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 42.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 42.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 42.5%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 42.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 42.5%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 42.5%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 42.9%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 36.4%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 42.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.65 \cdot 10^{+174}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -2.9 \cdot 10^{+60}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -1.9 \cdot 10^{-137}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;x \leq 7 \cdot 10^{-207}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 5.1 \cdot 10^{-110}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;x \leq 2.1 \cdot 10^{+65}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \end{array} \]

Alternative 20: 28.7% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{if}\;x \leq -5.6 \cdot 10^{+172}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -4 \cdot 10^{+60}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -7 \cdot 10^{-137}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;x \leq 1.15 \cdot 10^{-206}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq 8 \cdot 10^{-111}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;x \leq 2.9 \cdot 10^{-83}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* k (- (* y y5) (* z y1))))))
   (if (<= x -5.6e+172)
     (* a (* x (- (* y b) (* y1 y2))))
     (if (<= x -4e+60)
       (* c (* y2 (* x y0)))
       (if (<= x -7e-137)
         (* c (* y4 (* t (- y2))))
         (if (<= x 1.15e-206)
           t_1
           (if (<= x 8e-111)
             (* b (* k (* y (- y4))))
             (if (<= x 2.9e-83) t_1 (* 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 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (x <= -5.6e+172) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (x <= -4e+60) {
		tmp = c * (y2 * (x * y0));
	} else if (x <= -7e-137) {
		tmp = c * (y4 * (t * -y2));
	} else if (x <= 1.15e-206) {
		tmp = t_1;
	} else if (x <= 8e-111) {
		tmp = b * (k * (y * -y4));
	} else if (x <= 2.9e-83) {
		tmp = t_1;
	} 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 = i * (k * ((y * y5) - (z * y1)))
    if (x <= (-5.6d+172)) then
        tmp = a * (x * ((y * b) - (y1 * y2)))
    else if (x <= (-4d+60)) then
        tmp = c * (y2 * (x * y0))
    else if (x <= (-7d-137)) then
        tmp = c * (y4 * (t * -y2))
    else if (x <= 1.15d-206) then
        tmp = t_1
    else if (x <= 8d-111) then
        tmp = b * (k * (y * -y4))
    else if (x <= 2.9d-83) then
        tmp = t_1
    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 = i * (k * ((y * y5) - (z * y1)));
	double tmp;
	if (x <= -5.6e+172) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (x <= -4e+60) {
		tmp = c * (y2 * (x * y0));
	} else if (x <= -7e-137) {
		tmp = c * (y4 * (t * -y2));
	} else if (x <= 1.15e-206) {
		tmp = t_1;
	} else if (x <= 8e-111) {
		tmp = b * (k * (y * -y4));
	} else if (x <= 2.9e-83) {
		tmp = t_1;
	} 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 = i * (k * ((y * y5) - (z * y1)))
	tmp = 0
	if x <= -5.6e+172:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	elif x <= -4e+60:
		tmp = c * (y2 * (x * y0))
	elif x <= -7e-137:
		tmp = c * (y4 * (t * -y2))
	elif x <= 1.15e-206:
		tmp = t_1
	elif x <= 8e-111:
		tmp = b * (k * (y * -y4))
	elif x <= 2.9e-83:
		tmp = t_1
	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(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))))
	tmp = 0.0
	if (x <= -5.6e+172)
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	elseif (x <= -4e+60)
		tmp = Float64(c * Float64(y2 * Float64(x * y0)));
	elseif (x <= -7e-137)
		tmp = Float64(c * Float64(y4 * Float64(t * Float64(-y2))));
	elseif (x <= 1.15e-206)
		tmp = t_1;
	elseif (x <= 8e-111)
		tmp = Float64(b * Float64(k * Float64(y * Float64(-y4))));
	elseif (x <= 2.9e-83)
		tmp = t_1;
	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 = i * (k * ((y * y5) - (z * y1)));
	tmp = 0.0;
	if (x <= -5.6e+172)
		tmp = a * (x * ((y * b) - (y1 * y2)));
	elseif (x <= -4e+60)
		tmp = c * (y2 * (x * y0));
	elseif (x <= -7e-137)
		tmp = c * (y4 * (t * -y2));
	elseif (x <= 1.15e-206)
		tmp = t_1;
	elseif (x <= 8e-111)
		tmp = b * (k * (y * -y4));
	elseif (x <= 2.9e-83)
		tmp = t_1;
	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[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -5.6e+172], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -4e+60], N[(c * N[(y2 * N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -7e-137], N[(c * N[(y4 * N[(t * (-y2)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.15e-206], t$95$1, If[LessEqual[x, 8e-111], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 2.9e-83], t$95$1, 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 x < -5.5999999999999999e172

   1. Initial program 15.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 44.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 55.2%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 55.2%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 55.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 55.2%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 55.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 55.2%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 55.2%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   if -5.5999999999999999e172 < x < -3.9999999999999998e60

   1. Initial program 9.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 26.0%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 26.0%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 26.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 39.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 50.1%

         \[\leadsto c \cdot \color{blue}{\left(\left(x \cdot y0\right) \cdot y2\right)} \]

   8. Simplified 50.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(x \cdot y0\right) \cdot y2\right)} \]

   if -3.9999999999999998e60 < x < -7.0000000000000002e-137

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 40.2%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 40.2%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 40.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 28.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around 0 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 31.5%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 31.5%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

      3. associate-*r* 34.4%

         \[\leadsto c \cdot \left(-\color{blue}{\left(t \cdot y2\right) \cdot y4}\right) \]

      4. *-commutative 34.4%

         \[\leadsto c \cdot \left(-\color{blue}{y4 \cdot \left(t \cdot y2\right)}\right) \]

      5. *-commutative 34.4%

         \[\leadsto c \cdot \left(-y4 \cdot \color{blue}{\left(y2 \cdot t\right)}\right) \]

   8. Simplified 34.4%

      \[\leadsto \color{blue}{c \cdot \left(-y4 \cdot \left(y2 \cdot t\right)\right)} \]

   if -7.0000000000000002e-137 < x < 1.15e-206 or 8.00000000000000071e-111 < x < 2.8999999999999999e-83

   1. Initial program 35.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 51.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 51.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 51.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 51.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 51.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 51.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 51.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 51.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 51.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 42.5%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 1.15e-206 < x < 8.00000000000000071e-111

   1. Initial program 22.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 40.5%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 40.5%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 40.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 40.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 40.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 40.5%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 40.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 40.5%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 40.5%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 40.7%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in b around inf 35.2%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 35.2%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 35.2%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} \]

      3. *-commutative 35.2%

         \[\leadsto b \cdot \left(-k \cdot \color{blue}{\left(y4 \cdot y\right)}\right) \]

   8. Simplified 35.2%

      \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y4 \cdot y\right)\right)} \]

   if 2.8999999999999999e-83 < x

   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. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 41.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 43.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -5.6 \cdot 10^{+172}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;x \leq -4 \cdot 10^{+60}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{elif}\;x \leq -7 \cdot 10^{-137}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;x \leq 1.15 \cdot 10^{-206}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;x \leq 8 \cdot 10^{-111}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;x \leq 2.9 \cdot 10^{-83}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]

Alternative 21: 27.8% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ t_2 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y3 \leq -9.2 \cdot 10^{+69}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y3 \leq -1.52 \cdot 10^{-62}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y3 \leq -2.2 \cdot 10^{-130}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y3 \leq 5 \cdot 10^{-226}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y3 \leq 6.2 \cdot 10^{+119}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* t (- (* b y4) (* i y5)))))
        (t_2 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y3 -9.2e+69)
     t_2
     (if (<= y3 -1.52e-62)
       t_1
       (if (<= y3 -2.2e-130)
         t_2
         (if (<= y3 5e-226)
           t_1
           (if (<= y3 6.2e+119)
             (* i (* k (- (* y y5) (* z y1))))
             (* a (* x (- (* y b) (* y1 y2)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y3 <= -9.2e+69) {
		tmp = t_2;
	} else if (y3 <= -1.52e-62) {
		tmp = t_1;
	} else if (y3 <= -2.2e-130) {
		tmp = t_2;
	} else if (y3 <= 5e-226) {
		tmp = t_1;
	} else if (y3 <= 6.2e+119) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (t * ((b * y4) - (i * y5)))
    t_2 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y3 <= (-9.2d+69)) then
        tmp = t_2
    else if (y3 <= (-1.52d-62)) then
        tmp = t_1
    else if (y3 <= (-2.2d-130)) then
        tmp = t_2
    else if (y3 <= 5d-226) then
        tmp = t_1
    else if (y3 <= 6.2d+119) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else
        tmp = a * (x * ((y * b) - (y1 * y2)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (t * ((b * y4) - (i * y5)));
	double t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y3 <= -9.2e+69) {
		tmp = t_2;
	} else if (y3 <= -1.52e-62) {
		tmp = t_1;
	} else if (y3 <= -2.2e-130) {
		tmp = t_2;
	} else if (y3 <= 5e-226) {
		tmp = t_1;
	} else if (y3 <= 6.2e+119) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (t * ((b * y4) - (i * y5)))
	t_2 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y3 <= -9.2e+69:
		tmp = t_2
	elif y3 <= -1.52e-62:
		tmp = t_1
	elif y3 <= -2.2e-130:
		tmp = t_2
	elif y3 <= 5e-226:
		tmp = t_1
	elif y3 <= 6.2e+119:
		tmp = i * (k * ((y * y5) - (z * y1)))
	else:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))))
	t_2 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y3 <= -9.2e+69)
		tmp = t_2;
	elseif (y3 <= -1.52e-62)
		tmp = t_1;
	elseif (y3 <= -2.2e-130)
		tmp = t_2;
	elseif (y3 <= 5e-226)
		tmp = t_1;
	elseif (y3 <= 6.2e+119)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	else
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (t * ((b * y4) - (i * y5)));
	t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y3 <= -9.2e+69)
		tmp = t_2;
	elseif (y3 <= -1.52e-62)
		tmp = t_1;
	elseif (y3 <= -2.2e-130)
		tmp = t_2;
	elseif (y3 <= 5e-226)
		tmp = t_1;
	elseif (y3 <= 6.2e+119)
		tmp = i * (k * ((y * y5) - (z * y1)));
	else
		tmp = a * (x * ((y * b) - (y1 * y2)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y3, -9.2e+69], t$95$2, If[LessEqual[y3, -1.52e-62], t$95$1, If[LessEqual[y3, -2.2e-130], t$95$2, If[LessEqual[y3, 5e-226], t$95$1, If[LessEqual[y3, 6.2e+119], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if y3 < -9.20000000000000067e69 or -1.52000000000000007e-62 < y3 < -2.1999999999999999e-130

   1. Initial program 18.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. 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%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 33.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 38.4%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 38.4%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 38.4%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. unsub-neg 38.4%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - b \cdot x\right)}\right) \]

      4. *-commutative 38.4%

         \[\leadsto j \cdot \left(y0 \cdot \left(\color{blue}{y5 \cdot y3} - b \cdot x\right)\right) \]

   7. Simplified 38.4%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y5 \cdot y3 - b \cdot x\right)\right)} \]

   if -9.20000000000000067e69 < y3 < -1.52000000000000007e-62 or -2.1999999999999999e-130 < y3 < 4.9999999999999998e-226

   1. Initial program 30.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 46.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 46.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 46.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 46.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 46.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 46.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 40.6%

      \[\leadsto j \cdot \color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 40.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(b \cdot y4 - i \cdot y5\right) \cdot t\right)} \]

      2. *-commutative 40.6%

         \[\leadsto j \cdot \left(\left(\color{blue}{y4 \cdot b} - i \cdot y5\right) \cdot t\right) \]

   7. Simplified 40.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(y4 \cdot b - i \cdot y5\right) \cdot t\right)} \]

   if 4.9999999999999998e-226 < y3 < 6.1999999999999999e119

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 42.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 42.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 42.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 42.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 42.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 42.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 42.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 42.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 42.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in i around -inf 40.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]

   if 6.1999999999999999e119 < y3

   1. Initial program 12.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 34.6%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 50.9%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 50.9%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 50.9%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 50.9%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 50.9%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 50.9%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 50.9%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 41.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -9.2 \cdot 10^{+69}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y3 \leq -1.52 \cdot 10^{-62}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq -2.2 \cdot 10^{-130}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y3 \leq 5 \cdot 10^{-226}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y3 \leq 6.2 \cdot 10^{+119}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \end{array} \]

Alternative 22: 20.4% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -1.75 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.7 \cdot 10^{-41}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;i \leq -1.5 \cdot 10^{-244}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 7 \cdot 10^{-45}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 9.2 \cdot 10^{+107}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -1.75e+188)
   (* j (* x (* i y1)))
   (if (<= i -2.7e-41)
     (* i (* y5 (* y k)))
     (if (<= i -1.5e-244)
       (* k (* y1 (* y2 y4)))
       (if (<= i 7e-45)
         (* b (* k (* z y0)))
         (if (<= i 9.2e+107) (* i (* k (* y 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 <= -1.75e+188) {
		tmp = j * (x * (i * y1));
	} else if (i <= -2.7e-41) {
		tmp = i * (y5 * (y * k));
	} else if (i <= -1.5e-244) {
		tmp = k * (y1 * (y2 * y4));
	} else if (i <= 7e-45) {
		tmp = b * (k * (z * y0));
	} else if (i <= 9.2e+107) {
		tmp = i * (k * (y * 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 <= (-1.75d+188)) then
        tmp = j * (x * (i * y1))
    else if (i <= (-2.7d-41)) then
        tmp = i * (y5 * (y * k))
    else if (i <= (-1.5d-244)) then
        tmp = k * (y1 * (y2 * y4))
    else if (i <= 7d-45) then
        tmp = b * (k * (z * y0))
    else if (i <= 9.2d+107) then
        tmp = i * (k * (y * 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 <= -1.75e+188) {
		tmp = j * (x * (i * y1));
	} else if (i <= -2.7e-41) {
		tmp = i * (y5 * (y * k));
	} else if (i <= -1.5e-244) {
		tmp = k * (y1 * (y2 * y4));
	} else if (i <= 7e-45) {
		tmp = b * (k * (z * y0));
	} else if (i <= 9.2e+107) {
		tmp = i * (k * (y * 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 <= -1.75e+188:
		tmp = j * (x * (i * y1))
	elif i <= -2.7e-41:
		tmp = i * (y5 * (y * k))
	elif i <= -1.5e-244:
		tmp = k * (y1 * (y2 * y4))
	elif i <= 7e-45:
		tmp = b * (k * (z * y0))
	elif i <= 9.2e+107:
		tmp = i * (k * (y * 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 <= -1.75e+188)
		tmp = Float64(j * Float64(x * Float64(i * y1)));
	elseif (i <= -2.7e-41)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (i <= -1.5e-244)
		tmp = Float64(k * Float64(y1 * Float64(y2 * y4)));
	elseif (i <= 7e-45)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (i <= 9.2e+107)
		tmp = Float64(i * Float64(k * Float64(y * 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 <= -1.75e+188)
		tmp = j * (x * (i * y1));
	elseif (i <= -2.7e-41)
		tmp = i * (y5 * (y * k));
	elseif (i <= -1.5e-244)
		tmp = k * (y1 * (y2 * y4));
	elseif (i <= 7e-45)
		tmp = b * (k * (z * y0));
	elseif (i <= 9.2e+107)
		tmp = i * (k * (y * 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, -1.75e+188], N[(j * N[(x * N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -2.7e-41], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.5e-244], N[(k * N[(y1 * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 7e-45], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 9.2e+107], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if i < -1.75000000000000004e188

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 42.7%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(i \cdot y1\right)}\right) \]

   if -1.75000000000000004e188 < i < -2.7e-41

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 57.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 57.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 57.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 57.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 57.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 57.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 57.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 46.2%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 31.6%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 33.5%

         \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   8. Simplified 33.5%

      \[\leadsto \color{blue}{i \cdot \left(\left(k \cdot y\right) \cdot y5\right)} \]

   if -2.7e-41 < i < -1.5000000000000001e-244

   1. Initial program 19.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 38.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 38.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 38.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 38.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 38.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 45.7%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in y1 around inf 28.6%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]

   if -1.5000000000000001e-244 < i < 7e-45

   1. Initial program 29.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 45.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 45.6%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 45.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 45.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 45.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 45.6%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 45.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 45.6%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 45.6%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 36.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 36.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 36.8%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 36.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 36.8%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 36.8%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 36.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 28.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 7e-45 < i < 9.2000000000000001e107

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 33.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 33.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 33.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 33.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 33.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 33.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 33.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 34.1%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 28.0%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]

   if 9.2000000000000001e107 < i

   1. Initial program 15.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 43.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.4%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.5%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 56.1%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 56.1%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 56.1%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 35.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -1.75 \cdot 10^{+188}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -2.7 \cdot 10^{-41}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;i \leq -1.5 \cdot 10^{-244}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 7 \cdot 10^{-45}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 9.2 \cdot 10^{+107}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 23: 20.4% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -2.4 \cdot 10^{+191}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -7.5 \cdot 10^{-44}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;i \leq -6.4 \cdot 10^{-246}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 1.42 \cdot 10^{-42}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 1.05 \cdot 10^{+108}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -2.4e+191)
   (* j (* x (* i y1)))
   (if (<= i -7.5e-44)
     (* i (* y5 (* y k)))
     (if (<= i -6.4e-246)
       (* k (* y4 (* y1 y2)))
       (if (<= i 1.42e-42)
         (* b (* k (* z y0)))
         (if (<= i 1.05e+108) (* i (* k (* y 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 <= -2.4e+191) {
		tmp = j * (x * (i * y1));
	} else if (i <= -7.5e-44) {
		tmp = i * (y5 * (y * k));
	} else if (i <= -6.4e-246) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 1.42e-42) {
		tmp = b * (k * (z * y0));
	} else if (i <= 1.05e+108) {
		tmp = i * (k * (y * 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 <= (-2.4d+191)) then
        tmp = j * (x * (i * y1))
    else if (i <= (-7.5d-44)) then
        tmp = i * (y5 * (y * k))
    else if (i <= (-6.4d-246)) then
        tmp = k * (y4 * (y1 * y2))
    else if (i <= 1.42d-42) then
        tmp = b * (k * (z * y0))
    else if (i <= 1.05d+108) then
        tmp = i * (k * (y * 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 <= -2.4e+191) {
		tmp = j * (x * (i * y1));
	} else if (i <= -7.5e-44) {
		tmp = i * (y5 * (y * k));
	} else if (i <= -6.4e-246) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 1.42e-42) {
		tmp = b * (k * (z * y0));
	} else if (i <= 1.05e+108) {
		tmp = i * (k * (y * 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 <= -2.4e+191:
		tmp = j * (x * (i * y1))
	elif i <= -7.5e-44:
		tmp = i * (y5 * (y * k))
	elif i <= -6.4e-246:
		tmp = k * (y4 * (y1 * y2))
	elif i <= 1.42e-42:
		tmp = b * (k * (z * y0))
	elif i <= 1.05e+108:
		tmp = i * (k * (y * 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 <= -2.4e+191)
		tmp = Float64(j * Float64(x * Float64(i * y1)));
	elseif (i <= -7.5e-44)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (i <= -6.4e-246)
		tmp = Float64(k * Float64(y4 * Float64(y1 * y2)));
	elseif (i <= 1.42e-42)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (i <= 1.05e+108)
		tmp = Float64(i * Float64(k * Float64(y * 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 <= -2.4e+191)
		tmp = j * (x * (i * y1));
	elseif (i <= -7.5e-44)
		tmp = i * (y5 * (y * k));
	elseif (i <= -6.4e-246)
		tmp = k * (y4 * (y1 * y2));
	elseif (i <= 1.42e-42)
		tmp = b * (k * (z * y0));
	elseif (i <= 1.05e+108)
		tmp = i * (k * (y * 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, -2.4e+191], N[(j * N[(x * N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -7.5e-44], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -6.4e-246], N[(k * N[(y4 * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.42e-42], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.05e+108], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if i < -2.39999999999999986e191

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 42.7%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(i \cdot y1\right)}\right) \]

   if -2.39999999999999986e191 < i < -7.50000000000000008e-44

   1. Initial program 33.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 57.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 57.9%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 57.9%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 57.9%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 57.9%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 57.9%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 57.9%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 57.9%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 46.2%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 31.6%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 33.5%

         \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   8. Simplified 33.5%

      \[\leadsto \color{blue}{i \cdot \left(\left(k \cdot y\right) \cdot y5\right)} \]

   if -7.50000000000000008e-44 < i < -6.4000000000000001e-246

   1. Initial program 19.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 38.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 38.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 38.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 38.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 38.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 45.7%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in y1 around inf 28.6%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 35.3%

         \[\leadsto k \cdot \color{blue}{\left(\left(y1 \cdot y2\right) \cdot y4\right)} \]

      2. *-commutative 35.3%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot y1\right)} \cdot y4\right) \]

      3. *-commutative 35.3%

         \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   8. Simplified 35.3%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   if -6.4000000000000001e-246 < i < 1.42000000000000005e-42

   1. Initial program 29.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 45.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 45.6%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 45.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 45.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 45.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 45.6%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 45.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 45.6%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 45.6%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 36.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 36.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 36.8%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 36.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 36.8%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 36.8%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 36.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 28.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 1.42000000000000005e-42 < i < 1.05000000000000005e108

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 33.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 33.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 33.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 33.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 33.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 33.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 33.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 34.1%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 28.0%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]

   if 1.05000000000000005e108 < i

   1. Initial program 15.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 43.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.4%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.5%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 56.1%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 56.1%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 56.1%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 36.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -2.4 \cdot 10^{+191}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -7.5 \cdot 10^{-44}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;i \leq -6.4 \cdot 10^{-246}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 1.42 \cdot 10^{-42}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 1.05 \cdot 10^{+108}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 24: 20.3% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -1.96 \cdot 10^{-41}:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i\right)\\ \mathbf{elif}\;i \leq -1.1 \cdot 10^{-245}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 3.4 \cdot 10^{-119}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 2.7 \cdot 10^{-21}:\\ \;\;\;\;\left(-a\right) \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 1.2 \cdot 10^{+108}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -1.96e-41)
   (* (* k y5) (* y i))
   (if (<= i -1.1e-245)
     (* k (* y4 (* y1 y2)))
     (if (<= i 3.4e-119)
       (* b (* k (* z y0)))
       (if (<= i 2.7e-21)
         (* (- a) (* x (* y1 y2)))
         (if (<= i 1.2e+108) (* i (* k (* y 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 <= -1.96e-41) {
		tmp = (k * y5) * (y * i);
	} else if (i <= -1.1e-245) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 3.4e-119) {
		tmp = b * (k * (z * y0));
	} else if (i <= 2.7e-21) {
		tmp = -a * (x * (y1 * y2));
	} else if (i <= 1.2e+108) {
		tmp = i * (k * (y * 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 <= (-1.96d-41)) then
        tmp = (k * y5) * (y * i)
    else if (i <= (-1.1d-245)) then
        tmp = k * (y4 * (y1 * y2))
    else if (i <= 3.4d-119) then
        tmp = b * (k * (z * y0))
    else if (i <= 2.7d-21) then
        tmp = -a * (x * (y1 * y2))
    else if (i <= 1.2d+108) then
        tmp = i * (k * (y * 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 <= -1.96e-41) {
		tmp = (k * y5) * (y * i);
	} else if (i <= -1.1e-245) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 3.4e-119) {
		tmp = b * (k * (z * y0));
	} else if (i <= 2.7e-21) {
		tmp = -a * (x * (y1 * y2));
	} else if (i <= 1.2e+108) {
		tmp = i * (k * (y * 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 <= -1.96e-41:
		tmp = (k * y5) * (y * i)
	elif i <= -1.1e-245:
		tmp = k * (y4 * (y1 * y2))
	elif i <= 3.4e-119:
		tmp = b * (k * (z * y0))
	elif i <= 2.7e-21:
		tmp = -a * (x * (y1 * y2))
	elif i <= 1.2e+108:
		tmp = i * (k * (y * 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 <= -1.96e-41)
		tmp = Float64(Float64(k * y5) * Float64(y * i));
	elseif (i <= -1.1e-245)
		tmp = Float64(k * Float64(y4 * Float64(y1 * y2)));
	elseif (i <= 3.4e-119)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (i <= 2.7e-21)
		tmp = Float64(Float64(-a) * Float64(x * Float64(y1 * y2)));
	elseif (i <= 1.2e+108)
		tmp = Float64(i * Float64(k * Float64(y * 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 <= -1.96e-41)
		tmp = (k * y5) * (y * i);
	elseif (i <= -1.1e-245)
		tmp = k * (y4 * (y1 * y2));
	elseif (i <= 3.4e-119)
		tmp = b * (k * (z * y0));
	elseif (i <= 2.7e-21)
		tmp = -a * (x * (y1 * y2));
	elseif (i <= 1.2e+108)
		tmp = i * (k * (y * 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, -1.96e-41], N[(N[(k * y5), $MachinePrecision] * N[(y * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.1e-245], N[(k * N[(y4 * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 3.4e-119], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2.7e-21], N[((-a) * N[(x * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.2e+108], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if i < -1.96e-41

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 53.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 53.0%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 53.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 53.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 53.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 53.0%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 53.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 53.0%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 53.0%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y5 around -inf 42.4%

      \[\leadsto \color{blue}{k \cdot \left(y5 \cdot \left(i \cdot y - y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 40.9%

         \[\leadsto \color{blue}{\left(k \cdot y5\right) \cdot \left(i \cdot y - y0 \cdot y2\right)} \]

      2. *-commutative 40.9%

         \[\leadsto \left(k \cdot y5\right) \cdot \left(i \cdot y - \color{blue}{y2 \cdot y0}\right) \]

   7. Simplified 40.9%

      \[\leadsto \color{blue}{\left(k \cdot y5\right) \cdot \left(i \cdot y - y2 \cdot y0\right)} \]

   8. Taylor expanded in i around inf 34.4%

      \[\leadsto \left(k \cdot y5\right) \cdot \color{blue}{\left(i \cdot y\right)} \]
   9. Step-by-step derivation

      1. *-commutative 34.4%

         \[\leadsto \left(k \cdot y5\right) \cdot \color{blue}{\left(y \cdot i\right)} \]

   10. Simplified 34.4%

       \[\leadsto \left(k \cdot y5\right) \cdot \color{blue}{\left(y \cdot i\right)} \]

   if -1.96e-41 < i < -1.09999999999999996e-245

   1. Initial program 19.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 38.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 38.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 38.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 38.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 38.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 45.7%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in y1 around inf 28.6%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 35.3%

         \[\leadsto k \cdot \color{blue}{\left(\left(y1 \cdot y2\right) \cdot y4\right)} \]

      2. *-commutative 35.3%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot y1\right)} \cdot y4\right) \]

      3. *-commutative 35.3%

         \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   8. Simplified 35.3%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   if -1.09999999999999996e-245 < i < 3.40000000000000024e-119

   1. Initial program 29.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 47.5%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 47.5%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 47.5%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 47.5%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 47.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 47.5%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 47.5%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 47.5%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 47.5%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 39.0%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 39.0%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 39.0%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 39.0%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 39.0%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 39.0%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 39.0%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 28.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 3.40000000000000024e-119 < i < 2.7000000000000001e-21

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 58.3%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 58.9%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 58.9%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 58.9%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 58.9%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 58.9%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 58.9%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 58.9%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   6. Taylor expanded in y around 0 50.6%

      \[\leadsto a \cdot \left(\color{blue}{\left(-1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 50.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(-y1 \cdot y2\right)} \cdot x\right) \]

      2. distribute-lft-neg-out 50.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(\left(-y1\right) \cdot y2\right)} \cdot x\right) \]

      3. *-commutative 50.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(y2 \cdot \left(-y1\right)\right)} \cdot x\right) \]

   8. Simplified 50.6%

      \[\leadsto a \cdot \left(\color{blue}{\left(y2 \cdot \left(-y1\right)\right)} \cdot x\right) \]

   if 2.7000000000000001e-21 < i < 1.20000000000000009e108

   1. Initial program 25.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 33.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 33.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 33.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 33.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 33.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 33.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 33.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 34.1%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 27.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]

   if 1.20000000000000009e108 < i

   1. Initial program 15.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 43.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.4%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.5%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 56.1%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 56.1%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 56.1%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 37.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -1.96 \cdot 10^{-41}:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i\right)\\ \mathbf{elif}\;i \leq -1.1 \cdot 10^{-245}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 3.4 \cdot 10^{-119}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 2.7 \cdot 10^{-21}:\\ \;\;\;\;\left(-a\right) \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 1.2 \cdot 10^{+108}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 25: 26.5% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -1.35 \cdot 10^{+185}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -3.9 \cdot 10^{-34}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 4.7 \cdot 10^{+48}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 1.4 \cdot 10^{+131}:\\ \;\;\;\;\left(y \cdot y5\right) \cdot \left(i \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y2 \cdot \left(-y0\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y0 -1.35e+185)
   (* c (* x (* y0 y2)))
   (if (<= y0 -3.9e-34)
     (* j (* x (* i y1)))
     (if (<= y0 4.7e+48)
       (* a (* x (- (* y b) (* y1 y2))))
       (if (<= y0 1.4e+131)
         (* (* y y5) (* i k))
         (* k (* y5 (* y2 (- 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 <= -1.35e+185) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -3.9e-34) {
		tmp = j * (x * (i * y1));
	} else if (y0 <= 4.7e+48) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (y0 <= 1.4e+131) {
		tmp = (y * y5) * (i * k);
	} else {
		tmp = k * (y5 * (y2 * -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 <= (-1.35d+185)) then
        tmp = c * (x * (y0 * y2))
    else if (y0 <= (-3.9d-34)) then
        tmp = j * (x * (i * y1))
    else if (y0 <= 4.7d+48) then
        tmp = a * (x * ((y * b) - (y1 * y2)))
    else if (y0 <= 1.4d+131) then
        tmp = (y * y5) * (i * k)
    else
        tmp = k * (y5 * (y2 * -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 <= -1.35e+185) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -3.9e-34) {
		tmp = j * (x * (i * y1));
	} else if (y0 <= 4.7e+48) {
		tmp = a * (x * ((y * b) - (y1 * y2)));
	} else if (y0 <= 1.4e+131) {
		tmp = (y * y5) * (i * k);
	} else {
		tmp = k * (y5 * (y2 * -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 <= -1.35e+185:
		tmp = c * (x * (y0 * y2))
	elif y0 <= -3.9e-34:
		tmp = j * (x * (i * y1))
	elif y0 <= 4.7e+48:
		tmp = a * (x * ((y * b) - (y1 * y2)))
	elif y0 <= 1.4e+131:
		tmp = (y * y5) * (i * k)
	else:
		tmp = k * (y5 * (y2 * -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 <= -1.35e+185)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y0 <= -3.9e-34)
		tmp = Float64(j * Float64(x * Float64(i * y1)));
	elseif (y0 <= 4.7e+48)
		tmp = Float64(a * Float64(x * Float64(Float64(y * b) - Float64(y1 * y2))));
	elseif (y0 <= 1.4e+131)
		tmp = Float64(Float64(y * y5) * Float64(i * k));
	else
		tmp = Float64(k * Float64(y5 * Float64(y2 * Float64(-y0))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y0 <= -1.35e+185)
		tmp = c * (x * (y0 * y2));
	elseif (y0 <= -3.9e-34)
		tmp = j * (x * (i * y1));
	elseif (y0 <= 4.7e+48)
		tmp = a * (x * ((y * b) - (y1 * y2)));
	elseif (y0 <= 1.4e+131)
		tmp = (y * y5) * (i * k);
	else
		tmp = k * (y5 * (y2 * -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, -1.35e+185], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -3.9e-34], N[(j * N[(x * N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 4.7e+48], N[(a * N[(x * N[(N[(y * b), $MachinePrecision] - N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.4e+131], N[(N[(y * y5), $MachinePrecision] * N[(i * k), $MachinePrecision]), $MachinePrecision], N[(k * N[(y5 * N[(y2 * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y0 < -1.35000000000000003e185

   1. Initial program 21.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 29.3%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 29.3%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 29.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 39.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 64.6%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]

   if -1.35000000000000003e185 < y0 < -3.89999999999999991e-34

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 45.6%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 38.1%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(i \cdot y1\right)}\right) \]

   if -3.89999999999999991e-34 < y0 < 4.70000000000000012e48

   1. Initial program 29.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 41.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 30.6%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 30.6%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 30.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 30.6%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 30.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 30.6%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 30.6%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   if 4.70000000000000012e48 < y0 < 1.4e131

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 34.2%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 34.2%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 34.2%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 34.2%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 34.2%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 34.2%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 34.2%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 34.2%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 34.2%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 38.5%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 42.8%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 50.7%

         \[\leadsto \color{blue}{\left(i \cdot k\right) \cdot \left(y \cdot y5\right)} \]

      2. *-commutative 50.7%

         \[\leadsto \color{blue}{\left(y \cdot y5\right) \cdot \left(i \cdot k\right)} \]

      3. *-commutative 50.7%

         \[\leadsto \color{blue}{\left(y5 \cdot y\right)} \cdot \left(i \cdot k\right) \]

      4. *-commutative 50.7%

         \[\leadsto \left(y5 \cdot y\right) \cdot \color{blue}{\left(k \cdot i\right)} \]

   8. Simplified 50.7%

      \[\leadsto \color{blue}{\left(y5 \cdot y\right) \cdot \left(k \cdot i\right)} \]

   if 1.4e131 < y0

   1. Initial program 16.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 45.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 45.4%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 45.4%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 45.4%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 45.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 45.4%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 45.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 45.4%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 45.4%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 48.6%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in y0 around inf 35.1%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 35.1%

         \[\leadsto \color{blue}{-k \cdot \left(y0 \cdot \left(y2 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 35.1%

         \[\leadsto \color{blue}{k \cdot \left(-y0 \cdot \left(y2 \cdot y5\right)\right)} \]

      3. associate-*r* 43.2%

         \[\leadsto k \cdot \left(-\color{blue}{\left(y0 \cdot y2\right) \cdot y5}\right) \]

      4. *-commutative 43.2%

         \[\leadsto k \cdot \left(-\color{blue}{\left(y2 \cdot y0\right)} \cdot y5\right) \]

      5. distribute-rgt-neg-in 43.2%

         \[\leadsto k \cdot \color{blue}{\left(\left(y2 \cdot y0\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 43.2%

      \[\leadsto \color{blue}{k \cdot \left(\left(y2 \cdot y0\right) \cdot \left(-y5\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 39.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -1.35 \cdot 10^{+185}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -3.9 \cdot 10^{-34}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 4.7 \cdot 10^{+48}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y \cdot b - y1 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq 1.4 \cdot 10^{+131}:\\ \;\;\;\;\left(y \cdot y5\right) \cdot \left(i \cdot k\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y5 \cdot \left(y2 \cdot \left(-y0\right)\right)\right)\\ \end{array} \]

Alternative 26: 21.3% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{if}\;y2 \leq -8 \cdot 10^{+103}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq 8.5 \cdot 10^{-84}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 2.05 \cdot 10^{+76}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 7 \cdot 10^{+106}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* i (* j (* x y1)))))
   (if (<= y2 -8e+103)
     (* c (* x (* y0 y2)))
     (if (<= y2 8.5e-84)
       t_1
       (if (<= y2 2.05e+76)
         (* b (* k (* z y0)))
         (if (<= y2 7e+106) t_1 (* a (* t (* y2 y5)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (j * (x * y1));
	double tmp;
	if (y2 <= -8e+103) {
		tmp = c * (x * (y0 * y2));
	} else if (y2 <= 8.5e-84) {
		tmp = t_1;
	} else if (y2 <= 2.05e+76) {
		tmp = b * (k * (z * y0));
	} else if (y2 <= 7e+106) {
		tmp = t_1;
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = i * (j * (x * y1))
    if (y2 <= (-8d+103)) then
        tmp = c * (x * (y0 * y2))
    else if (y2 <= 8.5d-84) then
        tmp = t_1
    else if (y2 <= 2.05d+76) then
        tmp = b * (k * (z * y0))
    else if (y2 <= 7d+106) then
        tmp = t_1
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = i * (j * (x * y1));
	double tmp;
	if (y2 <= -8e+103) {
		tmp = c * (x * (y0 * y2));
	} else if (y2 <= 8.5e-84) {
		tmp = t_1;
	} else if (y2 <= 2.05e+76) {
		tmp = b * (k * (z * y0));
	} else if (y2 <= 7e+106) {
		tmp = t_1;
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = i * (j * (x * y1))
	tmp = 0
	if y2 <= -8e+103:
		tmp = c * (x * (y0 * y2))
	elif y2 <= 8.5e-84:
		tmp = t_1
	elif y2 <= 2.05e+76:
		tmp = b * (k * (z * y0))
	elif y2 <= 7e+106:
		tmp = t_1
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(i * Float64(j * Float64(x * y1)))
	tmp = 0.0
	if (y2 <= -8e+103)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y2 <= 8.5e-84)
		tmp = t_1;
	elseif (y2 <= 2.05e+76)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (y2 <= 7e+106)
		tmp = t_1;
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = i * (j * (x * y1));
	tmp = 0.0;
	if (y2 <= -8e+103)
		tmp = c * (x * (y0 * y2));
	elseif (y2 <= 8.5e-84)
		tmp = t_1;
	elseif (y2 <= 2.05e+76)
		tmp = b * (k * (z * y0));
	elseif (y2 <= 7e+106)
		tmp = t_1;
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -8e+103], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 8.5e-84], t$95$1, If[LessEqual[y2, 2.05e+76], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 7e+106], t$95$1, N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 4 regimes

2. if y2 < -8e103

   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. Taylor expanded in y2 around inf 32.8%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 32.8%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 32.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 51.4%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 47.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]

   if -8e103 < y2 < 8.4999999999999994e-84 or 2.0499999999999999e76 < y2 < 6.99999999999999962e106

   1. Initial program 31.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 47.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 47.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 47.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 47.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 47.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 47.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 37.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 28.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if 8.4999999999999994e-84 < y2 < 2.0499999999999999e76

   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. Taylor expanded in k around -inf 40.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 40.0%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 40.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 40.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 40.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 40.0%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 40.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 40.0%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 40.0%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 22.9%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 22.9%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 22.9%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 22.9%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 22.9%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 22.9%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 22.9%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 23.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 6.99999999999999962e106 < y2

   1. Initial program 13.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 33.0%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 33.0%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 33.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 35.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 33.6%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 33.6%

         \[\leadsto a \cdot \color{blue}{\left(\left(y2 \cdot y5\right) \cdot t\right)} \]

   8. Simplified 33.6%

      \[\leadsto \color{blue}{a \cdot \left(\left(y2 \cdot y5\right) \cdot t\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 31.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -8 \cdot 10^{+103}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq 8.5 \cdot 10^{-84}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{elif}\;y2 \leq 2.05 \cdot 10^{+76}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 7 \cdot 10^{+106}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]

Alternative 27: 19.6% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -8 \cdot 10^{+187}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -1.15 \cdot 10^{-197}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;i \leq 1.7 \cdot 10^{-42}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 9.5 \cdot 10^{+107}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -8e+187)
   (* j (* x (* i y1)))
   (if (<= i -1.15e-197)
     (* i (* y5 (* y k)))
     (if (<= i 1.7e-42)
       (* b (* k (* z y0)))
       (if (<= i 9.5e+107) (* i (* k (* y 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 <= -8e+187) {
		tmp = j * (x * (i * y1));
	} else if (i <= -1.15e-197) {
		tmp = i * (y5 * (y * k));
	} else if (i <= 1.7e-42) {
		tmp = b * (k * (z * y0));
	} else if (i <= 9.5e+107) {
		tmp = i * (k * (y * 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 <= (-8d+187)) then
        tmp = j * (x * (i * y1))
    else if (i <= (-1.15d-197)) then
        tmp = i * (y5 * (y * k))
    else if (i <= 1.7d-42) then
        tmp = b * (k * (z * y0))
    else if (i <= 9.5d+107) then
        tmp = i * (k * (y * 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 <= -8e+187) {
		tmp = j * (x * (i * y1));
	} else if (i <= -1.15e-197) {
		tmp = i * (y5 * (y * k));
	} else if (i <= 1.7e-42) {
		tmp = b * (k * (z * y0));
	} else if (i <= 9.5e+107) {
		tmp = i * (k * (y * 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 <= -8e+187:
		tmp = j * (x * (i * y1))
	elif i <= -1.15e-197:
		tmp = i * (y5 * (y * k))
	elif i <= 1.7e-42:
		tmp = b * (k * (z * y0))
	elif i <= 9.5e+107:
		tmp = i * (k * (y * 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 <= -8e+187)
		tmp = Float64(j * Float64(x * Float64(i * y1)));
	elseif (i <= -1.15e-197)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (i <= 1.7e-42)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (i <= 9.5e+107)
		tmp = Float64(i * Float64(k * Float64(y * 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 <= -8e+187)
		tmp = j * (x * (i * y1));
	elseif (i <= -1.15e-197)
		tmp = i * (y5 * (y * k));
	elseif (i <= 1.7e-42)
		tmp = b * (k * (z * y0));
	elseif (i <= 9.5e+107)
		tmp = i * (k * (y * 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, -8e+187], N[(j * N[(x * N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.15e-197], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.7e-42], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 9.5e+107], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if i < -7.99999999999999926e187

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 47.5%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 42.7%

      \[\leadsto j \cdot \left(x \cdot \color{blue}{\left(i \cdot y1\right)}\right) \]

   if -7.99999999999999926e187 < i < -1.15e-197

   1. Initial program 27.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 50.2%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 50.2%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 50.2%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 50.2%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 50.2%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 50.2%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 50.2%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 50.2%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 50.2%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 46.8%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 26.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 27.4%

         \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   8. Simplified 27.4%

      \[\leadsto \color{blue}{i \cdot \left(\left(k \cdot y\right) \cdot y5\right)} \]

   if -1.15e-197 < i < 1.70000000000000011e-42

   1. Initial program 30.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 44.7%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 44.7%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 44.7%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 44.7%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 44.7%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 44.7%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 44.7%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 44.7%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 44.7%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 36.6%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 36.6%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 36.6%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 36.6%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 36.6%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 36.6%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 36.6%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 27.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 1.70000000000000011e-42 < i < 9.50000000000000019e107

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 33.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 33.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 33.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 33.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 33.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 33.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 33.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 34.1%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 28.0%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]

   if 9.50000000000000019e107 < i

   1. Initial program 15.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 43.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.4%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.5%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 56.1%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 56.1%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 56.1%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 33.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -8 \cdot 10^{+187}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq -1.15 \cdot 10^{-197}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;i \leq 1.7 \cdot 10^{-42}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 9.5 \cdot 10^{+107}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 28: 20.3% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -1.7 \cdot 10^{-42}:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i\right)\\ \mathbf{elif}\;i \leq -1.28 \cdot 10^{-244}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 4.2 \cdot 10^{-48}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 1.5 \cdot 10^{+108}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= i -1.7e-42)
   (* (* k y5) (* y i))
   (if (<= i -1.28e-244)
     (* k (* y4 (* y1 y2)))
     (if (<= i 4.2e-48)
       (* b (* k (* z y0)))
       (if (<= i 1.5e+108) (* i (* k (* y 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 <= -1.7e-42) {
		tmp = (k * y5) * (y * i);
	} else if (i <= -1.28e-244) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 4.2e-48) {
		tmp = b * (k * (z * y0));
	} else if (i <= 1.5e+108) {
		tmp = i * (k * (y * 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 <= (-1.7d-42)) then
        tmp = (k * y5) * (y * i)
    else if (i <= (-1.28d-244)) then
        tmp = k * (y4 * (y1 * y2))
    else if (i <= 4.2d-48) then
        tmp = b * (k * (z * y0))
    else if (i <= 1.5d+108) then
        tmp = i * (k * (y * 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 <= -1.7e-42) {
		tmp = (k * y5) * (y * i);
	} else if (i <= -1.28e-244) {
		tmp = k * (y4 * (y1 * y2));
	} else if (i <= 4.2e-48) {
		tmp = b * (k * (z * y0));
	} else if (i <= 1.5e+108) {
		tmp = i * (k * (y * 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 <= -1.7e-42:
		tmp = (k * y5) * (y * i)
	elif i <= -1.28e-244:
		tmp = k * (y4 * (y1 * y2))
	elif i <= 4.2e-48:
		tmp = b * (k * (z * y0))
	elif i <= 1.5e+108:
		tmp = i * (k * (y * 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 <= -1.7e-42)
		tmp = Float64(Float64(k * y5) * Float64(y * i));
	elseif (i <= -1.28e-244)
		tmp = Float64(k * Float64(y4 * Float64(y1 * y2)));
	elseif (i <= 4.2e-48)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (i <= 1.5e+108)
		tmp = Float64(i * Float64(k * Float64(y * 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 <= -1.7e-42)
		tmp = (k * y5) * (y * i);
	elseif (i <= -1.28e-244)
		tmp = k * (y4 * (y1 * y2));
	elseif (i <= 4.2e-48)
		tmp = b * (k * (z * y0));
	elseif (i <= 1.5e+108)
		tmp = i * (k * (y * 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, -1.7e-42], N[(N[(k * y5), $MachinePrecision] * N[(y * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -1.28e-244], N[(k * N[(y4 * N[(y1 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 4.2e-48], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.5e+108], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if i < -1.70000000000000011e-42

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 53.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 53.0%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 53.0%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 53.0%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 53.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 53.0%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 53.0%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 53.0%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 53.0%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y5 around -inf 42.4%

      \[\leadsto \color{blue}{k \cdot \left(y5 \cdot \left(i \cdot y - y0 \cdot y2\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 40.9%

         \[\leadsto \color{blue}{\left(k \cdot y5\right) \cdot \left(i \cdot y - y0 \cdot y2\right)} \]

      2. *-commutative 40.9%

         \[\leadsto \left(k \cdot y5\right) \cdot \left(i \cdot y - \color{blue}{y2 \cdot y0}\right) \]

   7. Simplified 40.9%

      \[\leadsto \color{blue}{\left(k \cdot y5\right) \cdot \left(i \cdot y - y2 \cdot y0\right)} \]

   8. Taylor expanded in i around inf 34.4%

      \[\leadsto \left(k \cdot y5\right) \cdot \color{blue}{\left(i \cdot y\right)} \]
   9. Step-by-step derivation

      1. *-commutative 34.4%

         \[\leadsto \left(k \cdot y5\right) \cdot \color{blue}{\left(y \cdot i\right)} \]

   10. Simplified 34.4%

       \[\leadsto \left(k \cdot y5\right) \cdot \color{blue}{\left(y \cdot i\right)} \]

   if -1.70000000000000011e-42 < i < -1.27999999999999994e-244

   1. Initial program 19.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 38.3%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 38.3%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 38.3%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 38.3%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 38.3%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 38.3%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 45.7%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in y1 around inf 28.6%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 35.3%

         \[\leadsto k \cdot \color{blue}{\left(\left(y1 \cdot y2\right) \cdot y4\right)} \]

      2. *-commutative 35.3%

         \[\leadsto k \cdot \left(\color{blue}{\left(y2 \cdot y1\right)} \cdot y4\right) \]

      3. *-commutative 35.3%

         \[\leadsto k \cdot \color{blue}{\left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   8. Simplified 35.3%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(y2 \cdot y1\right)\right)} \]

   if -1.27999999999999994e-244 < i < 4.19999999999999977e-48

   1. Initial program 29.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 45.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 45.6%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 45.6%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 45.6%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 45.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 45.6%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 45.6%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 45.6%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 45.6%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 36.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 36.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 36.8%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 36.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 36.8%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 36.8%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 36.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 28.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 4.19999999999999977e-48 < i < 1.49999999999999992e108

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 33.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 33.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 33.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 33.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 33.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 33.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 33.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 33.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 34.1%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 28.0%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]

   if 1.49999999999999992e108 < i

   1. Initial program 15.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 33.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 33.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 33.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 45.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 43.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.4%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 47.5%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 47.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 56.1%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

      5. *-commutative 56.1%

         \[\leadsto j \cdot \left(y1 \cdot \color{blue}{\left(i \cdot x\right)}\right) \]

   8. Simplified 56.1%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(i \cdot x\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 35.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -1.7 \cdot 10^{-42}:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i\right)\\ \mathbf{elif}\;i \leq -1.28 \cdot 10^{-244}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2\right)\right)\\ \mathbf{elif}\;i \leq 4.2 \cdot 10^{-48}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;i \leq 1.5 \cdot 10^{+108}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \end{array} \]

Alternative 29: 21.4% accurate, 7.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -2.4 \cdot 10^{+174}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;x \leq -7.5 \cdot 10^{+54} \lor \neg \left(x \leq 1.3 \cdot 10^{+34}\right):\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -2.4e+174)
   (* a (* b (* x y)))
   (if (or (<= x -7.5e+54) (not (<= x 1.3e+34)))
     (* c (* x (* y0 y2)))
     (* a (* t (* y2 y5))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -2.4e+174) {
		tmp = a * (b * (x * y));
	} else if ((x <= -7.5e+54) || !(x <= 1.3e+34)) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (x <= (-2.4d+174)) then
        tmp = a * (b * (x * y))
    else if ((x <= (-7.5d+54)) .or. (.not. (x <= 1.3d+34))) then
        tmp = c * (x * (y0 * y2))
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -2.4e+174) {
		tmp = a * (b * (x * y));
	} else if ((x <= -7.5e+54) || !(x <= 1.3e+34)) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if x <= -2.4e+174:
		tmp = a * (b * (x * y))
	elif (x <= -7.5e+54) or not (x <= 1.3e+34):
		tmp = c * (x * (y0 * y2))
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (x <= -2.4e+174)
		tmp = Float64(a * Float64(b * Float64(x * y)));
	elseif ((x <= -7.5e+54) || !(x <= 1.3e+34))
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (x <= -2.4e+174)
		tmp = a * (b * (x * y));
	elseif ((x <= -7.5e+54) || ~((x <= 1.3e+34)))
		tmp = c * (x * (y0 * y2));
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[x, -2.4e+174], N[(a * N[(b * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, -7.5e+54], N[Not[LessEqual[x, 1.3e+34]], $MachinePrecision]], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if x < -2.3999999999999998e174

   1. Initial program 15.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 44.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 55.2%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 55.2%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 55.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 55.2%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 55.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 55.2%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 55.2%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   6. Taylor expanded in y around inf 44.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 44.4%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(y \cdot x\right)}\right) \]

   8. Simplified 44.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(y \cdot x\right)\right)} \]

   if -2.3999999999999998e174 < x < -7.50000000000000042e54 or 1.29999999999999999e34 < x

   1. Initial program 18.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 28.4%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 28.4%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 28.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 35.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]

   if -7.50000000000000042e54 < x < 1.29999999999999999e34

   1. Initial program 32.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 31.4%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 31.4%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 31.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 27.2%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 23.6%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 23.6%

         \[\leadsto a \cdot \color{blue}{\left(\left(y2 \cdot y5\right) \cdot t\right)} \]

   8. Simplified 23.6%

      \[\leadsto \color{blue}{a \cdot \left(\left(y2 \cdot y5\right) \cdot t\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 30.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2.4 \cdot 10^{+174}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;x \leq -7.5 \cdot 10^{+54} \lor \neg \left(x \leq 1.3 \cdot 10^{+34}\right):\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]

Alternative 30: 22.2% accurate, 7.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -6.1 \cdot 10^{+172}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{+55} \lor \neg \left(x \leq 5 \cdot 10^{+33}\right):\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -6.1e+172)
   (* a (* b (* x y)))
   (if (or (<= x -1.8e+55) (not (<= x 5e+33)))
     (* c (* y2 (* x y0)))
     (* a (* t (* y2 y5))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -6.1e+172) {
		tmp = a * (b * (x * y));
	} else if ((x <= -1.8e+55) || !(x <= 5e+33)) {
		tmp = c * (y2 * (x * y0));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (x <= (-6.1d+172)) then
        tmp = a * (b * (x * y))
    else if ((x <= (-1.8d+55)) .or. (.not. (x <= 5d+33))) then
        tmp = c * (y2 * (x * y0))
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -6.1e+172) {
		tmp = a * (b * (x * y));
	} else if ((x <= -1.8e+55) || !(x <= 5e+33)) {
		tmp = c * (y2 * (x * y0));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if x <= -6.1e+172:
		tmp = a * (b * (x * y))
	elif (x <= -1.8e+55) or not (x <= 5e+33):
		tmp = c * (y2 * (x * y0))
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (x <= -6.1e+172)
		tmp = Float64(a * Float64(b * Float64(x * y)));
	elseif ((x <= -1.8e+55) || !(x <= 5e+33))
		tmp = Float64(c * Float64(y2 * Float64(x * y0)));
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (x <= -6.1e+172)
		tmp = a * (b * (x * y));
	elseif ((x <= -1.8e+55) || ~((x <= 5e+33)))
		tmp = c * (y2 * (x * y0));
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[x, -6.1e+172], N[(a * N[(b * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, -1.8e+55], N[Not[LessEqual[x, 5e+33]], $MachinePrecision]], N[(c * N[(y2 * N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if x < -6.0999999999999998e172

   1. Initial program 15.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 44.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 55.2%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 55.2%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 55.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 55.2%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 55.2%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 55.2%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 55.2%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   6. Taylor expanded in y around inf 44.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 44.4%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(y \cdot x\right)}\right) \]

   8. Simplified 44.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(y \cdot x\right)\right)} \]

   if -6.0999999999999998e172 < x < -1.79999999999999994e55 or 4.99999999999999973e33 < x

   1. Initial program 18.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 28.4%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 28.4%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 28.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around 0 42.0%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   6. Taylor expanded in c around inf 35.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 37.2%

         \[\leadsto c \cdot \color{blue}{\left(\left(x \cdot y0\right) \cdot y2\right)} \]

   8. Simplified 37.2%

      \[\leadsto \color{blue}{c \cdot \left(\left(x \cdot y0\right) \cdot y2\right)} \]

   if -1.79999999999999994e55 < x < 4.99999999999999973e33

   1. Initial program 32.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 31.4%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 31.4%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 31.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 27.2%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 23.6%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 23.6%

         \[\leadsto a \cdot \color{blue}{\left(\left(y2 \cdot y5\right) \cdot t\right)} \]

   8. Simplified 23.6%

      \[\leadsto \color{blue}{a \cdot \left(\left(y2 \cdot y5\right) \cdot t\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 30.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -6.1 \cdot 10^{+172}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;x \leq -1.8 \cdot 10^{+55} \lor \neg \left(x \leq 5 \cdot 10^{+33}\right):\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]

Alternative 31: 19.6% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -4.9 \cdot 10^{+110}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;x \leq -5.5 \cdot 10^{-76}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -4.9e+110)
   (* a (* b (* x y)))
   (if (<= x -5.5e-76) (* b (* k (* z y0))) (* a (* t (* y2 y5))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -4.9e+110) {
		tmp = a * (b * (x * y));
	} else if (x <= -5.5e-76) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (x <= (-4.9d+110)) then
        tmp = a * (b * (x * y))
    else if (x <= (-5.5d-76)) then
        tmp = b * (k * (z * y0))
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -4.9e+110) {
		tmp = a * (b * (x * y));
	} else if (x <= -5.5e-76) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if x <= -4.9e+110:
		tmp = a * (b * (x * y))
	elif x <= -5.5e-76:
		tmp = b * (k * (z * y0))
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (x <= -4.9e+110)
		tmp = Float64(a * Float64(b * Float64(x * y)));
	elseif (x <= -5.5e-76)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (x <= -4.9e+110)
		tmp = a * (b * (x * y));
	elseif (x <= -5.5e-76)
		tmp = b * (k * (z * y0));
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[x, -4.9e+110], N[(a * N[(b * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -5.5e-76], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if x < -4.90000000000000002e110

   1. Initial program 10.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 34.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 46.3%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 46.3%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 46.3%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 46.3%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 46.3%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 46.3%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 46.3%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   6. Taylor expanded in y around inf 41.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 41.2%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(y \cdot x\right)}\right) \]

   8. Simplified 41.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(y \cdot x\right)\right)} \]

   if -4.90000000000000002e110 < x < -5.50000000000000014e-76

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 45.2%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 45.2%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 45.2%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 45.2%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 45.2%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 45.2%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 45.2%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 45.2%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 45.2%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 35.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 35.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 35.8%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 35.8%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 35.8%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 35.8%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 35.8%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 41.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if -5.50000000000000014e-76 < x

   1. Initial program 29.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 29.2%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 29.2%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 29.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 23.2%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 21.5%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 21.5%

         \[\leadsto a \cdot \color{blue}{\left(\left(y2 \cdot y5\right) \cdot t\right)} \]

   8. Simplified 21.5%

      \[\leadsto \color{blue}{a \cdot \left(\left(y2 \cdot y5\right) \cdot t\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 28.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -4.9 \cdot 10^{+110}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{elif}\;x \leq -5.5 \cdot 10^{-76}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]

Alternative 32: 19.0% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq -6.8 \cdot 10^{-203}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 9.5 \cdot 10^{+161}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= k -6.8e-203)
   (* i (* k (* y y5)))
   (if (<= k 9.5e+161) (* i (* j (* x y1))) (* b (* k (* z y0))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -6.8e-203) {
		tmp = i * (k * (y * y5));
	} else if (k <= 9.5e+161) {
		tmp = i * (j * (x * y1));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (k <= (-6.8d-203)) then
        tmp = i * (k * (y * y5))
    else if (k <= 9.5d+161) then
        tmp = i * (j * (x * y1))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -6.8e-203) {
		tmp = i * (k * (y * y5));
	} else if (k <= 9.5e+161) {
		tmp = i * (j * (x * y1));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if k <= -6.8e-203:
		tmp = i * (k * (y * y5))
	elif k <= 9.5e+161:
		tmp = i * (j * (x * y1))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (k <= -6.8e-203)
		tmp = Float64(i * Float64(k * Float64(y * y5)));
	elseif (k <= 9.5e+161)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (k <= -6.8e-203)
		tmp = i * (k * (y * y5));
	elseif (k <= 9.5e+161)
		tmp = i * (j * (x * y1));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[k, -6.8e-203], N[(i * N[(k * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 9.5e+161], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if k < -6.7999999999999998e-203

   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. Taylor expanded in k around -inf 39.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 39.4%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 39.4%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 39.4%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 39.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 39.4%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 39.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 39.4%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 39.4%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 38.6%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 28.0%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]

   if -6.7999999999999998e-203 < k < 9.50000000000000061e161

   1. Initial program 29.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 44.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 44.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 44.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 44.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 44.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 44.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 34.2%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 27.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if 9.50000000000000061e161 < k

   1. Initial program 16.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 56.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 56.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 56.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 56.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 56.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 56.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 56.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 56.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 56.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 41.1%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 41.1%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 41.1%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 41.1%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 41.1%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 41.1%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 41.1%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 35.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 29.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -6.8 \cdot 10^{-203}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 9.5 \cdot 10^{+161}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]

Alternative 33: 19.2% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq -6 \cdot 10^{-203}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;k \leq 1.15 \cdot 10^{+162}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= k -6e-203)
   (* i (* y5 (* y k)))
   (if (<= k 1.15e+162) (* i (* j (* x y1))) (* b (* k (* z y0))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -6e-203) {
		tmp = i * (y5 * (y * k));
	} else if (k <= 1.15e+162) {
		tmp = i * (j * (x * y1));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (k <= (-6d-203)) then
        tmp = i * (y5 * (y * k))
    else if (k <= 1.15d+162) then
        tmp = i * (j * (x * y1))
    else
        tmp = b * (k * (z * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -6e-203) {
		tmp = i * (y5 * (y * k));
	} else if (k <= 1.15e+162) {
		tmp = i * (j * (x * y1));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if k <= -6e-203:
		tmp = i * (y5 * (y * k))
	elif k <= 1.15e+162:
		tmp = i * (j * (x * y1))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (k <= -6e-203)
		tmp = Float64(i * Float64(y5 * Float64(y * k)));
	elseif (k <= 1.15e+162)
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (k <= -6e-203)
		tmp = i * (y5 * (y * k));
	elseif (k <= 1.15e+162)
		tmp = i * (j * (x * y1));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[k, -6e-203], N[(i * N[(y5 * N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.15e+162], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if k < -6.0000000000000002e-203

   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. Taylor expanded in k around -inf 39.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 39.4%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 39.4%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 39.4%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 39.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 39.4%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 39.4%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 39.4%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 39.4%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in z around 0 38.6%

      \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \cdot \left(-k\right) \]

   6. Taylor expanded in i around inf 28.0%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 29.0%

         \[\leadsto i \cdot \color{blue}{\left(\left(k \cdot y\right) \cdot y5\right)} \]

   8. Simplified 29.0%

      \[\leadsto \color{blue}{i \cdot \left(\left(k \cdot y\right) \cdot y5\right)} \]

   if -6.0000000000000002e-203 < k < 1.14999999999999997e162

   1. Initial program 29.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 44.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 44.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 44.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 44.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 44.0%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 44.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 34.2%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   6. Taylor expanded in i around inf 27.4%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]

   if 1.14999999999999997e162 < k

   1. Initial program 16.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in k around -inf 56.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
   3. Step-by-step derivation

      1. mul-1-neg 56.8%

         \[\leadsto \color{blue}{-k \cdot \left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

      2. *-commutative 56.8%

         \[\leadsto -\color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot k} \]

      3. distribute-rgt-neg-in 56.8%

         \[\leadsto \color{blue}{\left(\left(-1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

      4. +-commutative 56.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      5. mul-1-neg 56.8%

         \[\leadsto \left(\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      6. unsub-neg 56.8%

         \[\leadsto \left(\color{blue}{\left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

      7. *-commutative 56.8%

         \[\leadsto \left(\left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right) \]

   4. Simplified 56.8%

      \[\leadsto \color{blue}{\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \cdot \left(-k\right)} \]

   5. Taylor expanded in y0 around -inf 41.1%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot z\right) + y2 \cdot y5\right)\right)} \cdot \left(-k\right) \]
   6. Step-by-step derivation

      1. +-commutative 41.1%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 + -1 \cdot \left(b \cdot z\right)\right)}\right) \cdot \left(-k\right) \]

      2. mul-1-neg 41.1%

         \[\leadsto \left(y0 \cdot \left(y2 \cdot y5 + \color{blue}{\left(-b \cdot z\right)}\right)\right) \cdot \left(-k\right) \]

      3. unsub-neg 41.1%

         \[\leadsto \left(y0 \cdot \color{blue}{\left(y2 \cdot y5 - b \cdot z\right)}\right) \cdot \left(-k\right) \]

      4. *-commutative 41.1%

         \[\leadsto \left(y0 \cdot \left(\color{blue}{y5 \cdot y2} - b \cdot z\right)\right) \cdot \left(-k\right) \]

      5. *-commutative 41.1%

         \[\leadsto \left(y0 \cdot \left(y5 \cdot y2 - \color{blue}{z \cdot b}\right)\right) \cdot \left(-k\right) \]

   7. Simplified 41.1%

      \[\leadsto \color{blue}{\left(y0 \cdot \left(y5 \cdot y2 - z \cdot b\right)\right)} \cdot \left(-k\right) \]

   8. Taylor expanded in y5 around 0 35.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 29.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -6 \cdot 10^{-203}:\\ \;\;\;\;i \cdot \left(y5 \cdot \left(y \cdot k\right)\right)\\ \mathbf{elif}\;k \leq 1.15 \cdot 10^{+162}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]

Alternative 34: 19.6% accurate, 10.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -1.75 \cdot 10^{+56}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= x -1.75e+56) (* a (* b (* x y))) (* a (* t (* y2 y5)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -1.75e+56) {
		tmp = a * (b * (x * y));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (x <= (-1.75d+56)) then
        tmp = a * (b * (x * y))
    else
        tmp = a * (t * (y2 * y5))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (x <= -1.75e+56) {
		tmp = a * (b * (x * y));
	} else {
		tmp = a * (t * (y2 * y5));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if x <= -1.75e+56:
		tmp = a * (b * (x * y))
	else:
		tmp = a * (t * (y2 * y5))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (x <= -1.75e+56)
		tmp = Float64(a * Float64(b * Float64(x * y)));
	else
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (x <= -1.75e+56)
		tmp = a * (b * (x * y));
	else
		tmp = a * (t * (y2 * y5));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[x, -1.75e+56], N[(a * N[(b * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < -1.75e56

   1. Initial program 15.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in x around inf 39.5%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   3. Taylor expanded in a around inf 36.3%

      \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 36.3%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

      2. +-commutative 36.3%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

      3. mul-1-neg 36.3%

         \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

      4. sub-neg 36.3%

         \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

      5. *-commutative 36.3%

         \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

   5. Simplified 36.3%

      \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

   6. Taylor expanded in y around inf 32.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 32.8%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(y \cdot x\right)}\right) \]

   8. Simplified 32.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(y \cdot x\right)\right)} \]

   if -1.75e56 < x

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 30.8%

      \[\leadsto \color{blue}{y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   3. Step-by-step derivation

      1. *-commutative 30.8%

         \[\leadsto y2 \cdot \left(\color{blue}{\left(c \cdot y0 - a \cdot y1\right) \cdot x} - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Simplified 30.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot x - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Taylor expanded in t around inf 24.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   6. Taylor expanded in a around inf 22.4%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 22.4%

         \[\leadsto a \cdot \color{blue}{\left(\left(y2 \cdot y5\right) \cdot t\right)} \]

   8. Simplified 22.4%

      \[\leadsto \color{blue}{a \cdot \left(\left(y2 \cdot y5\right) \cdot t\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 25.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.75 \cdot 10^{+56}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \end{array} \]

Alternative 35: 17.0% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(b \cdot \left(x \cdot y\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* b (* x y))))

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 * (b * (x * y));
}

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 * (b * (x * y))
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 * (b * (x * y));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (b * (x * y))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(b * Float64(x * y)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (b * (x * y));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(b * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 25.1%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in x around inf 35.9%

   \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

3. Taylor expanded in a around inf 26.8%

   \[\leadsto \color{blue}{a \cdot \left(x \cdot \left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right)\right)} \]
4. Step-by-step derivation

   1. *-commutative 26.8%

      \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y2\right) + b \cdot y\right) \cdot x\right)} \]

   2. +-commutative 26.8%

      \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y + -1 \cdot \left(y1 \cdot y2\right)\right)} \cdot x\right) \]

   3. mul-1-neg 26.8%

      \[\leadsto a \cdot \left(\left(b \cdot y + \color{blue}{\left(-y1 \cdot y2\right)}\right) \cdot x\right) \]

   4. sub-neg 26.8%

      \[\leadsto a \cdot \left(\color{blue}{\left(b \cdot y - y1 \cdot y2\right)} \cdot x\right) \]

   5. *-commutative 26.8%

      \[\leadsto a \cdot \left(\left(\color{blue}{y \cdot b} - y1 \cdot y2\right) \cdot x\right) \]

5. Simplified 26.8%

   \[\leadsto \color{blue}{a \cdot \left(\left(y \cdot b - y1 \cdot y2\right) \cdot x\right)} \]

6. Taylor expanded in y around inf 15.6%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
7. Step-by-step derivation

   1. *-commutative 15.6%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(y \cdot x\right)}\right) \]

8. Simplified 15.6%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(y \cdot x\right)\right)} \]

9. Final simplification 15.6%

   \[\leadsto a \cdot \left(b \cdot \left(x \cdot y\right)\right) \]

Developer target: 28.3% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t_9\\ t_11 := t_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t_4 \cdot t_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t_3 \cdot t_1 - t_14\right)\right) + \left(t_8 - \left(t_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t_13\right)\right) + \left(t_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t_10 - \left(y \cdot x - z \cdot t\right) \cdot t_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t_8 - \left(t_11 - t_6\right)\right) - \left(\frac{t_3}{\frac{1}{t_1}} - t_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t_2 - \left(t_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t_5\right) - t_17 \cdot t_1\right) + t_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2023335 
(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)))))