Diagrams.Solve.Polynomial:cubForm from diagrams-solve-0.1, E

Percentage Accurate: 85.5% → 92.0%

Time: 33.0s

Alternatives: 24

Speedup: 0.9×

• 50.8% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (-
  (-
   (+ (- (* (* (* (* x 18.0) y) z) t) (* (* a 4.0) t)) (* b c))
   (* (* x 4.0) i))
  (* (* j 27.0) k)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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
    code = (((((((x * 18.0d0) * y) * z) * t) - ((a * 4.0d0) * t)) + (b * c)) - ((x * 4.0d0) * i)) - ((j * 27.0d0) * k)
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) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * 18.0) * y) * z) * t) - Float64(Float64(a * 4.0) * t)) + Float64(b * c)) - Float64(Float64(x * 4.0) * i)) - Float64(Float64(j * 27.0) * k))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k)
	tmp = (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := N[(N[(N[(N[(N[(N[(N[(N[(x * 18.0), $MachinePrecision] * y), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision] - N[(N[(a * 4.0), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(b * c), $MachinePrecision]), $MachinePrecision] - N[(N[(x * 4.0), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision]

Initial Program: 85.5% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (-
  (-
   (+ (- (* (* (* (* x 18.0) y) z) t) (* (* a 4.0) t)) (* b c))
   (* (* x 4.0) i))
  (* (* j 27.0) k)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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
    code = (((((((x * 18.0d0) * y) * z) * t) - ((a * 4.0d0) * t)) + (b * c)) - ((x * 4.0d0) * i)) - ((j * 27.0d0) * k)
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) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * 18.0) * y) * z) * t) - Float64(Float64(a * 4.0) * t)) + Float64(b * c)) - Float64(Float64(x * 4.0) * i)) - Float64(Float64(j * 27.0) * k))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k)
	tmp = (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := N[(N[(N[(N[(N[(N[(N[(N[(x * 18.0), $MachinePrecision] * y), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision] - N[(N[(a * 4.0), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(b * c), $MachinePrecision]), $MachinePrecision] - N[(N[(x * 4.0), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision]

Alternative 1: 92.0% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := \left(\left(b \cdot c - \left(t \cdot \left(a \cdot 4\right) - \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t\right)\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{if}\;t\_1 \leq \infty:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1
         (-
          (-
           (- (* b c) (- (* t (* a 4.0)) (* (* (* (* x 18.0) y) z) t)))
           (* (* x 4.0) i))
          (* (* j 27.0) k))))
   (if (<= t_1 INFINITY) t_1 (* x (+ (* (* 18.0 t) (* y z)) (* i -4.0))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (((b * c) - ((t * (a * 4.0)) - ((((x * 18.0) * y) * z) * t))) - ((x * 4.0) * i)) - ((j * 27.0) * k);
	double tmp;
	if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	}
	return tmp;
}

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = (((b * c) - ((t * (a * 4.0)) - ((((x * 18.0) * y) * z) * t))) - ((x * 4.0) * i)) - ((j * 27.0) * k);
	double tmp;
	if (t_1 <= Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (((b * c) - ((t * (a * 4.0)) - ((((x * 18.0) * y) * z) * t))) - ((x * 4.0) * i)) - ((j * 27.0) * k)
	tmp = 0
	if t_1 <= math.inf:
		tmp = t_1
	else:
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(Float64(Float64(b * c) - Float64(Float64(t * Float64(a * 4.0)) - Float64(Float64(Float64(Float64(x * 18.0) * y) * z) * t))) - Float64(Float64(x * 4.0) * i)) - Float64(Float64(j * 27.0) * k))
	tmp = 0.0
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(x * Float64(Float64(Float64(18.0 * t) * Float64(y * z)) + Float64(i * -4.0)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (((b * c) - ((t * (a * 4.0)) - ((((x * 18.0) * y) * z) * t))) - ((x * 4.0) * i)) - ((j * 27.0) * k);
	tmp = 0.0;
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(N[(N[(b * c), $MachinePrecision] - N[(N[(t * N[(a * 4.0), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(N[(x * 18.0), $MachinePrecision] * y), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(x * 4.0), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, Infinity], t$95$1, N[(x * N[(N[(N[(18.0 * t), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] + N[(i * -4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if (-.f64 (-.f64 (+.f64 (-.f64 (*.f64 (*.f64 (*.f64 (*.f64 x 18) y) z) t) (*.f64 (*.f64 a 4) t)) (*.f64 b c)) (*.f64 (*.f64 x 4) i)) (*.f64 (*.f64 j 27) k)) < +inf.0

   1. Initial program 99.1%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   if +inf.0 < (-.f64 (-.f64 (+.f64 (-.f64 (*.f64 (*.f64 (*.f64 (*.f64 x 18) y) z) t) (*.f64 (*.f64 a 4) t)) (*.f64 b c)) (*.f64 (*.f64 x 4) i)) (*.f64 (*.f64 j 27) k))

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 15.0%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 15.0%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 0.0%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 5.0%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 5.0%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 5.0%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 5.0%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in x around inf 70.2%

      \[\leadsto \color{blue}{x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)} \]
   8. Step-by-step derivation

      1. cancel-sign-sub-inv 70.2%

         \[\leadsto x \cdot \color{blue}{\left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) + \left(-4\right) \cdot i\right)} \]

      2. associate-*r* 70.2%

         \[\leadsto x \cdot \left(\color{blue}{\left(18 \cdot t\right) \cdot \left(y \cdot z\right)} + \left(-4\right) \cdot i\right) \]

      3. metadata-eval 70.2%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{-4} \cdot i\right) \]

      4. *-commutative 70.2%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{i \cdot -4}\right) \]

   9. Simplified 70.2%

      \[\leadsto \color{blue}{x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 96.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(b \cdot c - \left(t \cdot \left(a \cdot 4\right) - \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t\right)\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \leq \infty:\\ \;\;\;\;\left(\left(b \cdot c - \left(t \cdot \left(a \cdot 4\right) - \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t\right)\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 46.2% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := t\_1 + -4 \cdot \left(x \cdot i\right)\\ t_3 := b \cdot c - x \cdot \left(4 \cdot i\right)\\ t_4 := t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ t_5 := -4 \cdot \left(t \cdot a\right) + t\_1\\ \mathbf{if}\;t \leq -1.1 \cdot 10^{+221}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;t \leq -2.56 \cdot 10^{+64}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;t \leq -4.5 \cdot 10^{-81}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;t \leq -1.45 \cdot 10^{-120}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-198}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq -9.8 \cdot 10^{-250}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-241}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.2 \cdot 10^{-173}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + t\_1\\ \mathbf{elif}\;t \leq 8.8 \cdot 10^{+79}:\\ \;\;\;\;t\_4\\ \mathbf{else}:\\ \;\;\;\;t\_5\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0)))
        (t_2 (+ t_1 (* -4.0 (* x i))))
        (t_3 (- (* b c) (* x (* 4.0 i))))
        (t_4 (* t (* z (* 18.0 (* x y)))))
        (t_5 (+ (* -4.0 (* t a)) t_1)))
   (if (<= t -1.1e+221)
     t_5
     (if (<= t -2.56e+64)
       t_4
       (if (<= t -4.5e-81)
         t_5
         (if (<= t -1.45e-120)
           t_3
           (if (<= t -2.5e-198)
             t_2
             (if (<= t -9.8e-250)
               t_3
               (if (<= t 1.8e-241)
                 t_2
                 (if (<= t 2.2e-173)
                   t_3
                   (if (<= t 2.05e-69)
                     (+ (* b c) t_1)
                     (if (<= t 8.8e+79) t_4 t_5))))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = t_1 + (-4.0 * (x * i));
	double t_3 = (b * c) - (x * (4.0 * i));
	double t_4 = t * (z * (18.0 * (x * y)));
	double t_5 = (-4.0 * (t * a)) + t_1;
	double tmp;
	if (t <= -1.1e+221) {
		tmp = t_5;
	} else if (t <= -2.56e+64) {
		tmp = t_4;
	} else if (t <= -4.5e-81) {
		tmp = t_5;
	} else if (t <= -1.45e-120) {
		tmp = t_3;
	} else if (t <= -2.5e-198) {
		tmp = t_2;
	} else if (t <= -9.8e-250) {
		tmp = t_3;
	} else if (t <= 1.8e-241) {
		tmp = t_2;
	} else if (t <= 2.2e-173) {
		tmp = t_3;
	} else if (t <= 2.05e-69) {
		tmp = (b * c) + t_1;
	} else if (t <= 8.8e+79) {
		tmp = t_4;
	} else {
		tmp = t_5;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = t_1 + ((-4.0d0) * (x * i))
    t_3 = (b * c) - (x * (4.0d0 * i))
    t_4 = t * (z * (18.0d0 * (x * y)))
    t_5 = ((-4.0d0) * (t * a)) + t_1
    if (t <= (-1.1d+221)) then
        tmp = t_5
    else if (t <= (-2.56d+64)) then
        tmp = t_4
    else if (t <= (-4.5d-81)) then
        tmp = t_5
    else if (t <= (-1.45d-120)) then
        tmp = t_3
    else if (t <= (-2.5d-198)) then
        tmp = t_2
    else if (t <= (-9.8d-250)) then
        tmp = t_3
    else if (t <= 1.8d-241) then
        tmp = t_2
    else if (t <= 2.2d-173) then
        tmp = t_3
    else if (t <= 2.05d-69) then
        tmp = (b * c) + t_1
    else if (t <= 8.8d+79) then
        tmp = t_4
    else
        tmp = t_5
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = j * (k * -27.0);
	double t_2 = t_1 + (-4.0 * (x * i));
	double t_3 = (b * c) - (x * (4.0 * i));
	double t_4 = t * (z * (18.0 * (x * y)));
	double t_5 = (-4.0 * (t * a)) + t_1;
	double tmp;
	if (t <= -1.1e+221) {
		tmp = t_5;
	} else if (t <= -2.56e+64) {
		tmp = t_4;
	} else if (t <= -4.5e-81) {
		tmp = t_5;
	} else if (t <= -1.45e-120) {
		tmp = t_3;
	} else if (t <= -2.5e-198) {
		tmp = t_2;
	} else if (t <= -9.8e-250) {
		tmp = t_3;
	} else if (t <= 1.8e-241) {
		tmp = t_2;
	} else if (t <= 2.2e-173) {
		tmp = t_3;
	} else if (t <= 2.05e-69) {
		tmp = (b * c) + t_1;
	} else if (t <= 8.8e+79) {
		tmp = t_4;
	} else {
		tmp = t_5;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = t_1 + (-4.0 * (x * i))
	t_3 = (b * c) - (x * (4.0 * i))
	t_4 = t * (z * (18.0 * (x * y)))
	t_5 = (-4.0 * (t * a)) + t_1
	tmp = 0
	if t <= -1.1e+221:
		tmp = t_5
	elif t <= -2.56e+64:
		tmp = t_4
	elif t <= -4.5e-81:
		tmp = t_5
	elif t <= -1.45e-120:
		tmp = t_3
	elif t <= -2.5e-198:
		tmp = t_2
	elif t <= -9.8e-250:
		tmp = t_3
	elif t <= 1.8e-241:
		tmp = t_2
	elif t <= 2.2e-173:
		tmp = t_3
	elif t <= 2.05e-69:
		tmp = (b * c) + t_1
	elif t <= 8.8e+79:
		tmp = t_4
	else:
		tmp = t_5
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(t_1 + Float64(-4.0 * Float64(x * i)))
	t_3 = Float64(Float64(b * c) - Float64(x * Float64(4.0 * i)))
	t_4 = Float64(t * Float64(z * Float64(18.0 * Float64(x * y))))
	t_5 = Float64(Float64(-4.0 * Float64(t * a)) + t_1)
	tmp = 0.0
	if (t <= -1.1e+221)
		tmp = t_5;
	elseif (t <= -2.56e+64)
		tmp = t_4;
	elseif (t <= -4.5e-81)
		tmp = t_5;
	elseif (t <= -1.45e-120)
		tmp = t_3;
	elseif (t <= -2.5e-198)
		tmp = t_2;
	elseif (t <= -9.8e-250)
		tmp = t_3;
	elseif (t <= 1.8e-241)
		tmp = t_2;
	elseif (t <= 2.2e-173)
		tmp = t_3;
	elseif (t <= 2.05e-69)
		tmp = Float64(Float64(b * c) + t_1);
	elseif (t <= 8.8e+79)
		tmp = t_4;
	else
		tmp = t_5;
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = t_1 + (-4.0 * (x * i));
	t_3 = (b * c) - (x * (4.0 * i));
	t_4 = t * (z * (18.0 * (x * y)));
	t_5 = (-4.0 * (t * a)) + t_1;
	tmp = 0.0;
	if (t <= -1.1e+221)
		tmp = t_5;
	elseif (t <= -2.56e+64)
		tmp = t_4;
	elseif (t <= -4.5e-81)
		tmp = t_5;
	elseif (t <= -1.45e-120)
		tmp = t_3;
	elseif (t <= -2.5e-198)
		tmp = t_2;
	elseif (t <= -9.8e-250)
		tmp = t_3;
	elseif (t <= 1.8e-241)
		tmp = t_2;
	elseif (t <= 2.2e-173)
		tmp = t_3;
	elseif (t <= 2.05e-69)
		tmp = (b * c) + t_1;
	elseif (t <= 8.8e+79)
		tmp = t_4;
	else
		tmp = t_5;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 + N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(b * c), $MachinePrecision] - N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t * N[(z * N[(18.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, If[LessEqual[t, -1.1e+221], t$95$5, If[LessEqual[t, -2.56e+64], t$95$4, If[LessEqual[t, -4.5e-81], t$95$5, If[LessEqual[t, -1.45e-120], t$95$3, If[LessEqual[t, -2.5e-198], t$95$2, If[LessEqual[t, -9.8e-250], t$95$3, If[LessEqual[t, 1.8e-241], t$95$2, If[LessEqual[t, 2.2e-173], t$95$3, If[LessEqual[t, 2.05e-69], N[(N[(b * c), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[t, 8.8e+79], t$95$4, t$95$5]]]]]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -1.1e221 or -2.56000000000000009e64 < t < -4.5e-81 or 8.7999999999999996e79 < t

   1. Initial program 91.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 95.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in a around inf 64.3%

      \[\leadsto \color{blue}{-4 \cdot \left(a \cdot t\right)} + j \cdot \left(k \cdot -27\right) \]
   6. Step-by-step derivation

      1. *-commutative 64.3%

         \[\leadsto -4 \cdot \color{blue}{\left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   7. Simplified 64.3%

      \[\leadsto \color{blue}{-4 \cdot \left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   if -1.1e221 < t < -2.56000000000000009e64 or 2.04999999999999995e-69 < t < 8.7999999999999996e79

   1. Initial program 90.4%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 88.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 88.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 88.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 88.7%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 88.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 88.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 88.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 90.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 90.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 90.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 90.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 90.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 90.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 58.9%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 58.9%

         \[\leadsto \color{blue}{\left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot 18} \]

      2. associate-*l* 58.9%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot \left(y \cdot z\right)\right) \cdot 18\right)} \]

      3. *-commutative 58.9%

         \[\leadsto t \cdot \color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

      4. associate-*r* 58.9%

         \[\leadsto t \cdot \color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \]

      5. associate-*r* 60.7%

         \[\leadsto t \cdot \color{blue}{\left(\left(\left(18 \cdot x\right) \cdot y\right) \cdot z\right)} \]

      6. *-commutative 60.7%

         \[\leadsto t \cdot \left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot y\right) \cdot z\right) \]

   9. Simplified 60.7%

      \[\leadsto \color{blue}{t \cdot \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \]

   10. Taylor expanded in x around 0 60.7%

       \[\leadsto t \cdot \left(\color{blue}{\left(18 \cdot \left(x \cdot y\right)\right)} \cdot z\right) \]

   if -4.5e-81 < t < -1.45e-120 or -2.5e-198 < t < -9.79999999999999941e-250 or 1.7999999999999999e-241 < t < 2.1999999999999999e-173

   1. Initial program 91.2%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 87.0%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 90.2%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in i around inf 84.1%

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

      1. associate-*r* 84.1%

         \[\leadsto b \cdot c - \color{blue}{\left(4 \cdot i\right) \cdot x} \]

      2. *-commutative 84.1%

         \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   8. Simplified 84.1%

      \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   if -1.45e-120 < t < -2.5e-198 or -9.79999999999999941e-250 < t < 1.7999999999999999e-241

   1. Initial program 96.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 96.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in i around inf 77.9%

      \[\leadsto \color{blue}{-4 \cdot \left(i \cdot x\right)} + j \cdot \left(k \cdot -27\right) \]

   if 2.1999999999999999e-173 < t < 2.04999999999999995e-69

   1. Initial program 82.1%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 82.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in b around inf 82.0%

      \[\leadsto \color{blue}{b \cdot c} + j \cdot \left(k \cdot -27\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 71.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.1 \cdot 10^{+221}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq -2.56 \cdot 10^{+64}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;t \leq -4.5 \cdot 10^{-81}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq -1.45 \cdot 10^{-120}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-198}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -9.8 \cdot 10^{-250}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-241}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq 2.2 \cdot 10^{-173}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 8.8 \cdot 10^{+79}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 46.2% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := b \cdot c - x \cdot \left(4 \cdot i\right)\\ t_3 := t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ t_4 := -4 \cdot \left(t \cdot a\right) + t\_1\\ \mathbf{if}\;t \leq -2.2 \cdot 10^{+221}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{+63}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -1.4 \cdot 10^{-80}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-120}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq -2.15 \cdot 10^{-200}:\\ \;\;\;\;t\_1 + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-250}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{-242}:\\ \;\;\;\;\left(x \cdot i\right) \cdot \left(-4\right) - 27 \cdot \left(j \cdot k\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-173}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 1.95 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + t\_1\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{+80}:\\ \;\;\;\;t\_3\\ \mathbf{else}:\\ \;\;\;\;t\_4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0)))
        (t_2 (- (* b c) (* x (* 4.0 i))))
        (t_3 (* t (* z (* 18.0 (* x y)))))
        (t_4 (+ (* -4.0 (* t a)) t_1)))
   (if (<= t -2.2e+221)
     t_4
     (if (<= t -1.7e+63)
       t_3
       (if (<= t -1.4e-80)
         t_4
         (if (<= t -1.7e-120)
           t_2
           (if (<= t -2.15e-200)
             (+ t_1 (* -4.0 (* x i)))
             (if (<= t -9e-250)
               t_2
               (if (<= t 2.5e-242)
                 (- (* (* x i) (- 4.0)) (* 27.0 (* j k)))
                 (if (<= t 2e-173)
                   t_2
                   (if (<= t 1.95e-69)
                     (+ (* b c) t_1)
                     (if (<= t 2.7e+80) t_3 t_4))))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = (b * c) - (x * (4.0 * i));
	double t_3 = t * (z * (18.0 * (x * y)));
	double t_4 = (-4.0 * (t * a)) + t_1;
	double tmp;
	if (t <= -2.2e+221) {
		tmp = t_4;
	} else if (t <= -1.7e+63) {
		tmp = t_3;
	} else if (t <= -1.4e-80) {
		tmp = t_4;
	} else if (t <= -1.7e-120) {
		tmp = t_2;
	} else if (t <= -2.15e-200) {
		tmp = t_1 + (-4.0 * (x * i));
	} else if (t <= -9e-250) {
		tmp = t_2;
	} else if (t <= 2.5e-242) {
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	} else if (t <= 2e-173) {
		tmp = t_2;
	} else if (t <= 1.95e-69) {
		tmp = (b * c) + t_1;
	} else if (t <= 2.7e+80) {
		tmp = t_3;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = (b * c) - (x * (4.0d0 * i))
    t_3 = t * (z * (18.0d0 * (x * y)))
    t_4 = ((-4.0d0) * (t * a)) + t_1
    if (t <= (-2.2d+221)) then
        tmp = t_4
    else if (t <= (-1.7d+63)) then
        tmp = t_3
    else if (t <= (-1.4d-80)) then
        tmp = t_4
    else if (t <= (-1.7d-120)) then
        tmp = t_2
    else if (t <= (-2.15d-200)) then
        tmp = t_1 + ((-4.0d0) * (x * i))
    else if (t <= (-9d-250)) then
        tmp = t_2
    else if (t <= 2.5d-242) then
        tmp = ((x * i) * -4.0d0) - (27.0d0 * (j * k))
    else if (t <= 2d-173) then
        tmp = t_2
    else if (t <= 1.95d-69) then
        tmp = (b * c) + t_1
    else if (t <= 2.7d+80) then
        tmp = t_3
    else
        tmp = t_4
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = j * (k * -27.0);
	double t_2 = (b * c) - (x * (4.0 * i));
	double t_3 = t * (z * (18.0 * (x * y)));
	double t_4 = (-4.0 * (t * a)) + t_1;
	double tmp;
	if (t <= -2.2e+221) {
		tmp = t_4;
	} else if (t <= -1.7e+63) {
		tmp = t_3;
	} else if (t <= -1.4e-80) {
		tmp = t_4;
	} else if (t <= -1.7e-120) {
		tmp = t_2;
	} else if (t <= -2.15e-200) {
		tmp = t_1 + (-4.0 * (x * i));
	} else if (t <= -9e-250) {
		tmp = t_2;
	} else if (t <= 2.5e-242) {
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	} else if (t <= 2e-173) {
		tmp = t_2;
	} else if (t <= 1.95e-69) {
		tmp = (b * c) + t_1;
	} else if (t <= 2.7e+80) {
		tmp = t_3;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = (b * c) - (x * (4.0 * i))
	t_3 = t * (z * (18.0 * (x * y)))
	t_4 = (-4.0 * (t * a)) + t_1
	tmp = 0
	if t <= -2.2e+221:
		tmp = t_4
	elif t <= -1.7e+63:
		tmp = t_3
	elif t <= -1.4e-80:
		tmp = t_4
	elif t <= -1.7e-120:
		tmp = t_2
	elif t <= -2.15e-200:
		tmp = t_1 + (-4.0 * (x * i))
	elif t <= -9e-250:
		tmp = t_2
	elif t <= 2.5e-242:
		tmp = ((x * i) * -4.0) - (27.0 * (j * k))
	elif t <= 2e-173:
		tmp = t_2
	elif t <= 1.95e-69:
		tmp = (b * c) + t_1
	elif t <= 2.7e+80:
		tmp = t_3
	else:
		tmp = t_4
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(Float64(b * c) - Float64(x * Float64(4.0 * i)))
	t_3 = Float64(t * Float64(z * Float64(18.0 * Float64(x * y))))
	t_4 = Float64(Float64(-4.0 * Float64(t * a)) + t_1)
	tmp = 0.0
	if (t <= -2.2e+221)
		tmp = t_4;
	elseif (t <= -1.7e+63)
		tmp = t_3;
	elseif (t <= -1.4e-80)
		tmp = t_4;
	elseif (t <= -1.7e-120)
		tmp = t_2;
	elseif (t <= -2.15e-200)
		tmp = Float64(t_1 + Float64(-4.0 * Float64(x * i)));
	elseif (t <= -9e-250)
		tmp = t_2;
	elseif (t <= 2.5e-242)
		tmp = Float64(Float64(Float64(x * i) * Float64(-4.0)) - Float64(27.0 * Float64(j * k)));
	elseif (t <= 2e-173)
		tmp = t_2;
	elseif (t <= 1.95e-69)
		tmp = Float64(Float64(b * c) + t_1);
	elseif (t <= 2.7e+80)
		tmp = t_3;
	else
		tmp = t_4;
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = (b * c) - (x * (4.0 * i));
	t_3 = t * (z * (18.0 * (x * y)));
	t_4 = (-4.0 * (t * a)) + t_1;
	tmp = 0.0;
	if (t <= -2.2e+221)
		tmp = t_4;
	elseif (t <= -1.7e+63)
		tmp = t_3;
	elseif (t <= -1.4e-80)
		tmp = t_4;
	elseif (t <= -1.7e-120)
		tmp = t_2;
	elseif (t <= -2.15e-200)
		tmp = t_1 + (-4.0 * (x * i));
	elseif (t <= -9e-250)
		tmp = t_2;
	elseif (t <= 2.5e-242)
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	elseif (t <= 2e-173)
		tmp = t_2;
	elseif (t <= 1.95e-69)
		tmp = (b * c) + t_1;
	elseif (t <= 2.7e+80)
		tmp = t_3;
	else
		tmp = t_4;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * c), $MachinePrecision] - N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t * N[(z * N[(18.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, If[LessEqual[t, -2.2e+221], t$95$4, If[LessEqual[t, -1.7e+63], t$95$3, If[LessEqual[t, -1.4e-80], t$95$4, If[LessEqual[t, -1.7e-120], t$95$2, If[LessEqual[t, -2.15e-200], N[(t$95$1 + N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -9e-250], t$95$2, If[LessEqual[t, 2.5e-242], N[(N[(N[(x * i), $MachinePrecision] * (-4.0)), $MachinePrecision] - N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2e-173], t$95$2, If[LessEqual[t, 1.95e-69], N[(N[(b * c), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[t, 2.7e+80], t$95$3, t$95$4]]]]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -2.1999999999999999e221 or -1.6999999999999999e63 < t < -1.39999999999999995e-80 or 2.69999999999999983e80 < t

   1. Initial program 91.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 95.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in a around inf 64.3%

      \[\leadsto \color{blue}{-4 \cdot \left(a \cdot t\right)} + j \cdot \left(k \cdot -27\right) \]
   6. Step-by-step derivation

      1. *-commutative 64.3%

         \[\leadsto -4 \cdot \color{blue}{\left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   7. Simplified 64.3%

      \[\leadsto \color{blue}{-4 \cdot \left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   if -2.1999999999999999e221 < t < -1.6999999999999999e63 or 1.9499999999999999e-69 < t < 2.69999999999999983e80

   1. Initial program 90.4%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 88.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 88.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 88.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 88.7%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 88.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 88.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 88.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 90.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 90.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 90.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 90.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 90.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 90.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 58.9%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 58.9%

         \[\leadsto \color{blue}{\left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot 18} \]

      2. associate-*l* 58.9%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot \left(y \cdot z\right)\right) \cdot 18\right)} \]

      3. *-commutative 58.9%

         \[\leadsto t \cdot \color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

      4. associate-*r* 58.9%

         \[\leadsto t \cdot \color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \]

      5. associate-*r* 60.7%

         \[\leadsto t \cdot \color{blue}{\left(\left(\left(18 \cdot x\right) \cdot y\right) \cdot z\right)} \]

      6. *-commutative 60.7%

         \[\leadsto t \cdot \left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot y\right) \cdot z\right) \]

   9. Simplified 60.7%

      \[\leadsto \color{blue}{t \cdot \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \]

   10. Taylor expanded in x around 0 60.7%

       \[\leadsto t \cdot \left(\color{blue}{\left(18 \cdot \left(x \cdot y\right)\right)} \cdot z\right) \]

   if -1.39999999999999995e-80 < t < -1.70000000000000005e-120 or -2.14999999999999987e-200 < t < -8.99999999999999987e-250 or 2.4999999999999999e-242 < t < 2.0000000000000001e-173

   1. Initial program 91.2%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 87.0%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 90.2%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in i around inf 84.1%

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

      1. associate-*r* 84.1%

         \[\leadsto b \cdot c - \color{blue}{\left(4 \cdot i\right) \cdot x} \]

      2. *-commutative 84.1%

         \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   8. Simplified 84.1%

      \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   if -1.70000000000000005e-120 < t < -2.14999999999999987e-200

   1. Initial program 99.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in i around inf 74.3%

      \[\leadsto \color{blue}{-4 \cdot \left(i \cdot x\right)} + j \cdot \left(k \cdot -27\right) \]

   if -8.99999999999999987e-250 < t < 2.4999999999999999e-242

   1. Initial program 94.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 94.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 97.1%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in b around 0 79.6%

      \[\leadsto \color{blue}{-1 \cdot \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   if 2.0000000000000001e-173 < t < 1.9499999999999999e-69

   1. Initial program 82.1%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 82.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in b around inf 82.0%

      \[\leadsto \color{blue}{b \cdot c} + j \cdot \left(k \cdot -27\right) \]
3. Recombined 6 regimes into one program.

4. Final simplification 71.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.2 \cdot 10^{+221}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{+63}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;t \leq -1.4 \cdot 10^{-80}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-120}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq -2.15 \cdot 10^{-200}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-250}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{-242}:\\ \;\;\;\;\left(x \cdot i\right) \cdot \left(-4\right) - 27 \cdot \left(j \cdot k\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-173}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 1.95 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{+80}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 56.5% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := b \cdot c - x \cdot \left(4 \cdot i\right)\\ t_3 := t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{if}\;t \leq -1 \cdot 10^{-7}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-79}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + t\_1\\ \mathbf{elif}\;t \leq -1.36 \cdot 10^{-120}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq -6.1 \cdot 10^{-199}:\\ \;\;\;\;t\_1 + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -8.8 \cdot 10^{-250}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{-243}:\\ \;\;\;\;\left(x \cdot i\right) \cdot \left(-4\right) - 27 \cdot \left(j \cdot k\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{-157}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.2 \cdot 10^{+90}:\\ \;\;\;\;t\_1 + \left(18 \cdot t\right) \cdot \left(z \cdot \left(x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_3\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0)))
        (t_2 (- (* b c) (* x (* 4.0 i))))
        (t_3 (* t (- (* 18.0 (* x (* y z))) (* a 4.0)))))
   (if (<= t -1e-7)
     t_3
     (if (<= t -9e-79)
       (+ (* -4.0 (* t a)) t_1)
       (if (<= t -1.36e-120)
         t_2
         (if (<= t -6.1e-199)
           (+ t_1 (* -4.0 (* x i)))
           (if (<= t -8.8e-250)
             t_2
             (if (<= t 2.7e-243)
               (- (* (* x i) (- 4.0)) (* 27.0 (* j k)))
               (if (<= t 3.6e-157)
                 t_2
                 (if (<= t 2.2e+90)
                   (+ t_1 (* (* 18.0 t) (* z (* x y))))
                   t_3))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = (b * c) - (x * (4.0 * i));
	double t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	double tmp;
	if (t <= -1e-7) {
		tmp = t_3;
	} else if (t <= -9e-79) {
		tmp = (-4.0 * (t * a)) + t_1;
	} else if (t <= -1.36e-120) {
		tmp = t_2;
	} else if (t <= -6.1e-199) {
		tmp = t_1 + (-4.0 * (x * i));
	} else if (t <= -8.8e-250) {
		tmp = t_2;
	} else if (t <= 2.7e-243) {
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	} else if (t <= 3.6e-157) {
		tmp = t_2;
	} else if (t <= 2.2e+90) {
		tmp = t_1 + ((18.0 * t) * (z * (x * y)));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = (b * c) - (x * (4.0d0 * i))
    t_3 = t * ((18.0d0 * (x * (y * z))) - (a * 4.0d0))
    if (t <= (-1d-7)) then
        tmp = t_3
    else if (t <= (-9d-79)) then
        tmp = ((-4.0d0) * (t * a)) + t_1
    else if (t <= (-1.36d-120)) then
        tmp = t_2
    else if (t <= (-6.1d-199)) then
        tmp = t_1 + ((-4.0d0) * (x * i))
    else if (t <= (-8.8d-250)) then
        tmp = t_2
    else if (t <= 2.7d-243) then
        tmp = ((x * i) * -4.0d0) - (27.0d0 * (j * k))
    else if (t <= 3.6d-157) then
        tmp = t_2
    else if (t <= 2.2d+90) then
        tmp = t_1 + ((18.0d0 * t) * (z * (x * y)))
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = j * (k * -27.0);
	double t_2 = (b * c) - (x * (4.0 * i));
	double t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	double tmp;
	if (t <= -1e-7) {
		tmp = t_3;
	} else if (t <= -9e-79) {
		tmp = (-4.0 * (t * a)) + t_1;
	} else if (t <= -1.36e-120) {
		tmp = t_2;
	} else if (t <= -6.1e-199) {
		tmp = t_1 + (-4.0 * (x * i));
	} else if (t <= -8.8e-250) {
		tmp = t_2;
	} else if (t <= 2.7e-243) {
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	} else if (t <= 3.6e-157) {
		tmp = t_2;
	} else if (t <= 2.2e+90) {
		tmp = t_1 + ((18.0 * t) * (z * (x * y)));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = (b * c) - (x * (4.0 * i))
	t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0))
	tmp = 0
	if t <= -1e-7:
		tmp = t_3
	elif t <= -9e-79:
		tmp = (-4.0 * (t * a)) + t_1
	elif t <= -1.36e-120:
		tmp = t_2
	elif t <= -6.1e-199:
		tmp = t_1 + (-4.0 * (x * i))
	elif t <= -8.8e-250:
		tmp = t_2
	elif t <= 2.7e-243:
		tmp = ((x * i) * -4.0) - (27.0 * (j * k))
	elif t <= 3.6e-157:
		tmp = t_2
	elif t <= 2.2e+90:
		tmp = t_1 + ((18.0 * t) * (z * (x * y)))
	else:
		tmp = t_3
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(Float64(b * c) - Float64(x * Float64(4.0 * i)))
	t_3 = Float64(t * Float64(Float64(18.0 * Float64(x * Float64(y * z))) - Float64(a * 4.0)))
	tmp = 0.0
	if (t <= -1e-7)
		tmp = t_3;
	elseif (t <= -9e-79)
		tmp = Float64(Float64(-4.0 * Float64(t * a)) + t_1);
	elseif (t <= -1.36e-120)
		tmp = t_2;
	elseif (t <= -6.1e-199)
		tmp = Float64(t_1 + Float64(-4.0 * Float64(x * i)));
	elseif (t <= -8.8e-250)
		tmp = t_2;
	elseif (t <= 2.7e-243)
		tmp = Float64(Float64(Float64(x * i) * Float64(-4.0)) - Float64(27.0 * Float64(j * k)));
	elseif (t <= 3.6e-157)
		tmp = t_2;
	elseif (t <= 2.2e+90)
		tmp = Float64(t_1 + Float64(Float64(18.0 * t) * Float64(z * Float64(x * y))));
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = (b * c) - (x * (4.0 * i));
	t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	tmp = 0.0;
	if (t <= -1e-7)
		tmp = t_3;
	elseif (t <= -9e-79)
		tmp = (-4.0 * (t * a)) + t_1;
	elseif (t <= -1.36e-120)
		tmp = t_2;
	elseif (t <= -6.1e-199)
		tmp = t_1 + (-4.0 * (x * i));
	elseif (t <= -8.8e-250)
		tmp = t_2;
	elseif (t <= 2.7e-243)
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	elseif (t <= 3.6e-157)
		tmp = t_2;
	elseif (t <= 2.2e+90)
		tmp = t_1 + ((18.0 * t) * (z * (x * y)));
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * c), $MachinePrecision] - N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t * N[(N[(18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1e-7], t$95$3, If[LessEqual[t, -9e-79], N[(N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[t, -1.36e-120], t$95$2, If[LessEqual[t, -6.1e-199], N[(t$95$1 + N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -8.8e-250], t$95$2, If[LessEqual[t, 2.7e-243], N[(N[(N[(x * i), $MachinePrecision] * (-4.0)), $MachinePrecision] - N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.6e-157], t$95$2, If[LessEqual[t, 2.2e+90], N[(t$95$1 + N[(N[(18.0 * t), $MachinePrecision] * N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -9.9999999999999995e-8 or 2.1999999999999999e90 < t

   1. Initial program 87.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 89.2%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around inf 73.9%

      \[\leadsto \color{blue}{t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - 4 \cdot a\right)} \]

   if -9.9999999999999995e-8 < t < -9.0000000000000006e-79

   1. Initial program 99.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in a around inf 81.3%

      \[\leadsto \color{blue}{-4 \cdot \left(a \cdot t\right)} + j \cdot \left(k \cdot -27\right) \]
   6. Step-by-step derivation

      1. *-commutative 81.3%

         \[\leadsto -4 \cdot \color{blue}{\left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   7. Simplified 81.3%

      \[\leadsto \color{blue}{-4 \cdot \left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   if -9.0000000000000006e-79 < t < -1.36000000000000001e-120 or -6.0999999999999999e-199 < t < -8.8e-250 or 2.7000000000000001e-243 < t < 3.6e-157

   1. Initial program 90.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 86.8%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 89.6%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in i around inf 82.5%

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

      1. associate-*r* 82.5%

         \[\leadsto b \cdot c - \color{blue}{\left(4 \cdot i\right) \cdot x} \]

      2. *-commutative 82.5%

         \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   8. Simplified 82.5%

      \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   if -1.36000000000000001e-120 < t < -6.0999999999999999e-199

   1. Initial program 99.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in i around inf 74.3%

      \[\leadsto \color{blue}{-4 \cdot \left(i \cdot x\right)} + j \cdot \left(k \cdot -27\right) \]

   if -8.8e-250 < t < 2.7000000000000001e-243

   1. Initial program 94.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 94.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 97.1%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in b around 0 79.6%

      \[\leadsto \color{blue}{-1 \cdot \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   if 3.6e-157 < t < 2.1999999999999999e90

   1. Initial program 93.1%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 88.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around inf 66.2%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} + j \cdot \left(k \cdot -27\right) \]
   6. Step-by-step derivation

      1. associate-*r* 66.2%

         \[\leadsto \color{blue}{\left(18 \cdot t\right) \cdot \left(x \cdot \left(y \cdot z\right)\right)} + j \cdot \left(k \cdot -27\right) \]

      2. associate-*r* 70.6%

         \[\leadsto \left(18 \cdot t\right) \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot z\right)} + j \cdot \left(k \cdot -27\right) \]

   7. Simplified 70.6%

      \[\leadsto \color{blue}{\left(18 \cdot t\right) \cdot \left(\left(x \cdot y\right) \cdot z\right)} + j \cdot \left(k \cdot -27\right) \]
3. Recombined 6 regimes into one program.

4. Final simplification 76.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1 \cdot 10^{-7}:\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{elif}\;t \leq -9 \cdot 10^{-79}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq -1.36 \cdot 10^{-120}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq -6.1 \cdot 10^{-199}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -8.8 \cdot 10^{-250}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{-243}:\\ \;\;\;\;\left(x \cdot i\right) \cdot \left(-4\right) - 27 \cdot \left(j \cdot k\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{-157}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 2.2 \cdot 10^{+90}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + \left(18 \cdot t\right) \cdot \left(z \cdot \left(x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 36.9% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := -4 \cdot \left(x \cdot i\right)\\ t_2 := \left(j \cdot k\right) \cdot -27\\ \mathbf{if}\;b \cdot c \leq -1.7 \cdot 10^{+69}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -3 \cdot 10^{+27}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq -9.5 \cdot 10^{-68}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;b \cdot c \leq -4.6 \cdot 10^{-259}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq 0.0138:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;b \cdot c \leq 1.95 \cdot 10^{+100}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq 5.8 \cdot 10^{+128}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* -4.0 (* x i))) (t_2 (* (* j k) -27.0)))
   (if (<= (* b c) -1.7e+69)
     (* b c)
     (if (<= (* b c) -3e+27)
       t_1
       (if (<= (* b c) -9.5e-68)
         t_2
         (if (<= (* b c) -4.6e-259)
           t_1
           (if (<= (* b c) 0.0138)
             t_2
             (if (<= (* b c) 1.95e+100)
               t_1
               (if (<= (* b c) 5.8e+128) t_2 (* b c))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = -4.0 * (x * i);
	double t_2 = (j * k) * -27.0;
	double tmp;
	if ((b * c) <= -1.7e+69) {
		tmp = b * c;
	} else if ((b * c) <= -3e+27) {
		tmp = t_1;
	} else if ((b * c) <= -9.5e-68) {
		tmp = t_2;
	} else if ((b * c) <= -4.6e-259) {
		tmp = t_1;
	} else if ((b * c) <= 0.0138) {
		tmp = t_2;
	} else if ((b * c) <= 1.95e+100) {
		tmp = t_1;
	} else if ((b * c) <= 5.8e+128) {
		tmp = t_2;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (-4.0d0) * (x * i)
    t_2 = (j * k) * (-27.0d0)
    if ((b * c) <= (-1.7d+69)) then
        tmp = b * c
    else if ((b * c) <= (-3d+27)) then
        tmp = t_1
    else if ((b * c) <= (-9.5d-68)) then
        tmp = t_2
    else if ((b * c) <= (-4.6d-259)) then
        tmp = t_1
    else if ((b * c) <= 0.0138d0) then
        tmp = t_2
    else if ((b * c) <= 1.95d+100) then
        tmp = t_1
    else if ((b * c) <= 5.8d+128) then
        tmp = t_2
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = -4.0 * (x * i);
	double t_2 = (j * k) * -27.0;
	double tmp;
	if ((b * c) <= -1.7e+69) {
		tmp = b * c;
	} else if ((b * c) <= -3e+27) {
		tmp = t_1;
	} else if ((b * c) <= -9.5e-68) {
		tmp = t_2;
	} else if ((b * c) <= -4.6e-259) {
		tmp = t_1;
	} else if ((b * c) <= 0.0138) {
		tmp = t_2;
	} else if ((b * c) <= 1.95e+100) {
		tmp = t_1;
	} else if ((b * c) <= 5.8e+128) {
		tmp = t_2;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = -4.0 * (x * i)
	t_2 = (j * k) * -27.0
	tmp = 0
	if (b * c) <= -1.7e+69:
		tmp = b * c
	elif (b * c) <= -3e+27:
		tmp = t_1
	elif (b * c) <= -9.5e-68:
		tmp = t_2
	elif (b * c) <= -4.6e-259:
		tmp = t_1
	elif (b * c) <= 0.0138:
		tmp = t_2
	elif (b * c) <= 1.95e+100:
		tmp = t_1
	elif (b * c) <= 5.8e+128:
		tmp = t_2
	else:
		tmp = b * c
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(-4.0 * Float64(x * i))
	t_2 = Float64(Float64(j * k) * -27.0)
	tmp = 0.0
	if (Float64(b * c) <= -1.7e+69)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -3e+27)
		tmp = t_1;
	elseif (Float64(b * c) <= -9.5e-68)
		tmp = t_2;
	elseif (Float64(b * c) <= -4.6e-259)
		tmp = t_1;
	elseif (Float64(b * c) <= 0.0138)
		tmp = t_2;
	elseif (Float64(b * c) <= 1.95e+100)
		tmp = t_1;
	elseif (Float64(b * c) <= 5.8e+128)
		tmp = t_2;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = -4.0 * (x * i);
	t_2 = (j * k) * -27.0;
	tmp = 0.0;
	if ((b * c) <= -1.7e+69)
		tmp = b * c;
	elseif ((b * c) <= -3e+27)
		tmp = t_1;
	elseif ((b * c) <= -9.5e-68)
		tmp = t_2;
	elseif ((b * c) <= -4.6e-259)
		tmp = t_1;
	elseif ((b * c) <= 0.0138)
		tmp = t_2;
	elseif ((b * c) <= 1.95e+100)
		tmp = t_1;
	elseif ((b * c) <= 5.8e+128)
		tmp = t_2;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -1.7e+69], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -3e+27], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], -9.5e-68], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], -4.6e-259], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 0.0138], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], 1.95e+100], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 5.8e+128], t$95$2, N[(b * c), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 3 regimes

2. if (*.f64 b c) < -1.69999999999999993e69 or 5.8000000000000001e128 < (*.f64 b c)

   1. Initial program 84.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 84.8%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 84.8%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 84.8%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 84.8%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 84.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 84.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 84.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 84.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 84.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in b around inf 53.0%

      \[\leadsto \color{blue}{b \cdot c} \]

   if -1.69999999999999993e69 < (*.f64 b c) < -2.99999999999999976e27 or -9.4999999999999997e-68 < (*.f64 b c) < -4.5999999999999999e-259 or 0.0138 < (*.f64 b c) < 1.95e100

   1. Initial program 93.4%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.9%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 91.9%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 91.9%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 93.6%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 93.6%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 93.6%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 93.6%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 93.6%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 93.6%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 93.6%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 93.6%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 93.6%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 93.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in i around inf 48.9%

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

      1. *-commutative 48.9%

         \[\leadsto -4 \cdot \color{blue}{\left(x \cdot i\right)} \]

   9. Simplified 48.9%

      \[\leadsto \color{blue}{-4 \cdot \left(x \cdot i\right)} \]

   if -2.99999999999999976e27 < (*.f64 b c) < -9.4999999999999997e-68 or -4.5999999999999999e-259 < (*.f64 b c) < 0.0138 or 1.95e100 < (*.f64 b c) < 5.8000000000000001e128

   1. Initial program 94.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in j around inf 42.2%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 47.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \cdot c \leq -1.7 \cdot 10^{+69}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -3 \cdot 10^{+27}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq -9.5 \cdot 10^{-68}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq -4.6 \cdot 10^{-259}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq 0.0138:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq 1.95 \cdot 10^{+100}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq 5.8 \cdot 10^{+128}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 35.5% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := 18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)\\ t_2 := -4 \cdot \left(x \cdot i\right)\\ \mathbf{if}\;b \cdot c \leq -3.2 \cdot 10^{+293}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -2.9 \cdot 10^{+69}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq -1.2 \cdot 10^{-259}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;b \cdot c \leq -2.05 \cdot 10^{-303}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq 2.2 \cdot 10^{-286}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq 6.2 \cdot 10^{-5}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 8.4 \cdot 10^{+74}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* 18.0 (* t (* x (* y z))))) (t_2 (* -4.0 (* x i))))
   (if (<= (* b c) -3.2e+293)
     (* b c)
     (if (<= (* b c) -2.9e+69)
       t_1
       (if (<= (* b c) -1.2e-259)
         t_2
         (if (<= (* b c) -2.05e-303)
           (* (* j k) -27.0)
           (if (<= (* b c) 2.2e-286)
             t_1
             (if (<= (* b c) 6.2e-5)
               (* j (* k -27.0))
               (if (<= (* b c) 8.4e+74) t_2 (* b c))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = 18.0 * (t * (x * (y * z)));
	double t_2 = -4.0 * (x * i);
	double tmp;
	if ((b * c) <= -3.2e+293) {
		tmp = b * c;
	} else if ((b * c) <= -2.9e+69) {
		tmp = t_1;
	} else if ((b * c) <= -1.2e-259) {
		tmp = t_2;
	} else if ((b * c) <= -2.05e-303) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= 2.2e-286) {
		tmp = t_1;
	} else if ((b * c) <= 6.2e-5) {
		tmp = j * (k * -27.0);
	} else if ((b * c) <= 8.4e+74) {
		tmp = t_2;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = 18.0d0 * (t * (x * (y * z)))
    t_2 = (-4.0d0) * (x * i)
    if ((b * c) <= (-3.2d+293)) then
        tmp = b * c
    else if ((b * c) <= (-2.9d+69)) then
        tmp = t_1
    else if ((b * c) <= (-1.2d-259)) then
        tmp = t_2
    else if ((b * c) <= (-2.05d-303)) then
        tmp = (j * k) * (-27.0d0)
    else if ((b * c) <= 2.2d-286) then
        tmp = t_1
    else if ((b * c) <= 6.2d-5) then
        tmp = j * (k * (-27.0d0))
    else if ((b * c) <= 8.4d+74) then
        tmp = t_2
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = 18.0 * (t * (x * (y * z)));
	double t_2 = -4.0 * (x * i);
	double tmp;
	if ((b * c) <= -3.2e+293) {
		tmp = b * c;
	} else if ((b * c) <= -2.9e+69) {
		tmp = t_1;
	} else if ((b * c) <= -1.2e-259) {
		tmp = t_2;
	} else if ((b * c) <= -2.05e-303) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= 2.2e-286) {
		tmp = t_1;
	} else if ((b * c) <= 6.2e-5) {
		tmp = j * (k * -27.0);
	} else if ((b * c) <= 8.4e+74) {
		tmp = t_2;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = 18.0 * (t * (x * (y * z)))
	t_2 = -4.0 * (x * i)
	tmp = 0
	if (b * c) <= -3.2e+293:
		tmp = b * c
	elif (b * c) <= -2.9e+69:
		tmp = t_1
	elif (b * c) <= -1.2e-259:
		tmp = t_2
	elif (b * c) <= -2.05e-303:
		tmp = (j * k) * -27.0
	elif (b * c) <= 2.2e-286:
		tmp = t_1
	elif (b * c) <= 6.2e-5:
		tmp = j * (k * -27.0)
	elif (b * c) <= 8.4e+74:
		tmp = t_2
	else:
		tmp = b * c
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(18.0 * Float64(t * Float64(x * Float64(y * z))))
	t_2 = Float64(-4.0 * Float64(x * i))
	tmp = 0.0
	if (Float64(b * c) <= -3.2e+293)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -2.9e+69)
		tmp = t_1;
	elseif (Float64(b * c) <= -1.2e-259)
		tmp = t_2;
	elseif (Float64(b * c) <= -2.05e-303)
		tmp = Float64(Float64(j * k) * -27.0);
	elseif (Float64(b * c) <= 2.2e-286)
		tmp = t_1;
	elseif (Float64(b * c) <= 6.2e-5)
		tmp = Float64(j * Float64(k * -27.0));
	elseif (Float64(b * c) <= 8.4e+74)
		tmp = t_2;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = 18.0 * (t * (x * (y * z)));
	t_2 = -4.0 * (x * i);
	tmp = 0.0;
	if ((b * c) <= -3.2e+293)
		tmp = b * c;
	elseif ((b * c) <= -2.9e+69)
		tmp = t_1;
	elseif ((b * c) <= -1.2e-259)
		tmp = t_2;
	elseif ((b * c) <= -2.05e-303)
		tmp = (j * k) * -27.0;
	elseif ((b * c) <= 2.2e-286)
		tmp = t_1;
	elseif ((b * c) <= 6.2e-5)
		tmp = j * (k * -27.0);
	elseif ((b * c) <= 8.4e+74)
		tmp = t_2;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(18.0 * N[(t * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -3.2e+293], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -2.9e+69], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], -1.2e-259], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], -2.05e-303], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 2.2e-286], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 6.2e-5], N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 8.4e+74], t$95$2, N[(b * c), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if (*.f64 b c) < -3.2e293 or 8.3999999999999995e74 < (*.f64 b c)

   1. Initial program 85.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 84.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 84.1%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 84.1%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 84.1%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 84.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 84.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 84.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 84.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 84.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in b around inf 62.6%

      \[\leadsto \color{blue}{b \cdot c} \]

   if -3.2e293 < (*.f64 b c) < -2.8999999999999998e69 or -2.05000000000000009e-303 < (*.f64 b c) < 2.1999999999999999e-286

   1. Initial program 88.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 90.6%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 90.6%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 90.6%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 90.6%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 90.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 90.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 90.6%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 92.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 92.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 92.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 92.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 92.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 92.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 40.1%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

   if -2.8999999999999998e69 < (*.f64 b c) < -1.2e-259 or 6.20000000000000027e-5 < (*.f64 b c) < 8.3999999999999995e74

   1. Initial program 94.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 93.3%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 93.3%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 94.7%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 94.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 94.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 94.7%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 94.7%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 94.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in i around inf 40.7%

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

      1. *-commutative 40.7%

         \[\leadsto -4 \cdot \color{blue}{\left(x \cdot i\right)} \]

   9. Simplified 40.7%

      \[\leadsto \color{blue}{-4 \cdot \left(x \cdot i\right)} \]

   if -1.2e-259 < (*.f64 b c) < -2.05000000000000009e-303

   1. Initial program 84.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 85.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in j around inf 62.4%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]

   if 2.1999999999999999e-286 < (*.f64 b c) < 6.20000000000000027e-5

   1. Initial program 96.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 93.1%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 93.1%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 93.1%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 93.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 93.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 93.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 93.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 93.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in j around inf 48.7%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]
   8. Step-by-step derivation

      1. *-commutative 48.7%

         \[\leadsto \color{blue}{\left(j \cdot k\right) \cdot -27} \]

      2. associate-*r* 48.7%

         \[\leadsto \color{blue}{j \cdot \left(k \cdot -27\right)} \]

   9. Simplified 48.7%

      \[\leadsto \color{blue}{j \cdot \left(k \cdot -27\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 48.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \cdot c \leq -3.2 \cdot 10^{+293}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -2.9 \cdot 10^{+69}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq -1.2 \cdot 10^{-259}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq -2.05 \cdot 10^{-303}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq 2.2 \cdot 10^{-286}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq 6.2 \cdot 10^{-5}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 8.4 \cdot 10^{+74}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 35.5% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := -4 \cdot \left(x \cdot i\right)\\ \mathbf{if}\;b \cdot c \leq -3.2 \cdot 10^{+293}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -3.8 \cdot 10^{+69}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq -1.65 \cdot 10^{-260}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq -1.2 \cdot 10^{-298}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq 1.25 \cdot 10^{-300}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq 0.52:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 1.65 \cdot 10^{+68}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* -4.0 (* x i))))
   (if (<= (* b c) -3.2e+293)
     (* b c)
     (if (<= (* b c) -3.8e+69)
       (* t (* z (* 18.0 (* x y))))
       (if (<= (* b c) -1.65e-260)
         t_1
         (if (<= (* b c) -1.2e-298)
           (* (* j k) -27.0)
           (if (<= (* b c) 1.25e-300)
             (* 18.0 (* t (* x (* y z))))
             (if (<= (* b c) 0.52)
               (* j (* k -27.0))
               (if (<= (* b c) 1.65e+68) t_1 (* b c))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = -4.0 * (x * i);
	double tmp;
	if ((b * c) <= -3.2e+293) {
		tmp = b * c;
	} else if ((b * c) <= -3.8e+69) {
		tmp = t * (z * (18.0 * (x * y)));
	} else if ((b * c) <= -1.65e-260) {
		tmp = t_1;
	} else if ((b * c) <= -1.2e-298) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= 1.25e-300) {
		tmp = 18.0 * (t * (x * (y * z)));
	} else if ((b * c) <= 0.52) {
		tmp = j * (k * -27.0);
	} else if ((b * c) <= 1.65e+68) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (-4.0d0) * (x * i)
    if ((b * c) <= (-3.2d+293)) then
        tmp = b * c
    else if ((b * c) <= (-3.8d+69)) then
        tmp = t * (z * (18.0d0 * (x * y)))
    else if ((b * c) <= (-1.65d-260)) then
        tmp = t_1
    else if ((b * c) <= (-1.2d-298)) then
        tmp = (j * k) * (-27.0d0)
    else if ((b * c) <= 1.25d-300) then
        tmp = 18.0d0 * (t * (x * (y * z)))
    else if ((b * c) <= 0.52d0) then
        tmp = j * (k * (-27.0d0))
    else if ((b * c) <= 1.65d+68) then
        tmp = t_1
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = -4.0 * (x * i);
	double tmp;
	if ((b * c) <= -3.2e+293) {
		tmp = b * c;
	} else if ((b * c) <= -3.8e+69) {
		tmp = t * (z * (18.0 * (x * y)));
	} else if ((b * c) <= -1.65e-260) {
		tmp = t_1;
	} else if ((b * c) <= -1.2e-298) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= 1.25e-300) {
		tmp = 18.0 * (t * (x * (y * z)));
	} else if ((b * c) <= 0.52) {
		tmp = j * (k * -27.0);
	} else if ((b * c) <= 1.65e+68) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = -4.0 * (x * i)
	tmp = 0
	if (b * c) <= -3.2e+293:
		tmp = b * c
	elif (b * c) <= -3.8e+69:
		tmp = t * (z * (18.0 * (x * y)))
	elif (b * c) <= -1.65e-260:
		tmp = t_1
	elif (b * c) <= -1.2e-298:
		tmp = (j * k) * -27.0
	elif (b * c) <= 1.25e-300:
		tmp = 18.0 * (t * (x * (y * z)))
	elif (b * c) <= 0.52:
		tmp = j * (k * -27.0)
	elif (b * c) <= 1.65e+68:
		tmp = t_1
	else:
		tmp = b * c
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(-4.0 * Float64(x * i))
	tmp = 0.0
	if (Float64(b * c) <= -3.2e+293)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -3.8e+69)
		tmp = Float64(t * Float64(z * Float64(18.0 * Float64(x * y))));
	elseif (Float64(b * c) <= -1.65e-260)
		tmp = t_1;
	elseif (Float64(b * c) <= -1.2e-298)
		tmp = Float64(Float64(j * k) * -27.0);
	elseif (Float64(b * c) <= 1.25e-300)
		tmp = Float64(18.0 * Float64(t * Float64(x * Float64(y * z))));
	elseif (Float64(b * c) <= 0.52)
		tmp = Float64(j * Float64(k * -27.0));
	elseif (Float64(b * c) <= 1.65e+68)
		tmp = t_1;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = -4.0 * (x * i);
	tmp = 0.0;
	if ((b * c) <= -3.2e+293)
		tmp = b * c;
	elseif ((b * c) <= -3.8e+69)
		tmp = t * (z * (18.0 * (x * y)));
	elseif ((b * c) <= -1.65e-260)
		tmp = t_1;
	elseif ((b * c) <= -1.2e-298)
		tmp = (j * k) * -27.0;
	elseif ((b * c) <= 1.25e-300)
		tmp = 18.0 * (t * (x * (y * z)));
	elseif ((b * c) <= 0.52)
		tmp = j * (k * -27.0);
	elseif ((b * c) <= 1.65e+68)
		tmp = t_1;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -3.2e+293], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -3.8e+69], N[(t * N[(z * N[(18.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1.65e-260], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], -1.2e-298], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 1.25e-300], N[(18.0 * N[(t * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 0.52], N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 1.65e+68], t$95$1, N[(b * c), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if (*.f64 b c) < -3.2e293 or 1.65e68 < (*.f64 b c)

   1. Initial program 85.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 84.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 84.1%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 84.1%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 84.1%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 84.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 84.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 84.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 84.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 84.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 84.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in b around inf 62.6%

      \[\leadsto \color{blue}{b \cdot c} \]

   if -3.2e293 < (*.f64 b c) < -3.80000000000000028e69

   1. Initial program 87.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.8%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 91.8%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 91.8%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 91.8%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 91.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 91.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 91.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 91.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 91.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 91.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 91.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 91.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 91.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 43.3%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 43.3%

         \[\leadsto \color{blue}{\left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot 18} \]

      2. associate-*l* 43.2%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot \left(y \cdot z\right)\right) \cdot 18\right)} \]

      3. *-commutative 43.2%

         \[\leadsto t \cdot \color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

      4. associate-*r* 43.2%

         \[\leadsto t \cdot \color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \]

      5. associate-*r* 47.0%

         \[\leadsto t \cdot \color{blue}{\left(\left(\left(18 \cdot x\right) \cdot y\right) \cdot z\right)} \]

      6. *-commutative 47.0%

         \[\leadsto t \cdot \left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot y\right) \cdot z\right) \]

   9. Simplified 47.0%

      \[\leadsto \color{blue}{t \cdot \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \]

   10. Taylor expanded in x around 0 47.0%

       \[\leadsto t \cdot \left(\color{blue}{\left(18 \cdot \left(x \cdot y\right)\right)} \cdot z\right) \]

   if -3.80000000000000028e69 < (*.f64 b c) < -1.6499999999999999e-260 or 0.52000000000000002 < (*.f64 b c) < 1.65e68

   1. Initial program 94.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 93.3%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 93.3%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 94.7%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 94.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 94.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 94.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 94.7%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 94.7%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 94.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in i around inf 40.7%

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

      1. *-commutative 40.7%

         \[\leadsto -4 \cdot \color{blue}{\left(x \cdot i\right)} \]

   9. Simplified 40.7%

      \[\leadsto \color{blue}{-4 \cdot \left(x \cdot i\right)} \]

   if -1.6499999999999999e-260 < (*.f64 b c) < -1.19999999999999994e-298

   1. Initial program 84.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 85.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in j around inf 62.4%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]

   if -1.19999999999999994e-298 < (*.f64 b c) < 1.24999999999999999e-300

   1. Initial program 89.4%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 89.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 89.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 89.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 89.7%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 89.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 89.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 89.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 93.0%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 93.0%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 93.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 37.4%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

   if 1.24999999999999999e-300 < (*.f64 b c) < 0.52000000000000002

   1. Initial program 96.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 93.1%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 93.1%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 93.1%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 93.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 93.1%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 93.1%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 93.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 93.1%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 93.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in j around inf 48.7%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]
   8. Step-by-step derivation

      1. *-commutative 48.7%

         \[\leadsto \color{blue}{\left(j \cdot k\right) \cdot -27} \]

      2. associate-*r* 48.7%

         \[\leadsto \color{blue}{j \cdot \left(k \cdot -27\right)} \]

   9. Simplified 48.7%

      \[\leadsto \color{blue}{j \cdot \left(k \cdot -27\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 48.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \cdot c \leq -3.2 \cdot 10^{+293}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -3.8 \cdot 10^{+69}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq -1.65 \cdot 10^{-260}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq -1.2 \cdot 10^{-298}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq 1.25 \cdot 10^{-300}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq 0.52:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 1.65 \cdot 10^{+68}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 57.6% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := b \cdot c - x \cdot \left(4 \cdot i\right)\\ t_3 := t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{if}\;t \leq -1.8 \cdot 10^{-9}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-86}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + t\_1\\ \mathbf{elif}\;t \leq -1.25 \cdot 10^{-120}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq -1.4 \cdot 10^{-196}:\\ \;\;\;\;t\_1 + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-249}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 1.1 \cdot 10^{-240}:\\ \;\;\;\;\left(x \cdot i\right) \cdot \left(-4\right) - 27 \cdot \left(j \cdot k\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{-175}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + t\_1\\ \mathbf{else}:\\ \;\;\;\;t\_3\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0)))
        (t_2 (- (* b c) (* x (* 4.0 i))))
        (t_3 (* t (- (* 18.0 (* x (* y z))) (* a 4.0)))))
   (if (<= t -1.8e-9)
     t_3
     (if (<= t -3.2e-86)
       (+ (* -4.0 (* t a)) t_1)
       (if (<= t -1.25e-120)
         t_2
         (if (<= t -1.4e-196)
           (+ t_1 (* -4.0 (* x i)))
           (if (<= t -1.1e-249)
             t_2
             (if (<= t 1.1e-240)
               (- (* (* x i) (- 4.0)) (* 27.0 (* j k)))
               (if (<= t 9.5e-175)
                 t_2
                 (if (<= t 2.05e-69) (+ (* b c) t_1) t_3))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = (b * c) - (x * (4.0 * i));
	double t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	double tmp;
	if (t <= -1.8e-9) {
		tmp = t_3;
	} else if (t <= -3.2e-86) {
		tmp = (-4.0 * (t * a)) + t_1;
	} else if (t <= -1.25e-120) {
		tmp = t_2;
	} else if (t <= -1.4e-196) {
		tmp = t_1 + (-4.0 * (x * i));
	} else if (t <= -1.1e-249) {
		tmp = t_2;
	} else if (t <= 1.1e-240) {
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	} else if (t <= 9.5e-175) {
		tmp = t_2;
	} else if (t <= 2.05e-69) {
		tmp = (b * c) + t_1;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = (b * c) - (x * (4.0d0 * i))
    t_3 = t * ((18.0d0 * (x * (y * z))) - (a * 4.0d0))
    if (t <= (-1.8d-9)) then
        tmp = t_3
    else if (t <= (-3.2d-86)) then
        tmp = ((-4.0d0) * (t * a)) + t_1
    else if (t <= (-1.25d-120)) then
        tmp = t_2
    else if (t <= (-1.4d-196)) then
        tmp = t_1 + ((-4.0d0) * (x * i))
    else if (t <= (-1.1d-249)) then
        tmp = t_2
    else if (t <= 1.1d-240) then
        tmp = ((x * i) * -4.0d0) - (27.0d0 * (j * k))
    else if (t <= 9.5d-175) then
        tmp = t_2
    else if (t <= 2.05d-69) then
        tmp = (b * c) + t_1
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = j * (k * -27.0);
	double t_2 = (b * c) - (x * (4.0 * i));
	double t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	double tmp;
	if (t <= -1.8e-9) {
		tmp = t_3;
	} else if (t <= -3.2e-86) {
		tmp = (-4.0 * (t * a)) + t_1;
	} else if (t <= -1.25e-120) {
		tmp = t_2;
	} else if (t <= -1.4e-196) {
		tmp = t_1 + (-4.0 * (x * i));
	} else if (t <= -1.1e-249) {
		tmp = t_2;
	} else if (t <= 1.1e-240) {
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	} else if (t <= 9.5e-175) {
		tmp = t_2;
	} else if (t <= 2.05e-69) {
		tmp = (b * c) + t_1;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = (b * c) - (x * (4.0 * i))
	t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0))
	tmp = 0
	if t <= -1.8e-9:
		tmp = t_3
	elif t <= -3.2e-86:
		tmp = (-4.0 * (t * a)) + t_1
	elif t <= -1.25e-120:
		tmp = t_2
	elif t <= -1.4e-196:
		tmp = t_1 + (-4.0 * (x * i))
	elif t <= -1.1e-249:
		tmp = t_2
	elif t <= 1.1e-240:
		tmp = ((x * i) * -4.0) - (27.0 * (j * k))
	elif t <= 9.5e-175:
		tmp = t_2
	elif t <= 2.05e-69:
		tmp = (b * c) + t_1
	else:
		tmp = t_3
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(Float64(b * c) - Float64(x * Float64(4.0 * i)))
	t_3 = Float64(t * Float64(Float64(18.0 * Float64(x * Float64(y * z))) - Float64(a * 4.0)))
	tmp = 0.0
	if (t <= -1.8e-9)
		tmp = t_3;
	elseif (t <= -3.2e-86)
		tmp = Float64(Float64(-4.0 * Float64(t * a)) + t_1);
	elseif (t <= -1.25e-120)
		tmp = t_2;
	elseif (t <= -1.4e-196)
		tmp = Float64(t_1 + Float64(-4.0 * Float64(x * i)));
	elseif (t <= -1.1e-249)
		tmp = t_2;
	elseif (t <= 1.1e-240)
		tmp = Float64(Float64(Float64(x * i) * Float64(-4.0)) - Float64(27.0 * Float64(j * k)));
	elseif (t <= 9.5e-175)
		tmp = t_2;
	elseif (t <= 2.05e-69)
		tmp = Float64(Float64(b * c) + t_1);
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = (b * c) - (x * (4.0 * i));
	t_3 = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	tmp = 0.0;
	if (t <= -1.8e-9)
		tmp = t_3;
	elseif (t <= -3.2e-86)
		tmp = (-4.0 * (t * a)) + t_1;
	elseif (t <= -1.25e-120)
		tmp = t_2;
	elseif (t <= -1.4e-196)
		tmp = t_1 + (-4.0 * (x * i));
	elseif (t <= -1.1e-249)
		tmp = t_2;
	elseif (t <= 1.1e-240)
		tmp = ((x * i) * -4.0) - (27.0 * (j * k));
	elseif (t <= 9.5e-175)
		tmp = t_2;
	elseif (t <= 2.05e-69)
		tmp = (b * c) + t_1;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * c), $MachinePrecision] - N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t * N[(N[(18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.8e-9], t$95$3, If[LessEqual[t, -3.2e-86], N[(N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[t, -1.25e-120], t$95$2, If[LessEqual[t, -1.4e-196], N[(t$95$1 + N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.1e-249], t$95$2, If[LessEqual[t, 1.1e-240], N[(N[(N[(x * i), $MachinePrecision] * (-4.0)), $MachinePrecision] - N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 9.5e-175], t$95$2, If[LessEqual[t, 2.05e-69], N[(N[(b * c), $MachinePrecision] + t$95$1), $MachinePrecision], t$95$3]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -1.8e-9 or 2.04999999999999995e-69 < t

   1. Initial program 90.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 90.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around inf 71.1%

      \[\leadsto \color{blue}{t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - 4 \cdot a\right)} \]

   if -1.8e-9 < t < -3.20000000000000006e-86

   1. Initial program 99.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in a around inf 81.3%

      \[\leadsto \color{blue}{-4 \cdot \left(a \cdot t\right)} + j \cdot \left(k \cdot -27\right) \]
   6. Step-by-step derivation

      1. *-commutative 81.3%

         \[\leadsto -4 \cdot \color{blue}{\left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   7. Simplified 81.3%

      \[\leadsto \color{blue}{-4 \cdot \left(t \cdot a\right)} + j \cdot \left(k \cdot -27\right) \]

   if -3.20000000000000006e-86 < t < -1.25000000000000002e-120 or -1.3999999999999999e-196 < t < -1.1e-249 or 1.1e-240 < t < 9.50000000000000052e-175

   1. Initial program 91.2%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 87.0%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 90.2%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in i around inf 84.1%

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

      1. associate-*r* 84.1%

         \[\leadsto b \cdot c - \color{blue}{\left(4 \cdot i\right) \cdot x} \]

      2. *-commutative 84.1%

         \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   8. Simplified 84.1%

      \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   if -1.25000000000000002e-120 < t < -1.3999999999999999e-196

   1. Initial program 99.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in i around inf 74.3%

      \[\leadsto \color{blue}{-4 \cdot \left(i \cdot x\right)} + j \cdot \left(k \cdot -27\right) \]

   if -1.1e-249 < t < 1.1e-240

   1. Initial program 94.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 94.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 97.1%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in b around 0 79.6%

      \[\leadsto \color{blue}{-1 \cdot \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   if 9.50000000000000052e-175 < t < 2.04999999999999995e-69

   1. Initial program 82.1%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 82.3%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in b around inf 82.0%

      \[\leadsto \color{blue}{b \cdot c} + j \cdot \left(k \cdot -27\right) \]
3. Recombined 6 regimes into one program.

4. Final simplification 76.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.8 \cdot 10^{-9}:\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-86}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq -1.25 \cdot 10^{-120}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq -1.4 \cdot 10^{-196}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-249}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 1.1 \cdot 10^{-240}:\\ \;\;\;\;\left(x \cdot i\right) \cdot \left(-4\right) - 27 \cdot \left(j \cdot k\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{-175}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 45.6% accurate, 0.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := b \cdot c - x \cdot \left(4 \cdot i\right)\\ t_2 := b \cdot c + j \cdot \left(k \cdot -27\right)\\ t_3 := t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{if}\;t \leq -3.5 \cdot 10^{-7}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-90}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{-295}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 10^{-249}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 3.4 \cdot 10^{-239}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq 1.55 \cdot 10^{-175}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{+143}:\\ \;\;\;\;t\_3\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - 4 \cdot \left(t \cdot a\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (- (* b c) (* x (* 4.0 i))))
        (t_2 (+ (* b c) (* j (* k -27.0))))
        (t_3 (* t (* z (* 18.0 (* x y))))))
   (if (<= t -3.5e-7)
     t_3
     (if (<= t -1.1e-90)
       t_2
       (if (<= t 2.4e-295)
         t_1
         (if (<= t 1e-249)
           t_2
           (if (<= t 3.4e-239)
             (* -4.0 (* x i))
             (if (<= t 1.55e-175)
               t_1
               (if (<= t 2.05e-69)
                 t_2
                 (if (<= t 2.6e+143) t_3 (- (* b c) (* 4.0 (* t a)))))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (b * c) - (x * (4.0 * i));
	double t_2 = (b * c) + (j * (k * -27.0));
	double t_3 = t * (z * (18.0 * (x * y)));
	double tmp;
	if (t <= -3.5e-7) {
		tmp = t_3;
	} else if (t <= -1.1e-90) {
		tmp = t_2;
	} else if (t <= 2.4e-295) {
		tmp = t_1;
	} else if (t <= 1e-249) {
		tmp = t_2;
	} else if (t <= 3.4e-239) {
		tmp = -4.0 * (x * i);
	} else if (t <= 1.55e-175) {
		tmp = t_1;
	} else if (t <= 2.05e-69) {
		tmp = t_2;
	} else if (t <= 2.6e+143) {
		tmp = t_3;
	} else {
		tmp = (b * c) - (4.0 * (t * a));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = (b * c) - (x * (4.0d0 * i))
    t_2 = (b * c) + (j * (k * (-27.0d0)))
    t_3 = t * (z * (18.0d0 * (x * y)))
    if (t <= (-3.5d-7)) then
        tmp = t_3
    else if (t <= (-1.1d-90)) then
        tmp = t_2
    else if (t <= 2.4d-295) then
        tmp = t_1
    else if (t <= 1d-249) then
        tmp = t_2
    else if (t <= 3.4d-239) then
        tmp = (-4.0d0) * (x * i)
    else if (t <= 1.55d-175) then
        tmp = t_1
    else if (t <= 2.05d-69) then
        tmp = t_2
    else if (t <= 2.6d+143) then
        tmp = t_3
    else
        tmp = (b * c) - (4.0d0 * (t * a))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = (b * c) - (x * (4.0 * i));
	double t_2 = (b * c) + (j * (k * -27.0));
	double t_3 = t * (z * (18.0 * (x * y)));
	double tmp;
	if (t <= -3.5e-7) {
		tmp = t_3;
	} else if (t <= -1.1e-90) {
		tmp = t_2;
	} else if (t <= 2.4e-295) {
		tmp = t_1;
	} else if (t <= 1e-249) {
		tmp = t_2;
	} else if (t <= 3.4e-239) {
		tmp = -4.0 * (x * i);
	} else if (t <= 1.55e-175) {
		tmp = t_1;
	} else if (t <= 2.05e-69) {
		tmp = t_2;
	} else if (t <= 2.6e+143) {
		tmp = t_3;
	} else {
		tmp = (b * c) - (4.0 * (t * a));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (b * c) - (x * (4.0 * i))
	t_2 = (b * c) + (j * (k * -27.0))
	t_3 = t * (z * (18.0 * (x * y)))
	tmp = 0
	if t <= -3.5e-7:
		tmp = t_3
	elif t <= -1.1e-90:
		tmp = t_2
	elif t <= 2.4e-295:
		tmp = t_1
	elif t <= 1e-249:
		tmp = t_2
	elif t <= 3.4e-239:
		tmp = -4.0 * (x * i)
	elif t <= 1.55e-175:
		tmp = t_1
	elif t <= 2.05e-69:
		tmp = t_2
	elif t <= 2.6e+143:
		tmp = t_3
	else:
		tmp = (b * c) - (4.0 * (t * a))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(b * c) - Float64(x * Float64(4.0 * i)))
	t_2 = Float64(Float64(b * c) + Float64(j * Float64(k * -27.0)))
	t_3 = Float64(t * Float64(z * Float64(18.0 * Float64(x * y))))
	tmp = 0.0
	if (t <= -3.5e-7)
		tmp = t_3;
	elseif (t <= -1.1e-90)
		tmp = t_2;
	elseif (t <= 2.4e-295)
		tmp = t_1;
	elseif (t <= 1e-249)
		tmp = t_2;
	elseif (t <= 3.4e-239)
		tmp = Float64(-4.0 * Float64(x * i));
	elseif (t <= 1.55e-175)
		tmp = t_1;
	elseif (t <= 2.05e-69)
		tmp = t_2;
	elseif (t <= 2.6e+143)
		tmp = t_3;
	else
		tmp = Float64(Float64(b * c) - Float64(4.0 * Float64(t * a)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (b * c) - (x * (4.0 * i));
	t_2 = (b * c) + (j * (k * -27.0));
	t_3 = t * (z * (18.0 * (x * y)));
	tmp = 0.0;
	if (t <= -3.5e-7)
		tmp = t_3;
	elseif (t <= -1.1e-90)
		tmp = t_2;
	elseif (t <= 2.4e-295)
		tmp = t_1;
	elseif (t <= 1e-249)
		tmp = t_2;
	elseif (t <= 3.4e-239)
		tmp = -4.0 * (x * i);
	elseif (t <= 1.55e-175)
		tmp = t_1;
	elseif (t <= 2.05e-69)
		tmp = t_2;
	elseif (t <= 2.6e+143)
		tmp = t_3;
	else
		tmp = (b * c) - (4.0 * (t * a));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(b * c), $MachinePrecision] - N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * c), $MachinePrecision] + N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t * N[(z * N[(18.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.5e-7], t$95$3, If[LessEqual[t, -1.1e-90], t$95$2, If[LessEqual[t, 2.4e-295], t$95$1, If[LessEqual[t, 1e-249], t$95$2, If[LessEqual[t, 3.4e-239], N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.55e-175], t$95$1, If[LessEqual[t, 2.05e-69], t$95$2, If[LessEqual[t, 2.6e+143], t$95$3, N[(N[(b * c), $MachinePrecision] - N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -3.49999999999999984e-7 or 2.04999999999999995e-69 < t < 2.5999999999999999e143

   1. Initial program 88.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 87.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 87.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 87.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 88.8%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 88.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 88.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 88.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 89.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 89.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 89.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 49.8%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 49.8%

         \[\leadsto \color{blue}{\left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot 18} \]

      2. associate-*l* 49.8%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot \left(y \cdot z\right)\right) \cdot 18\right)} \]

      3. *-commutative 49.8%

         \[\leadsto t \cdot \color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

      4. associate-*r* 49.8%

         \[\leadsto t \cdot \color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \]

      5. associate-*r* 51.9%

         \[\leadsto t \cdot \color{blue}{\left(\left(\left(18 \cdot x\right) \cdot y\right) \cdot z\right)} \]

      6. *-commutative 51.9%

         \[\leadsto t \cdot \left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot y\right) \cdot z\right) \]

   9. Simplified 51.9%

      \[\leadsto \color{blue}{t \cdot \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \]

   10. Taylor expanded in x around 0 51.9%

       \[\leadsto t \cdot \left(\color{blue}{\left(18 \cdot \left(x \cdot y\right)\right)} \cdot z\right) \]

   if -3.49999999999999984e-7 < t < -1.09999999999999993e-90 or 2.3999999999999998e-295 < t < 1.00000000000000005e-249 or 1.54999999999999999e-175 < t < 2.04999999999999995e-69

   1. Initial program 89.4%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 89.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in b around inf 74.5%

      \[\leadsto \color{blue}{b \cdot c} + j \cdot \left(k \cdot -27\right) \]

   if -1.09999999999999993e-90 < t < 2.3999999999999998e-295 or 3.4e-239 < t < 1.54999999999999999e-175

   1. Initial program 93.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.4%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 92.1%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   6. Taylor expanded in i around inf 70.9%

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

      1. associate-*r* 70.9%

         \[\leadsto b \cdot c - \color{blue}{\left(4 \cdot i\right) \cdot x} \]

      2. *-commutative 70.9%

         \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   8. Simplified 70.9%

      \[\leadsto b \cdot c - \color{blue}{x \cdot \left(4 \cdot i\right)} \]

   if 1.00000000000000005e-249 < t < 3.4e-239

   1. Initial program 99.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 99.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 99.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 99.7%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 99.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 99.7%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 99.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 99.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 99.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 99.7%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 99.7%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 99.7%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 99.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in i around inf 69.3%

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

      1. *-commutative 69.3%

         \[\leadsto -4 \cdot \color{blue}{\left(x \cdot i\right)} \]

   9. Simplified 69.3%

      \[\leadsto \color{blue}{-4 \cdot \left(x \cdot i\right)} \]

   if 2.5999999999999999e143 < t

   1. Initial program 93.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 72.7%

      \[\leadsto \color{blue}{\left(b \cdot c - 4 \cdot \left(a \cdot t\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   4. Taylor expanded in j around 0 59.3%

      \[\leadsto \color{blue}{b \cdot c - 4 \cdot \left(a \cdot t\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 63.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.5 \cdot 10^{-7}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-90}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{-295}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 10^{-249}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 3.4 \cdot 10^{-239}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;t \leq 1.55 \cdot 10^{-175}:\\ \;\;\;\;b \cdot c - x \cdot \left(4 \cdot i\right)\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{+143}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - 4 \cdot \left(t \cdot a\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 10: 37.0% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := -4 \cdot \left(x \cdot i\right)\\ \mathbf{if}\;b \cdot c \leq -1.7 \cdot 10^{+69}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -2.6 \cdot 10^{+28}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq -1.25 \cdot 10^{-67}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq -1 \cdot 10^{-260}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;b \cdot c \leq 2020000:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 6 \cdot 10^{+68}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* -4.0 (* x i))))
   (if (<= (* b c) -1.7e+69)
     (* b c)
     (if (<= (* b c) -2.6e+28)
       t_1
       (if (<= (* b c) -1.25e-67)
         (* (* j k) -27.0)
         (if (<= (* b c) -1e-260)
           t_1
           (if (<= (* b c) 2020000.0)
             (* j (* k -27.0))
             (if (<= (* b c) 6e+68) t_1 (* b c)))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = -4.0 * (x * i);
	double tmp;
	if ((b * c) <= -1.7e+69) {
		tmp = b * c;
	} else if ((b * c) <= -2.6e+28) {
		tmp = t_1;
	} else if ((b * c) <= -1.25e-67) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= -1e-260) {
		tmp = t_1;
	} else if ((b * c) <= 2020000.0) {
		tmp = j * (k * -27.0);
	} else if ((b * c) <= 6e+68) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (-4.0d0) * (x * i)
    if ((b * c) <= (-1.7d+69)) then
        tmp = b * c
    else if ((b * c) <= (-2.6d+28)) then
        tmp = t_1
    else if ((b * c) <= (-1.25d-67)) then
        tmp = (j * k) * (-27.0d0)
    else if ((b * c) <= (-1d-260)) then
        tmp = t_1
    else if ((b * c) <= 2020000.0d0) then
        tmp = j * (k * (-27.0d0))
    else if ((b * c) <= 6d+68) then
        tmp = t_1
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = -4.0 * (x * i);
	double tmp;
	if ((b * c) <= -1.7e+69) {
		tmp = b * c;
	} else if ((b * c) <= -2.6e+28) {
		tmp = t_1;
	} else if ((b * c) <= -1.25e-67) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= -1e-260) {
		tmp = t_1;
	} else if ((b * c) <= 2020000.0) {
		tmp = j * (k * -27.0);
	} else if ((b * c) <= 6e+68) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = -4.0 * (x * i)
	tmp = 0
	if (b * c) <= -1.7e+69:
		tmp = b * c
	elif (b * c) <= -2.6e+28:
		tmp = t_1
	elif (b * c) <= -1.25e-67:
		tmp = (j * k) * -27.0
	elif (b * c) <= -1e-260:
		tmp = t_1
	elif (b * c) <= 2020000.0:
		tmp = j * (k * -27.0)
	elif (b * c) <= 6e+68:
		tmp = t_1
	else:
		tmp = b * c
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(-4.0 * Float64(x * i))
	tmp = 0.0
	if (Float64(b * c) <= -1.7e+69)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -2.6e+28)
		tmp = t_1;
	elseif (Float64(b * c) <= -1.25e-67)
		tmp = Float64(Float64(j * k) * -27.0);
	elseif (Float64(b * c) <= -1e-260)
		tmp = t_1;
	elseif (Float64(b * c) <= 2020000.0)
		tmp = Float64(j * Float64(k * -27.0));
	elseif (Float64(b * c) <= 6e+68)
		tmp = t_1;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = -4.0 * (x * i);
	tmp = 0.0;
	if ((b * c) <= -1.7e+69)
		tmp = b * c;
	elseif ((b * c) <= -2.6e+28)
		tmp = t_1;
	elseif ((b * c) <= -1.25e-67)
		tmp = (j * k) * -27.0;
	elseif ((b * c) <= -1e-260)
		tmp = t_1;
	elseif ((b * c) <= 2020000.0)
		tmp = j * (k * -27.0);
	elseif ((b * c) <= 6e+68)
		tmp = t_1;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -1.7e+69], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -2.6e+28], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], -1.25e-67], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1e-260], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 2020000.0], N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 6e+68], t$95$1, N[(b * c), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if (*.f64 b c) < -1.69999999999999993e69 or 6.0000000000000004e68 < (*.f64 b c)

   1. Initial program 86.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 86.4%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 86.4%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 86.4%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 86.4%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 86.4%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 86.4%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 86.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 86.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 86.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 86.4%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 86.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 86.4%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 86.4%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in b around inf 51.2%

      \[\leadsto \color{blue}{b \cdot c} \]

   if -1.69999999999999993e69 < (*.f64 b c) < -2.6000000000000002e28 or -1.25e-67 < (*.f64 b c) < -9.99999999999999961e-261 or 2.02e6 < (*.f64 b c) < 6.0000000000000004e68

   1. Initial program 92.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.2%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 91.2%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 91.2%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 93.0%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 93.0%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 93.0%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 93.0%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 93.0%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 93.0%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 93.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in i around inf 51.2%

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

      1. *-commutative 51.2%

         \[\leadsto -4 \cdot \color{blue}{\left(x \cdot i\right)} \]

   9. Simplified 51.2%

      \[\leadsto \color{blue}{-4 \cdot \left(x \cdot i\right)} \]

   if -2.6000000000000002e28 < (*.f64 b c) < -1.25e-67

   1. Initial program 99.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 99.6%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in j around inf 45.8%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]

   if -9.99999999999999961e-261 < (*.f64 b c) < 2.02e6

   1. Initial program 93.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.5%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 91.5%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 91.5%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 91.5%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 91.5%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 91.5%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 91.5%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 92.5%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 92.5%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 92.5%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 92.5%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 92.5%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 92.5%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in j around inf 41.1%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]
   8. Step-by-step derivation

      1. *-commutative 41.1%

         \[\leadsto \color{blue}{\left(j \cdot k\right) \cdot -27} \]

      2. associate-*r* 41.2%

         \[\leadsto \color{blue}{j \cdot \left(k \cdot -27\right)} \]

   9. Simplified 41.2%

      \[\leadsto \color{blue}{j \cdot \left(k \cdot -27\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 47.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \cdot c \leq -1.7 \cdot 10^{+69}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -2.6 \cdot 10^{+28}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq -1.25 \cdot 10^{-67}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq -1 \cdot 10^{-260}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{elif}\;b \cdot c \leq 2020000:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 6 \cdot 10^{+68}:\\ \;\;\;\;-4 \cdot \left(x \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 89.1% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\\ \mathbf{if}\;x \leq -3 \cdot 10^{+258}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \mathbf{elif}\;x \leq -5 \cdot 10^{+14} \lor \neg \left(x \leq 6 \cdot 10^{-87}\right):\\ \;\;\;\;\left(b \cdot c + t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right)\right) - t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + \left(z \cdot \left(\left(18 \cdot t\right) \cdot \left(x \cdot y\right)\right) - t \cdot \left(a \cdot 4\right)\right)\right) - t\_1\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (+ (* x (* 4.0 i)) (* j (* 27.0 k)))))
   (if (<= x -3e+258)
     (* x (+ (* (* 18.0 t) (* y z)) (* i -4.0)))
     (if (or (<= x -5e+14) (not (<= x 6e-87)))
       (- (+ (* b c) (* t (- (* (* x 18.0) (* y z)) (* a 4.0)))) t_1)
       (- (+ (* b c) (- (* z (* (* 18.0 t) (* x y))) (* t (* a 4.0)))) t_1)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (x * (4.0 * i)) + (j * (27.0 * k));
	double tmp;
	if (x <= -3e+258) {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	} else if ((x <= -5e+14) || !(x <= 6e-87)) {
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1;
	} else {
		tmp = ((b * c) + ((z * ((18.0 * t) * (x * y))) - (t * (a * 4.0)))) - t_1;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (x * (4.0d0 * i)) + (j * (27.0d0 * k))
    if (x <= (-3d+258)) then
        tmp = x * (((18.0d0 * t) * (y * z)) + (i * (-4.0d0)))
    else if ((x <= (-5d+14)) .or. (.not. (x <= 6d-87))) then
        tmp = ((b * c) + (t * (((x * 18.0d0) * (y * z)) - (a * 4.0d0)))) - t_1
    else
        tmp = ((b * c) + ((z * ((18.0d0 * t) * (x * y))) - (t * (a * 4.0d0)))) - t_1
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = (x * (4.0 * i)) + (j * (27.0 * k));
	double tmp;
	if (x <= -3e+258) {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	} else if ((x <= -5e+14) || !(x <= 6e-87)) {
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1;
	} else {
		tmp = ((b * c) + ((z * ((18.0 * t) * (x * y))) - (t * (a * 4.0)))) - t_1;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (x * (4.0 * i)) + (j * (27.0 * k))
	tmp = 0
	if x <= -3e+258:
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0))
	elif (x <= -5e+14) or not (x <= 6e-87):
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1
	else:
		tmp = ((b * c) + ((z * ((18.0 * t) * (x * y))) - (t * (a * 4.0)))) - t_1
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(x * Float64(4.0 * i)) + Float64(j * Float64(27.0 * k)))
	tmp = 0.0
	if (x <= -3e+258)
		tmp = Float64(x * Float64(Float64(Float64(18.0 * t) * Float64(y * z)) + Float64(i * -4.0)));
	elseif ((x <= -5e+14) || !(x <= 6e-87))
		tmp = Float64(Float64(Float64(b * c) + Float64(t * Float64(Float64(Float64(x * 18.0) * Float64(y * z)) - Float64(a * 4.0)))) - t_1);
	else
		tmp = Float64(Float64(Float64(b * c) + Float64(Float64(z * Float64(Float64(18.0 * t) * Float64(x * y))) - Float64(t * Float64(a * 4.0)))) - t_1);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (x * (4.0 * i)) + (j * (27.0 * k));
	tmp = 0.0;
	if (x <= -3e+258)
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	elseif ((x <= -5e+14) || ~((x <= 6e-87)))
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1;
	else
		tmp = ((b * c) + ((z * ((18.0 * t) * (x * y))) - (t * (a * 4.0)))) - t_1;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision] + N[(j * N[(27.0 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -3e+258], N[(x * N[(N[(N[(18.0 * t), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] + N[(i * -4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, -5e+14], N[Not[LessEqual[x, 6e-87]], $MachinePrecision]], N[(N[(N[(b * c), $MachinePrecision] + N[(t * N[(N[(N[(x * 18.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] + N[(N[(z * N[(N[(18.0 * t), $MachinePrecision] * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if x < -3e258

   1. Initial program 42.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 42.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 42.3%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 42.3%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 50.0%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 50.0%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 50.0%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 50.0%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in x around inf 100.0%

      \[\leadsto \color{blue}{x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)} \]
   8. Step-by-step derivation

      1. cancel-sign-sub-inv 100.0%

         \[\leadsto x \cdot \color{blue}{\left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) + \left(-4\right) \cdot i\right)} \]

      2. associate-*r* 100.0%

         \[\leadsto x \cdot \left(\color{blue}{\left(18 \cdot t\right) \cdot \left(y \cdot z\right)} + \left(-4\right) \cdot i\right) \]

      3. metadata-eval 100.0%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{-4} \cdot i\right) \]

      4. *-commutative 100.0%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{i \cdot -4}\right) \]

   9. Simplified 100.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)} \]

   if -3e258 < x < -5e14 or 6.00000000000000033e-87 < x

   1. Initial program 89.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.8%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   if -5e14 < x < 6.00000000000000033e-87

   1. Initial program 98.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.6%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 97.9%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 97.9%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 92.1%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 92.1%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 92.1%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 92.1%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in y around 0 93.6%

      \[\leadsto \left(\left(\color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]
   8. Step-by-step derivation

      1. *-commutative 93.6%

         \[\leadsto \left(\left(18 \cdot \color{blue}{\left(\left(x \cdot \left(y \cdot z\right)\right) \cdot t\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. associate-*r* 93.6%

         \[\leadsto \left(\left(\color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot t} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*r* 93.6%

         \[\leadsto \left(\left(\color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 93.6%

         \[\leadsto \left(\left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot \left(y \cdot z\right)\right) \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. associate-*r* 97.9%

         \[\leadsto \left(\left(\color{blue}{\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      6. *-commutative 97.9%

         \[\leadsto \left(\left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot z\right) \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      7. *-commutative 97.9%

         \[\leadsto \left(\left(\color{blue}{\left(z \cdot \left(y \cdot \left(x \cdot 18\right)\right)\right)} \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      8. associate-*l* 98.0%

         \[\leadsto \left(\left(\color{blue}{z \cdot \left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot t\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      9. *-commutative 98.0%

         \[\leadsto \left(\left(z \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right)} \cdot t\right) - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      10. associate-*l* 98.0%

          \[\leadsto \left(\left(z \cdot \left(\color{blue}{\left(x \cdot \left(18 \cdot y\right)\right)} \cdot t\right) - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   9. Simplified 98.0%

      \[\leadsto \left(\left(\color{blue}{z \cdot \left(\left(x \cdot \left(18 \cdot y\right)\right) \cdot t\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   10. Taylor expanded in x around 0 98.0%

       \[\leadsto \left(\left(z \cdot \color{blue}{\left(18 \cdot \left(t \cdot \left(x \cdot y\right)\right)\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]
   11. Step-by-step derivation

       1. associate-*r* 98.0%

          \[\leadsto \left(\left(z \cdot \color{blue}{\left(\left(18 \cdot t\right) \cdot \left(x \cdot y\right)\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   12. Simplified 98.0%

       \[\leadsto \left(\left(z \cdot \color{blue}{\left(\left(18 \cdot t\right) \cdot \left(x \cdot y\right)\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]
3. Recombined 3 regimes into one program.

4. Final simplification 94.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -3 \cdot 10^{+258}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \mathbf{elif}\;x \leq -5 \cdot 10^{+14} \lor \neg \left(x \leq 6 \cdot 10^{-87}\right):\\ \;\;\;\;\left(b \cdot c + t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right)\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + \left(z \cdot \left(\left(18 \cdot t\right) \cdot \left(x \cdot y\right)\right) - t \cdot \left(a \cdot 4\right)\right)\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 89.0% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\\ \mathbf{if}\;x \leq -7.2 \cdot 10^{+257}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \mathbf{elif}\;x \leq -20000 \lor \neg \left(x \leq 2 \cdot 10^{-148}\right):\\ \;\;\;\;\left(b \cdot c + t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right)\right) - t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + \left(z \cdot \left(t \cdot \left(x \cdot \left(18 \cdot y\right)\right)\right) - t \cdot \left(a \cdot 4\right)\right)\right) - t\_1\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (+ (* x (* 4.0 i)) (* j (* 27.0 k)))))
   (if (<= x -7.2e+257)
     (* x (+ (* (* 18.0 t) (* y z)) (* i -4.0)))
     (if (or (<= x -20000.0) (not (<= x 2e-148)))
       (- (+ (* b c) (* t (- (* (* x 18.0) (* y z)) (* a 4.0)))) t_1)
       (- (+ (* b c) (- (* z (* t (* x (* 18.0 y)))) (* t (* a 4.0)))) t_1)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (x * (4.0 * i)) + (j * (27.0 * k));
	double tmp;
	if (x <= -7.2e+257) {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	} else if ((x <= -20000.0) || !(x <= 2e-148)) {
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1;
	} else {
		tmp = ((b * c) + ((z * (t * (x * (18.0 * y)))) - (t * (a * 4.0)))) - t_1;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (x * (4.0d0 * i)) + (j * (27.0d0 * k))
    if (x <= (-7.2d+257)) then
        tmp = x * (((18.0d0 * t) * (y * z)) + (i * (-4.0d0)))
    else if ((x <= (-20000.0d0)) .or. (.not. (x <= 2d-148))) then
        tmp = ((b * c) + (t * (((x * 18.0d0) * (y * z)) - (a * 4.0d0)))) - t_1
    else
        tmp = ((b * c) + ((z * (t * (x * (18.0d0 * y)))) - (t * (a * 4.0d0)))) - t_1
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = (x * (4.0 * i)) + (j * (27.0 * k));
	double tmp;
	if (x <= -7.2e+257) {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	} else if ((x <= -20000.0) || !(x <= 2e-148)) {
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1;
	} else {
		tmp = ((b * c) + ((z * (t * (x * (18.0 * y)))) - (t * (a * 4.0)))) - t_1;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (x * (4.0 * i)) + (j * (27.0 * k))
	tmp = 0
	if x <= -7.2e+257:
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0))
	elif (x <= -20000.0) or not (x <= 2e-148):
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1
	else:
		tmp = ((b * c) + ((z * (t * (x * (18.0 * y)))) - (t * (a * 4.0)))) - t_1
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(x * Float64(4.0 * i)) + Float64(j * Float64(27.0 * k)))
	tmp = 0.0
	if (x <= -7.2e+257)
		tmp = Float64(x * Float64(Float64(Float64(18.0 * t) * Float64(y * z)) + Float64(i * -4.0)));
	elseif ((x <= -20000.0) || !(x <= 2e-148))
		tmp = Float64(Float64(Float64(b * c) + Float64(t * Float64(Float64(Float64(x * 18.0) * Float64(y * z)) - Float64(a * 4.0)))) - t_1);
	else
		tmp = Float64(Float64(Float64(b * c) + Float64(Float64(z * Float64(t * Float64(x * Float64(18.0 * y)))) - Float64(t * Float64(a * 4.0)))) - t_1);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (x * (4.0 * i)) + (j * (27.0 * k));
	tmp = 0.0;
	if (x <= -7.2e+257)
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	elseif ((x <= -20000.0) || ~((x <= 2e-148)))
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - t_1;
	else
		tmp = ((b * c) + ((z * (t * (x * (18.0 * y)))) - (t * (a * 4.0)))) - t_1;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision] + N[(j * N[(27.0 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -7.2e+257], N[(x * N[(N[(N[(18.0 * t), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] + N[(i * -4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, -20000.0], N[Not[LessEqual[x, 2e-148]], $MachinePrecision]], N[(N[(N[(b * c), $MachinePrecision] + N[(t * N[(N[(N[(x * 18.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] + N[(N[(z * N[(t * N[(x * N[(18.0 * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if x < -7.19999999999999968e257

   1. Initial program 42.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 42.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 42.3%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 42.3%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 50.0%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 50.0%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 50.0%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 50.0%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in x around inf 100.0%

      \[\leadsto \color{blue}{x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)} \]
   8. Step-by-step derivation

      1. cancel-sign-sub-inv 100.0%

         \[\leadsto x \cdot \color{blue}{\left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) + \left(-4\right) \cdot i\right)} \]

      2. associate-*r* 100.0%

         \[\leadsto x \cdot \left(\color{blue}{\left(18 \cdot t\right) \cdot \left(y \cdot z\right)} + \left(-4\right) \cdot i\right) \]

      3. metadata-eval 100.0%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{-4} \cdot i\right) \]

      4. *-commutative 100.0%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{i \cdot -4}\right) \]

   9. Simplified 100.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)} \]

   if -7.19999999999999968e257 < x < -2e4 or 1.99999999999999987e-148 < x

   1. Initial program 90.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 92.4%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   if -2e4 < x < 1.99999999999999987e-148

   1. Initial program 98.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 92.9%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 97.8%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 97.8%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 91.3%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 91.3%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 91.3%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 91.3%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in y around 0 92.9%

      \[\leadsto \left(\left(\color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]
   8. Step-by-step derivation

      1. *-commutative 92.9%

         \[\leadsto \left(\left(18 \cdot \color{blue}{\left(\left(x \cdot \left(y \cdot z\right)\right) \cdot t\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. associate-*r* 92.9%

         \[\leadsto \left(\left(\color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot t} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*r* 92.9%

         \[\leadsto \left(\left(\color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 92.9%

         \[\leadsto \left(\left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot \left(y \cdot z\right)\right) \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. associate-*r* 97.8%

         \[\leadsto \left(\left(\color{blue}{\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      6. *-commutative 97.8%

         \[\leadsto \left(\left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot z\right) \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      7. *-commutative 97.8%

         \[\leadsto \left(\left(\color{blue}{\left(z \cdot \left(y \cdot \left(x \cdot 18\right)\right)\right)} \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      8. associate-*l* 98.9%

         \[\leadsto \left(\left(\color{blue}{z \cdot \left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot t\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      9. *-commutative 98.9%

         \[\leadsto \left(\left(z \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right)} \cdot t\right) - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      10. associate-*l* 98.8%

          \[\leadsto \left(\left(z \cdot \left(\color{blue}{\left(x \cdot \left(18 \cdot y\right)\right)} \cdot t\right) - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   9. Simplified 98.8%

      \[\leadsto \left(\left(\color{blue}{z \cdot \left(\left(x \cdot \left(18 \cdot y\right)\right) \cdot t\right)} - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]
3. Recombined 3 regimes into one program.

4. Final simplification 95.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -7.2 \cdot 10^{+257}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \mathbf{elif}\;x \leq -20000 \lor \neg \left(x \leq 2 \cdot 10^{-148}\right):\\ \;\;\;\;\left(b \cdot c + t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right)\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + \left(z \cdot \left(t \cdot \left(x \cdot \left(18 \cdot y\right)\right)\right) - t \cdot \left(a \cdot 4\right)\right)\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 68.4% accurate, 0.8× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := \left(b \cdot c - 4 \cdot \left(t \cdot a\right)\right) - \left(j \cdot 27\right) \cdot k\\ t_3 := t \cdot \left(18 \cdot t\_1 - a \cdot 4\right)\\ \mathbf{if}\;t \leq -5.2:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;t \leq -4.4 \cdot 10^{-77}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{-45}:\\ \;\;\;\;b \cdot c - \left(4 \cdot \left(x \cdot i\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 4.7 \cdot 10^{+215}:\\ \;\;\;\;18 \cdot \left(t \cdot t\_1\right) + -4 \cdot \left(t \cdot a\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{+287}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_3\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* x (* y z)))
        (t_2 (- (- (* b c) (* 4.0 (* t a))) (* (* j 27.0) k)))
        (t_3 (* t (- (* 18.0 t_1) (* a 4.0)))))
   (if (<= t -5.2)
     t_3
     (if (<= t -4.4e-77)
       t_2
       (if (<= t 2.3e-45)
         (- (* b c) (+ (* 4.0 (* x i)) (* 27.0 (* j k))))
         (if (<= t 4.7e+215)
           (+ (* 18.0 (* t t_1)) (* -4.0 (* t a)))
           (if (<= t 4.8e+287) t_2 t_3)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = x * (y * z);
	double t_2 = ((b * c) - (4.0 * (t * a))) - ((j * 27.0) * k);
	double t_3 = t * ((18.0 * t_1) - (a * 4.0));
	double tmp;
	if (t <= -5.2) {
		tmp = t_3;
	} else if (t <= -4.4e-77) {
		tmp = t_2;
	} else if (t <= 2.3e-45) {
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	} else if (t <= 4.7e+215) {
		tmp = (18.0 * (t * t_1)) + (-4.0 * (t * a));
	} else if (t <= 4.8e+287) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = x * (y * z)
    t_2 = ((b * c) - (4.0d0 * (t * a))) - ((j * 27.0d0) * k)
    t_3 = t * ((18.0d0 * t_1) - (a * 4.0d0))
    if (t <= (-5.2d0)) then
        tmp = t_3
    else if (t <= (-4.4d-77)) then
        tmp = t_2
    else if (t <= 2.3d-45) then
        tmp = (b * c) - ((4.0d0 * (x * i)) + (27.0d0 * (j * k)))
    else if (t <= 4.7d+215) then
        tmp = (18.0d0 * (t * t_1)) + ((-4.0d0) * (t * a))
    else if (t <= 4.8d+287) then
        tmp = t_2
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = x * (y * z);
	double t_2 = ((b * c) - (4.0 * (t * a))) - ((j * 27.0) * k);
	double t_3 = t * ((18.0 * t_1) - (a * 4.0));
	double tmp;
	if (t <= -5.2) {
		tmp = t_3;
	} else if (t <= -4.4e-77) {
		tmp = t_2;
	} else if (t <= 2.3e-45) {
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	} else if (t <= 4.7e+215) {
		tmp = (18.0 * (t * t_1)) + (-4.0 * (t * a));
	} else if (t <= 4.8e+287) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = x * (y * z)
	t_2 = ((b * c) - (4.0 * (t * a))) - ((j * 27.0) * k)
	t_3 = t * ((18.0 * t_1) - (a * 4.0))
	tmp = 0
	if t <= -5.2:
		tmp = t_3
	elif t <= -4.4e-77:
		tmp = t_2
	elif t <= 2.3e-45:
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)))
	elif t <= 4.7e+215:
		tmp = (18.0 * (t * t_1)) + (-4.0 * (t * a))
	elif t <= 4.8e+287:
		tmp = t_2
	else:
		tmp = t_3
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(Float64(Float64(b * c) - Float64(4.0 * Float64(t * a))) - Float64(Float64(j * 27.0) * k))
	t_3 = Float64(t * Float64(Float64(18.0 * t_1) - Float64(a * 4.0)))
	tmp = 0.0
	if (t <= -5.2)
		tmp = t_3;
	elseif (t <= -4.4e-77)
		tmp = t_2;
	elseif (t <= 2.3e-45)
		tmp = Float64(Float64(b * c) - Float64(Float64(4.0 * Float64(x * i)) + Float64(27.0 * Float64(j * k))));
	elseif (t <= 4.7e+215)
		tmp = Float64(Float64(18.0 * Float64(t * t_1)) + Float64(-4.0 * Float64(t * a)));
	elseif (t <= 4.8e+287)
		tmp = t_2;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = x * (y * z);
	t_2 = ((b * c) - (4.0 * (t * a))) - ((j * 27.0) * k);
	t_3 = t * ((18.0 * t_1) - (a * 4.0));
	tmp = 0.0;
	if (t <= -5.2)
		tmp = t_3;
	elseif (t <= -4.4e-77)
		tmp = t_2;
	elseif (t <= 2.3e-45)
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	elseif (t <= 4.7e+215)
		tmp = (18.0 * (t * t_1)) + (-4.0 * (t * a));
	elseif (t <= 4.8e+287)
		tmp = t_2;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(b * c), $MachinePrecision] - N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t * N[(N[(18.0 * t$95$1), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -5.2], t$95$3, If[LessEqual[t, -4.4e-77], t$95$2, If[LessEqual[t, 2.3e-45], N[(N[(b * c), $MachinePrecision] - N[(N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision] + N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.7e+215], N[(N[(18.0 * N[(t * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.8e+287], t$95$2, t$95$3]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if t < -5.20000000000000018 or 4.7999999999999998e287 < t

   1. Initial program 81.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 85.2%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around inf 73.3%

      \[\leadsto \color{blue}{t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - 4 \cdot a\right)} \]

   if -5.20000000000000018 < t < -4.40000000000000014e-77 or 4.7000000000000002e215 < t < 4.7999999999999998e287

   1. Initial program 96.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 90.9%

      \[\leadsto \color{blue}{\left(b \cdot c - 4 \cdot \left(a \cdot t\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if -4.40000000000000014e-77 < t < 2.29999999999999992e-45

   1. Initial program 91.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 89.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 90.5%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]

   if 2.29999999999999992e-45 < t < 4.7000000000000002e215

   1. Initial program 97.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 92.2%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around inf 72.5%

      \[\leadsto \color{blue}{t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - 4 \cdot a\right)} \]

   6. Taylor expanded in x around 0 72.5%

      \[\leadsto \color{blue}{-4 \cdot \left(a \cdot t\right) + 18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 83.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5.2:\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{elif}\;t \leq -4.4 \cdot 10^{-77}:\\ \;\;\;\;\left(b \cdot c - 4 \cdot \left(t \cdot a\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{-45}:\\ \;\;\;\;b \cdot c - \left(4 \cdot \left(x \cdot i\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \mathbf{elif}\;t \leq 4.7 \cdot 10^{+215}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) + -4 \cdot \left(t \cdot a\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{+287}:\\ \;\;\;\;\left(b \cdot c - 4 \cdot \left(t \cdot a\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 14: 81.0% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := 4 \cdot \left(t \cdot a\right)\\ t_3 := \left(j \cdot 27\right) \cdot k\\ \mathbf{if}\;t \leq -3.9 \cdot 10^{+59}:\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot t\_1\right) - t\_3\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{-131}:\\ \;\;\;\;\left(b \cdot c - \left(t\_2 + 4 \cdot \left(x \cdot i\right)\right)\right) - t\_3\\ \mathbf{else}:\\ \;\;\;\;\left(\left(b \cdot c + 18 \cdot \left(t \cdot t\_1\right)\right) - t\_2\right) - t\_3\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* 4.0 (* t a))) (t_3 (* (* j 27.0) k)))
   (if (<= t -3.9e+59)
     (- (* t (- (* a -4.0) (* -18.0 t_1))) t_3)
     (if (<= t 1.6e-131)
       (- (- (* b c) (+ t_2 (* 4.0 (* x i)))) t_3)
       (- (- (+ (* b c) (* 18.0 (* t t_1))) t_2) t_3)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = x * (y * z);
	double t_2 = 4.0 * (t * a);
	double t_3 = (j * 27.0) * k;
	double tmp;
	if (t <= -3.9e+59) {
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_3;
	} else if (t <= 1.6e-131) {
		tmp = ((b * c) - (t_2 + (4.0 * (x * i)))) - t_3;
	} else {
		tmp = (((b * c) + (18.0 * (t * t_1))) - t_2) - t_3;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = x * (y * z)
    t_2 = 4.0d0 * (t * a)
    t_3 = (j * 27.0d0) * k
    if (t <= (-3.9d+59)) then
        tmp = (t * ((a * (-4.0d0)) - ((-18.0d0) * t_1))) - t_3
    else if (t <= 1.6d-131) then
        tmp = ((b * c) - (t_2 + (4.0d0 * (x * i)))) - t_3
    else
        tmp = (((b * c) + (18.0d0 * (t * t_1))) - t_2) - t_3
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = x * (y * z);
	double t_2 = 4.0 * (t * a);
	double t_3 = (j * 27.0) * k;
	double tmp;
	if (t <= -3.9e+59) {
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_3;
	} else if (t <= 1.6e-131) {
		tmp = ((b * c) - (t_2 + (4.0 * (x * i)))) - t_3;
	} else {
		tmp = (((b * c) + (18.0 * (t * t_1))) - t_2) - t_3;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = x * (y * z)
	t_2 = 4.0 * (t * a)
	t_3 = (j * 27.0) * k
	tmp = 0
	if t <= -3.9e+59:
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_3
	elif t <= 1.6e-131:
		tmp = ((b * c) - (t_2 + (4.0 * (x * i)))) - t_3
	else:
		tmp = (((b * c) + (18.0 * (t * t_1))) - t_2) - t_3
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(4.0 * Float64(t * a))
	t_3 = Float64(Float64(j * 27.0) * k)
	tmp = 0.0
	if (t <= -3.9e+59)
		tmp = Float64(Float64(t * Float64(Float64(a * -4.0) - Float64(-18.0 * t_1))) - t_3);
	elseif (t <= 1.6e-131)
		tmp = Float64(Float64(Float64(b * c) - Float64(t_2 + Float64(4.0 * Float64(x * i)))) - t_3);
	else
		tmp = Float64(Float64(Float64(Float64(b * c) + Float64(18.0 * Float64(t * t_1))) - t_2) - t_3);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = x * (y * z);
	t_2 = 4.0 * (t * a);
	t_3 = (j * 27.0) * k;
	tmp = 0.0;
	if (t <= -3.9e+59)
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_3;
	elseif (t <= 1.6e-131)
		tmp = ((b * c) - (t_2 + (4.0 * (x * i)))) - t_3;
	else
		tmp = (((b * c) + (18.0 * (t * t_1))) - t_2) - t_3;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]}, If[LessEqual[t, -3.9e+59], N[(N[(t * N[(N[(a * -4.0), $MachinePrecision] - N[(-18.0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$3), $MachinePrecision], If[LessEqual[t, 1.6e-131], N[(N[(N[(b * c), $MachinePrecision] - N[(t$95$2 + N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$3), $MachinePrecision], N[(N[(N[(N[(b * c), $MachinePrecision] + N[(18.0 * N[(t * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision] - t$95$3), $MachinePrecision]]]]]]

Derivation

1. Split input into 3 regimes

2. if t < -3.90000000000000021e59

   1. Initial program 85.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in t around -inf 88.4%

      \[\leadsto \color{blue}{-1 \cdot \left(t \cdot \left(-18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - -4 \cdot a\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if -3.90000000000000021e59 < t < 1.6e-131

   1. Initial program 91.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0 91.7%

      \[\leadsto \color{blue}{\left(b \cdot c - \left(4 \cdot \left(a \cdot t\right) + 4 \cdot \left(i \cdot x\right)\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if 1.6e-131 < t

   1. Initial program 93.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in i around 0 86.7%

      \[\leadsto \color{blue}{\left(\left(18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) + b \cdot c\right) - 4 \cdot \left(a \cdot t\right)\right)} - \left(j \cdot 27\right) \cdot k \]
3. Recombined 3 regimes into one program.

4. Final simplification 89.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.9 \cdot 10^{+59}:\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{-131}:\\ \;\;\;\;\left(b \cdot c - \left(4 \cdot \left(t \cdot a\right) + 4 \cdot \left(x \cdot i\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;\left(\left(b \cdot c + 18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)\right) - 4 \cdot \left(t \cdot a\right)\right) - \left(j \cdot 27\right) \cdot k\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 87.3% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} \mathbf{if}\;x \leq -1.1 \cdot 10^{+258}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right)\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<= x -1.1e+258)
   (* x (+ (* (* 18.0 t) (* y z)) (* i -4.0)))
   (-
    (+ (* b c) (* t (- (* (* x 18.0) (* y z)) (* a 4.0))))
    (+ (* x (* 4.0 i)) (* j (* 27.0 k))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (x <= -1.1e+258) {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	} else {
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - ((x * (4.0 * i)) + (j * (27.0 * k)));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (x <= (-1.1d+258)) then
        tmp = x * (((18.0d0 * t) * (y * z)) + (i * (-4.0d0)))
    else
        tmp = ((b * c) + (t * (((x * 18.0d0) * (y * z)) - (a * 4.0d0)))) - ((x * (4.0d0 * i)) + (j * (27.0d0 * k)))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 tmp;
	if (x <= -1.1e+258) {
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	} else {
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - ((x * (4.0 * i)) + (j * (27.0 * k)));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if x <= -1.1e+258:
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0))
	else:
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - ((x * (4.0 * i)) + (j * (27.0 * k)))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (x <= -1.1e+258)
		tmp = Float64(x * Float64(Float64(Float64(18.0 * t) * Float64(y * z)) + Float64(i * -4.0)));
	else
		tmp = Float64(Float64(Float64(b * c) + Float64(t * Float64(Float64(Float64(x * 18.0) * Float64(y * z)) - Float64(a * 4.0)))) - Float64(Float64(x * Float64(4.0 * i)) + Float64(j * Float64(27.0 * k))));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (x <= -1.1e+258)
		tmp = x * (((18.0 * t) * (y * z)) + (i * -4.0));
	else
		tmp = ((b * c) + (t * (((x * 18.0) * (y * z)) - (a * 4.0)))) - ((x * (4.0 * i)) + (j * (27.0 * k)));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[x, -1.1e+258], N[(x * N[(N[(N[(18.0 * t), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] + N[(i * -4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] + N[(t * N[(N[(N[(x * 18.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(x * N[(4.0 * i), $MachinePrecision]), $MachinePrecision] + N[(j * N[(27.0 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < -1.09999999999999991e258

   1. Initial program 42.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 42.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 42.3%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 42.3%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 50.0%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 50.0%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 50.0%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 50.0%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in x around inf 100.0%

      \[\leadsto \color{blue}{x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)} \]
   8. Step-by-step derivation

      1. cancel-sign-sub-inv 100.0%

         \[\leadsto x \cdot \color{blue}{\left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) + \left(-4\right) \cdot i\right)} \]

      2. associate-*r* 100.0%

         \[\leadsto x \cdot \left(\color{blue}{\left(18 \cdot t\right) \cdot \left(y \cdot z\right)} + \left(-4\right) \cdot i\right) \]

      3. metadata-eval 100.0%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{-4} \cdot i\right) \]

      4. *-commutative 100.0%

         \[\leadsto x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + \color{blue}{i \cdot -4}\right) \]

   9. Simplified 100.0%

      \[\leadsto \color{blue}{x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)} \]

   if -1.09999999999999991e258 < x

   1. Initial program 93.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 92.6%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
3. Recombined 2 regimes into one program.

4. Final simplification 93.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.1 \cdot 10^{+258}:\\ \;\;\;\;x \cdot \left(\left(18 \cdot t\right) \cdot \left(y \cdot z\right) + i \cdot -4\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right)\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 81.3% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := \left(j \cdot 27\right) \cdot k\\ t_3 := 4 \cdot \left(x \cdot i\right)\\ \mathbf{if}\;t \leq -1.38 \cdot 10^{+56}:\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot t\_1\right) - t\_2\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-70}:\\ \;\;\;\;\left(b \cdot c - \left(4 \cdot \left(t \cdot a\right) + t\_3\right)\right) - t\_2\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + t \cdot \left(18 \cdot t\_1 - a \cdot 4\right)\right) - t\_3\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* (* j 27.0) k)) (t_3 (* 4.0 (* x i))))
   (if (<= t -1.38e+56)
     (- (* t (- (* a -4.0) (* -18.0 t_1))) t_2)
     (if (<= t 4.5e-70)
       (- (- (* b c) (+ (* 4.0 (* t a)) t_3)) t_2)
       (- (+ (* b c) (* t (- (* 18.0 t_1) (* a 4.0)))) t_3)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = x * (y * z);
	double t_2 = (j * 27.0) * k;
	double t_3 = 4.0 * (x * i);
	double tmp;
	if (t <= -1.38e+56) {
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_2;
	} else if (t <= 4.5e-70) {
		tmp = ((b * c) - ((4.0 * (t * a)) + t_3)) - t_2;
	} else {
		tmp = ((b * c) + (t * ((18.0 * t_1) - (a * 4.0)))) - t_3;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = x * (y * z)
    t_2 = (j * 27.0d0) * k
    t_3 = 4.0d0 * (x * i)
    if (t <= (-1.38d+56)) then
        tmp = (t * ((a * (-4.0d0)) - ((-18.0d0) * t_1))) - t_2
    else if (t <= 4.5d-70) then
        tmp = ((b * c) - ((4.0d0 * (t * a)) + t_3)) - t_2
    else
        tmp = ((b * c) + (t * ((18.0d0 * t_1) - (a * 4.0d0)))) - t_3
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = x * (y * z);
	double t_2 = (j * 27.0) * k;
	double t_3 = 4.0 * (x * i);
	double tmp;
	if (t <= -1.38e+56) {
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_2;
	} else if (t <= 4.5e-70) {
		tmp = ((b * c) - ((4.0 * (t * a)) + t_3)) - t_2;
	} else {
		tmp = ((b * c) + (t * ((18.0 * t_1) - (a * 4.0)))) - t_3;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = x * (y * z)
	t_2 = (j * 27.0) * k
	t_3 = 4.0 * (x * i)
	tmp = 0
	if t <= -1.38e+56:
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_2
	elif t <= 4.5e-70:
		tmp = ((b * c) - ((4.0 * (t * a)) + t_3)) - t_2
	else:
		tmp = ((b * c) + (t * ((18.0 * t_1) - (a * 4.0)))) - t_3
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(Float64(j * 27.0) * k)
	t_3 = Float64(4.0 * Float64(x * i))
	tmp = 0.0
	if (t <= -1.38e+56)
		tmp = Float64(Float64(t * Float64(Float64(a * -4.0) - Float64(-18.0 * t_1))) - t_2);
	elseif (t <= 4.5e-70)
		tmp = Float64(Float64(Float64(b * c) - Float64(Float64(4.0 * Float64(t * a)) + t_3)) - t_2);
	else
		tmp = Float64(Float64(Float64(b * c) + Float64(t * Float64(Float64(18.0 * t_1) - Float64(a * 4.0)))) - t_3);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = x * (y * z);
	t_2 = (j * 27.0) * k;
	t_3 = 4.0 * (x * i);
	tmp = 0.0;
	if (t <= -1.38e+56)
		tmp = (t * ((a * -4.0) - (-18.0 * t_1))) - t_2;
	elseif (t <= 4.5e-70)
		tmp = ((b * c) - ((4.0 * (t * a)) + t_3)) - t_2;
	else
		tmp = ((b * c) + (t * ((18.0 * t_1) - (a * 4.0)))) - t_3;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]}, Block[{t$95$3 = N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.38e+56], N[(N[(t * N[(N[(a * -4.0), $MachinePrecision] - N[(-18.0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision], If[LessEqual[t, 4.5e-70], N[(N[(N[(b * c), $MachinePrecision] - N[(N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] + N[(t * N[(N[(18.0 * t$95$1), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$3), $MachinePrecision]]]]]]

Derivation

1. Split input into 3 regimes

2. if t < -1.3800000000000001e56

   1. Initial program 85.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in t around -inf 88.4%

      \[\leadsto \color{blue}{-1 \cdot \left(t \cdot \left(-18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - -4 \cdot a\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if -1.3800000000000001e56 < t < 4.50000000000000022e-70

   1. Initial program 90.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0 90.9%

      \[\leadsto \color{blue}{\left(b \cdot c - \left(4 \cdot \left(a \cdot t\right) + 4 \cdot \left(i \cdot x\right)\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if 4.50000000000000022e-70 < t

   1. Initial program 95.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 94.5%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in j around 0 84.5%

      \[\leadsto \color{blue}{\left(b \cdot c + t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - 4 \cdot a\right)\right) - 4 \cdot \left(i \cdot x\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 88.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.38 \cdot 10^{+56}:\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-70}:\\ \;\;\;\;\left(b \cdot c - \left(4 \cdot \left(t \cdot a\right) + 4 \cdot \left(x \cdot i\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\right) - 4 \cdot \left(x \cdot i\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 17: 79.9% accurate, 1.0× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := \left(j \cdot 27\right) \cdot k\\ \mathbf{if}\;t \leq -1.65 \cdot 10^{+64} \lor \neg \left(t \leq 4.6 \cdot 10^{-30}\right):\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) - t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c - \left(4 \cdot \left(t \cdot a\right) + 4 \cdot \left(x \cdot i\right)\right)\right) - t\_1\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* (* j 27.0) k)))
   (if (or (<= t -1.65e+64) (not (<= t 4.6e-30)))
     (- (* t (- (* a -4.0) (* -18.0 (* x (* y z))))) t_1)
     (- (- (* b c) (+ (* 4.0 (* t a)) (* 4.0 (* x i)))) t_1))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (j * 27.0) * k;
	double tmp;
	if ((t <= -1.65e+64) || !(t <= 4.6e-30)) {
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - t_1;
	} else {
		tmp = ((b * c) - ((4.0 * (t * a)) + (4.0 * (x * i)))) - t_1;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (j * 27.0d0) * k
    if ((t <= (-1.65d+64)) .or. (.not. (t <= 4.6d-30))) then
        tmp = (t * ((a * (-4.0d0)) - ((-18.0d0) * (x * (y * z))))) - t_1
    else
        tmp = ((b * c) - ((4.0d0 * (t * a)) + (4.0d0 * (x * i)))) - t_1
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = (j * 27.0) * k;
	double tmp;
	if ((t <= -1.65e+64) || !(t <= 4.6e-30)) {
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - t_1;
	} else {
		tmp = ((b * c) - ((4.0 * (t * a)) + (4.0 * (x * i)))) - t_1;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (j * 27.0) * k
	tmp = 0
	if (t <= -1.65e+64) or not (t <= 4.6e-30):
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - t_1
	else:
		tmp = ((b * c) - ((4.0 * (t * a)) + (4.0 * (x * i)))) - t_1
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(j * 27.0) * k)
	tmp = 0.0
	if ((t <= -1.65e+64) || !(t <= 4.6e-30))
		tmp = Float64(Float64(t * Float64(Float64(a * -4.0) - Float64(-18.0 * Float64(x * Float64(y * z))))) - t_1);
	else
		tmp = Float64(Float64(Float64(b * c) - Float64(Float64(4.0 * Float64(t * a)) + Float64(4.0 * Float64(x * i)))) - t_1);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (j * 27.0) * k;
	tmp = 0.0;
	if ((t <= -1.65e+64) || ~((t <= 4.6e-30)))
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - t_1;
	else
		tmp = ((b * c) - ((4.0 * (t * a)) + (4.0 * (x * i)))) - t_1;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]}, If[Or[LessEqual[t, -1.65e+64], N[Not[LessEqual[t, 4.6e-30]], $MachinePrecision]], N[(N[(t * N[(N[(a * -4.0), $MachinePrecision] - N[(-18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] - N[(N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if t < -1.64999999999999994e64 or 4.59999999999999968e-30 < t

   1. Initial program 91.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in t around -inf 87.3%

      \[\leadsto \color{blue}{-1 \cdot \left(t \cdot \left(-18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - -4 \cdot a\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if -1.64999999999999994e64 < t < 4.59999999999999968e-30

   1. Initial program 91.2%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in y around 0 89.3%

      \[\leadsto \color{blue}{\left(b \cdot c - \left(4 \cdot \left(a \cdot t\right) + 4 \cdot \left(i \cdot x\right)\right)\right)} - \left(j \cdot 27\right) \cdot k \]
3. Recombined 2 regimes into one program.

4. Final simplification 88.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.65 \cdot 10^{+64} \lor \neg \left(t \leq 4.6 \cdot 10^{-30}\right):\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c - \left(4 \cdot \left(t \cdot a\right) + 4 \cdot \left(x \cdot i\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \end{array} \]
5. Add Preprocessing

Alternative 18: 74.8% accurate, 1.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} \mathbf{if}\;t \leq -1.6 \cdot 10^{-74} \lor \neg \left(t \leq 6.5 \cdot 10^{-46}\right):\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - \left(4 \cdot \left(x \cdot i\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= t -1.6e-74) (not (<= t 6.5e-46)))
   (- (* t (- (* a -4.0) (* -18.0 (* x (* y z))))) (* (* j 27.0) k))
   (- (* b c) (+ (* 4.0 (* x i)) (* 27.0 (* j k))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((t <= -1.6e-74) || !(t <= 6.5e-46)) {
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - ((j * 27.0) * k);
	} else {
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((t <= (-1.6d-74)) .or. (.not. (t <= 6.5d-46))) then
        tmp = (t * ((a * (-4.0d0)) - ((-18.0d0) * (x * (y * z))))) - ((j * 27.0d0) * k)
    else
        tmp = (b * c) - ((4.0d0 * (x * i)) + (27.0d0 * (j * k)))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 tmp;
	if ((t <= -1.6e-74) || !(t <= 6.5e-46)) {
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - ((j * 27.0) * k);
	} else {
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (t <= -1.6e-74) or not (t <= 6.5e-46):
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - ((j * 27.0) * k)
	else:
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((t <= -1.6e-74) || !(t <= 6.5e-46))
		tmp = Float64(Float64(t * Float64(Float64(a * -4.0) - Float64(-18.0 * Float64(x * Float64(y * z))))) - Float64(Float64(j * 27.0) * k));
	else
		tmp = Float64(Float64(b * c) - Float64(Float64(4.0 * Float64(x * i)) + Float64(27.0 * Float64(j * k))));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((t <= -1.6e-74) || ~((t <= 6.5e-46)))
		tmp = (t * ((a * -4.0) - (-18.0 * (x * (y * z))))) - ((j * 27.0) * k);
	else
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[t, -1.6e-74], N[Not[LessEqual[t, 6.5e-46]], $MachinePrecision]], N[(N[(t * N[(N[(a * -4.0), $MachinePrecision] - N[(-18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision], N[(N[(b * c), $MachinePrecision] - N[(N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision] + N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < -1.5999999999999999e-74 or 6.49999999999999966e-46 < t

   1. Initial program 91.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in t around -inf 84.1%

      \[\leadsto \color{blue}{-1 \cdot \left(t \cdot \left(-18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - -4 \cdot a\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   if -1.5999999999999999e-74 < t < 6.49999999999999966e-46

   1. Initial program 91.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 89.3%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 90.5%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 87.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.6 \cdot 10^{-74} \lor \neg \left(t \leq 6.5 \cdot 10^{-46}\right):\\ \;\;\;\;t \cdot \left(a \cdot -4 - -18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) - \left(j \cdot 27\right) \cdot k\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - \left(4 \cdot \left(x \cdot i\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 19: 54.7% accurate, 1.2× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} \mathbf{if}\;b \cdot c \leq -1.55 \cdot 10^{+69} \lor \neg \left(b \cdot c \leq 5.3 \cdot 10^{+107}\right):\\ \;\;\;\;b \cdot c - 4 \cdot \left(t \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= (* b c) -1.55e+69) (not (<= (* b c) 5.3e+107)))
   (- (* b c) (* 4.0 (* t a)))
   (+ (* j (* k -27.0)) (* -4.0 (* x i)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (((b * c) <= -1.55e+69) || !((b * c) <= 5.3e+107)) {
		tmp = (b * c) - (4.0 * (t * a));
	} else {
		tmp = (j * (k * -27.0)) + (-4.0 * (x * i));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (((b * c) <= (-1.55d+69)) .or. (.not. ((b * c) <= 5.3d+107))) then
        tmp = (b * c) - (4.0d0 * (t * a))
    else
        tmp = (j * (k * (-27.0d0))) + ((-4.0d0) * (x * i))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 tmp;
	if (((b * c) <= -1.55e+69) || !((b * c) <= 5.3e+107)) {
		tmp = (b * c) - (4.0 * (t * a));
	} else {
		tmp = (j * (k * -27.0)) + (-4.0 * (x * i));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if ((b * c) <= -1.55e+69) or not ((b * c) <= 5.3e+107):
		tmp = (b * c) - (4.0 * (t * a))
	else:
		tmp = (j * (k * -27.0)) + (-4.0 * (x * i))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((Float64(b * c) <= -1.55e+69) || !(Float64(b * c) <= 5.3e+107))
		tmp = Float64(Float64(b * c) - Float64(4.0 * Float64(t * a)));
	else
		tmp = Float64(Float64(j * Float64(k * -27.0)) + Float64(-4.0 * Float64(x * i)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (((b * c) <= -1.55e+69) || ~(((b * c) <= 5.3e+107)))
		tmp = (b * c) - (4.0 * (t * a));
	else
		tmp = (j * (k * -27.0)) + (-4.0 * (x * i));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[N[(b * c), $MachinePrecision], -1.55e+69], N[Not[LessEqual[N[(b * c), $MachinePrecision], 5.3e+107]], $MachinePrecision]], N[(N[(b * c), $MachinePrecision] - N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision] + N[(-4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 b c) < -1.5499999999999999e69 or 5.3e107 < (*.f64 b c)

   1. Initial program 85.3%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 70.1%

      \[\leadsto \color{blue}{\left(b \cdot c - 4 \cdot \left(a \cdot t\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   4. Taylor expanded in j around 0 65.5%

      \[\leadsto \color{blue}{b \cdot c - 4 \cdot \left(a \cdot t\right)} \]

   if -1.5499999999999999e69 < (*.f64 b c) < 5.3e107

   1. Initial program 94.2%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in i around inf 59.4%

      \[\leadsto \color{blue}{-4 \cdot \left(i \cdot x\right)} + j \cdot \left(k \cdot -27\right) \]
3. Recombined 2 regimes into one program.

4. Final simplification 61.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \cdot c \leq -1.55 \cdot 10^{+69} \lor \neg \left(b \cdot c \leq 5.3 \cdot 10^{+107}\right):\\ \;\;\;\;b \cdot c - 4 \cdot \left(t \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right) + -4 \cdot \left(x \cdot i\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 20: 70.8% accurate, 1.2× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} \mathbf{if}\;t \leq -6.5 \cdot 10^{+38} \lor \neg \left(t \leq 2.3 \cdot 10^{-45}\right):\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - \left(4 \cdot \left(x \cdot i\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= t -6.5e+38) (not (<= t 2.3e-45)))
   (* t (- (* 18.0 (* x (* y z))) (* a 4.0)))
   (- (* b c) (+ (* 4.0 (* x i)) (* 27.0 (* j k))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((t <= -6.5e+38) || !(t <= 2.3e-45)) {
		tmp = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	} else {
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((t <= (-6.5d+38)) .or. (.not. (t <= 2.3d-45))) then
        tmp = t * ((18.0d0 * (x * (y * z))) - (a * 4.0d0))
    else
        tmp = (b * c) - ((4.0d0 * (x * i)) + (27.0d0 * (j * k)))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 tmp;
	if ((t <= -6.5e+38) || !(t <= 2.3e-45)) {
		tmp = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	} else {
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (t <= -6.5e+38) or not (t <= 2.3e-45):
		tmp = t * ((18.0 * (x * (y * z))) - (a * 4.0))
	else:
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((t <= -6.5e+38) || !(t <= 2.3e-45))
		tmp = Float64(t * Float64(Float64(18.0 * Float64(x * Float64(y * z))) - Float64(a * 4.0)));
	else
		tmp = Float64(Float64(b * c) - Float64(Float64(4.0 * Float64(x * i)) + Float64(27.0 * Float64(j * k))));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((t <= -6.5e+38) || ~((t <= 2.3e-45)))
		tmp = t * ((18.0 * (x * (y * z))) - (a * 4.0));
	else
		tmp = (b * c) - ((4.0 * (x * i)) + (27.0 * (j * k)));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[t, -6.5e+38], N[Not[LessEqual[t, 2.3e-45]], $MachinePrecision]], N[(t * N[(N[(18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * c), $MachinePrecision] - N[(N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision] + N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < -6.5e38 or 2.29999999999999992e-45 < t

   1. Initial program 91.9%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 92.1%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around inf 73.3%

      \[\leadsto \color{blue}{t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - 4 \cdot a\right)} \]

   if -6.5e38 < t < 2.29999999999999992e-45

   1. Initial program 90.8%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 88.8%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in t around 0 85.0%

      \[\leadsto \color{blue}{b \cdot c - \left(4 \cdot \left(i \cdot x\right) + 27 \cdot \left(j \cdot k\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 79.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.5 \cdot 10^{+38} \lor \neg \left(t \leq 2.3 \cdot 10^{-45}\right):\\ \;\;\;\;t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - \left(4 \cdot \left(x \cdot i\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 21: 45.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{if}\;t \leq -3.4:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 1.95 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 8.2 \cdot 10^{+141}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot -4\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* t (* z (* 18.0 (* x y))))))
   (if (<= t -3.4)
     t_1
     (if (<= t 1.95e-69)
       (+ (* b c) (* j (* k -27.0)))
       (if (<= t 8.2e+141) t_1 (* a (* t -4.0)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = t * (z * (18.0 * (x * y)));
	double tmp;
	if (t <= -3.4) {
		tmp = t_1;
	} else if (t <= 1.95e-69) {
		tmp = (b * c) + (j * (k * -27.0));
	} else if (t <= 8.2e+141) {
		tmp = t_1;
	} else {
		tmp = a * (t * -4.0);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = t * (z * (18.0d0 * (x * y)))
    if (t <= (-3.4d0)) then
        tmp = t_1
    else if (t <= 1.95d-69) then
        tmp = (b * c) + (j * (k * (-27.0d0)))
    else if (t <= 8.2d+141) then
        tmp = t_1
    else
        tmp = a * (t * (-4.0d0))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = t * (z * (18.0 * (x * y)));
	double tmp;
	if (t <= -3.4) {
		tmp = t_1;
	} else if (t <= 1.95e-69) {
		tmp = (b * c) + (j * (k * -27.0));
	} else if (t <= 8.2e+141) {
		tmp = t_1;
	} else {
		tmp = a * (t * -4.0);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = t * (z * (18.0 * (x * y)))
	tmp = 0
	if t <= -3.4:
		tmp = t_1
	elif t <= 1.95e-69:
		tmp = (b * c) + (j * (k * -27.0))
	elif t <= 8.2e+141:
		tmp = t_1
	else:
		tmp = a * (t * -4.0)
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(t * Float64(z * Float64(18.0 * Float64(x * y))))
	tmp = 0.0
	if (t <= -3.4)
		tmp = t_1;
	elseif (t <= 1.95e-69)
		tmp = Float64(Float64(b * c) + Float64(j * Float64(k * -27.0)));
	elseif (t <= 8.2e+141)
		tmp = t_1;
	else
		tmp = Float64(a * Float64(t * -4.0));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = t * (z * (18.0 * (x * y)));
	tmp = 0.0;
	if (t <= -3.4)
		tmp = t_1;
	elseif (t <= 1.95e-69)
		tmp = (b * c) + (j * (k * -27.0));
	elseif (t <= 8.2e+141)
		tmp = t_1;
	else
		tmp = a * (t * -4.0);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(t * N[(z * N[(18.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.4], t$95$1, If[LessEqual[t, 1.95e-69], N[(N[(b * c), $MachinePrecision] + N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 8.2e+141], t$95$1, N[(a * N[(t * -4.0), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 3 regimes

2. if t < -3.39999999999999991 or 1.9499999999999999e-69 < t < 8.20000000000000044e141

   1. Initial program 88.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 87.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 87.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 87.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 88.8%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 88.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 88.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 88.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 89.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 89.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 89.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 49.8%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 49.8%

         \[\leadsto \color{blue}{\left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot 18} \]

      2. associate-*l* 49.8%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot \left(y \cdot z\right)\right) \cdot 18\right)} \]

      3. *-commutative 49.8%

         \[\leadsto t \cdot \color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

      4. associate-*r* 49.8%

         \[\leadsto t \cdot \color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \]

      5. associate-*r* 51.9%

         \[\leadsto t \cdot \color{blue}{\left(\left(\left(18 \cdot x\right) \cdot y\right) \cdot z\right)} \]

      6. *-commutative 51.9%

         \[\leadsto t \cdot \left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot y\right) \cdot z\right) \]

   9. Simplified 51.9%

      \[\leadsto \color{blue}{t \cdot \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \]

   10. Taylor expanded in x around 0 51.9%

       \[\leadsto t \cdot \left(\color{blue}{\left(18 \cdot \left(x \cdot y\right)\right)} \cdot z\right) \]

   if -3.39999999999999991 < t < 1.9499999999999999e-69

   1. Initial program 92.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in b around inf 60.9%

      \[\leadsto \color{blue}{b \cdot c} + j \cdot \left(k \cdot -27\right) \]

   if 8.20000000000000044e141 < t

   1. Initial program 93.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 97.0%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate-*r* 99.9%

         \[\leadsto \left(t \cdot \left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot z} - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      2. distribute-rgt-out-- 93.6%

         \[\leadsto \left(\color{blue}{\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      3. associate-*l* 81.8%

         \[\leadsto \left(\left(\color{blue}{\left(\left(x \cdot 18\right) \cdot y\right) \cdot \left(z \cdot t\right)} - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      4. *-commutative 81.8%

         \[\leadsto \left(\left(\color{blue}{\left(y \cdot \left(x \cdot 18\right)\right)} \cdot \left(z \cdot t\right) - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

      5. *-commutative 81.8%

         \[\leadsto \left(\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - \color{blue}{t \cdot \left(a \cdot 4\right)}\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   6. Applied egg-rr 81.8%

      \[\leadsto \left(\color{blue}{\left(\left(y \cdot \left(x \cdot 18\right)\right) \cdot \left(z \cdot t\right) - t \cdot \left(a \cdot 4\right)\right)} + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right) \]

   7. Taylor expanded in a around inf 53.3%

      \[\leadsto \color{blue}{-4 \cdot \left(a \cdot t\right)} \]
   8. Step-by-step derivation

      1. *-commutative 53.3%

         \[\leadsto -4 \cdot \color{blue}{\left(t \cdot a\right)} \]

      2. associate-*l* 56.3%

         \[\leadsto \color{blue}{\left(-4 \cdot t\right) \cdot a} \]

      3. *-commutative 56.3%

         \[\leadsto \color{blue}{a \cdot \left(-4 \cdot t\right)} \]

      4. *-commutative 56.3%

         \[\leadsto a \cdot \color{blue}{\left(t \cdot -4\right)} \]

   9. Simplified 56.3%

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

4. Final simplification 57.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.4:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.95 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 8.2 \cdot 10^{+141}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot -4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 22: 46.7% accurate, 1.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} t_1 := t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{if}\;t \leq -0.9:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{+142}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - 4 \cdot \left(t \cdot a\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* t (* z (* 18.0 (* x y))))))
   (if (<= t -0.9)
     t_1
     (if (<= t 2.05e-69)
       (+ (* b c) (* j (* k -27.0)))
       (if (<= t 4.5e+142) t_1 (- (* b c) (* 4.0 (* t a))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = t * (z * (18.0 * (x * y)));
	double tmp;
	if (t <= -0.9) {
		tmp = t_1;
	} else if (t <= 2.05e-69) {
		tmp = (b * c) + (j * (k * -27.0));
	} else if (t <= 4.5e+142) {
		tmp = t_1;
	} else {
		tmp = (b * c) - (4.0 * (t * a));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = t * (z * (18.0d0 * (x * y)))
    if (t <= (-0.9d0)) then
        tmp = t_1
    else if (t <= 2.05d-69) then
        tmp = (b * c) + (j * (k * (-27.0d0)))
    else if (t <= 4.5d+142) then
        tmp = t_1
    else
        tmp = (b * c) - (4.0d0 * (t * a))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 t_1 = t * (z * (18.0 * (x * y)));
	double tmp;
	if (t <= -0.9) {
		tmp = t_1;
	} else if (t <= 2.05e-69) {
		tmp = (b * c) + (j * (k * -27.0));
	} else if (t <= 4.5e+142) {
		tmp = t_1;
	} else {
		tmp = (b * c) - (4.0 * (t * a));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = t * (z * (18.0 * (x * y)))
	tmp = 0
	if t <= -0.9:
		tmp = t_1
	elif t <= 2.05e-69:
		tmp = (b * c) + (j * (k * -27.0))
	elif t <= 4.5e+142:
		tmp = t_1
	else:
		tmp = (b * c) - (4.0 * (t * a))
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(t * Float64(z * Float64(18.0 * Float64(x * y))))
	tmp = 0.0
	if (t <= -0.9)
		tmp = t_1;
	elseif (t <= 2.05e-69)
		tmp = Float64(Float64(b * c) + Float64(j * Float64(k * -27.0)));
	elseif (t <= 4.5e+142)
		tmp = t_1;
	else
		tmp = Float64(Float64(b * c) - Float64(4.0 * Float64(t * a)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = t * (z * (18.0 * (x * y)));
	tmp = 0.0;
	if (t <= -0.9)
		tmp = t_1;
	elseif (t <= 2.05e-69)
		tmp = (b * c) + (j * (k * -27.0));
	elseif (t <= 4.5e+142)
		tmp = t_1;
	else
		tmp = (b * c) - (4.0 * (t * a));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(t * N[(z * N[(18.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -0.9], t$95$1, If[LessEqual[t, 2.05e-69], N[(N[(b * c), $MachinePrecision] + N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.5e+142], t$95$1, N[(N[(b * c), $MachinePrecision] - N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 3 regimes

2. if t < -0.900000000000000022 or 2.04999999999999995e-69 < t < 4.4999999999999999e142

   1. Initial program 88.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 87.7%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 87.7%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 87.7%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 88.8%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 88.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 88.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 88.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 89.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 89.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 89.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 89.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in y around inf 49.8%

      \[\leadsto \color{blue}{18 \cdot \left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 49.8%

         \[\leadsto \color{blue}{\left(t \cdot \left(x \cdot \left(y \cdot z\right)\right)\right) \cdot 18} \]

      2. associate-*l* 49.8%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot \left(y \cdot z\right)\right) \cdot 18\right)} \]

      3. *-commutative 49.8%

         \[\leadsto t \cdot \color{blue}{\left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right)\right)} \]

      4. associate-*r* 49.8%

         \[\leadsto t \cdot \color{blue}{\left(\left(18 \cdot x\right) \cdot \left(y \cdot z\right)\right)} \]

      5. associate-*r* 51.9%

         \[\leadsto t \cdot \color{blue}{\left(\left(\left(18 \cdot x\right) \cdot y\right) \cdot z\right)} \]

      6. *-commutative 51.9%

         \[\leadsto t \cdot \left(\left(\color{blue}{\left(x \cdot 18\right)} \cdot y\right) \cdot z\right) \]

   9. Simplified 51.9%

      \[\leadsto \color{blue}{t \cdot \left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right)} \]

   10. Taylor expanded in x around 0 51.9%

       \[\leadsto t \cdot \left(\color{blue}{\left(18 \cdot \left(x \cdot y\right)\right)} \cdot z\right) \]

   if -0.900000000000000022 < t < 2.04999999999999995e-69

   1. Initial program 92.5%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 91.1%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in b around inf 60.9%

      \[\leadsto \color{blue}{b \cdot c} + j \cdot \left(k \cdot -27\right) \]

   if 4.4999999999999999e142 < t

   1. Initial program 93.6%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 72.7%

      \[\leadsto \color{blue}{\left(b \cdot c - 4 \cdot \left(a \cdot t\right)\right)} - \left(j \cdot 27\right) \cdot k \]

   4. Taylor expanded in j around 0 59.3%

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

4. Final simplification 57.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -0.9:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-69}:\\ \;\;\;\;b \cdot c + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{+142}:\\ \;\;\;\;t \cdot \left(z \cdot \left(18 \cdot \left(x \cdot y\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - 4 \cdot \left(t \cdot a\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 23: 37.4% accurate, 1.6× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ \begin{array}{l} \mathbf{if}\;b \cdot c \leq -8.8 \cdot 10^{+144} \lor \neg \left(b \cdot c \leq 9.8 \cdot 10^{+36}\right):\\ \;\;\;\;b \cdot c\\ \mathbf{else}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= (* b c) -8.8e+144) (not (<= (* b c) 9.8e+36)))
   (* b c)
   (* (* j k) -27.0)))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (((b * c) <= -8.8e+144) || !((b * c) <= 9.8e+36)) {
		tmp = b * c;
	} else {
		tmp = (j * k) * -27.0;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (((b * c) <= (-8.8d+144)) .or. (.not. ((b * c) <= 9.8d+36))) then
        tmp = b * c
    else
        tmp = (j * k) * (-27.0d0)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
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 tmp;
	if (((b * c) <= -8.8e+144) || !((b * c) <= 9.8e+36)) {
		tmp = b * c;
	} else {
		tmp = (j * k) * -27.0;
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if ((b * c) <= -8.8e+144) or not ((b * c) <= 9.8e+36):
		tmp = b * c
	else:
		tmp = (j * k) * -27.0
	return tmp

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((Float64(b * c) <= -8.8e+144) || !(Float64(b * c) <= 9.8e+36))
		tmp = Float64(b * c);
	else
		tmp = Float64(Float64(j * k) * -27.0);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (((b * c) <= -8.8e+144) || ~(((b * c) <= 9.8e+36)))
		tmp = b * c;
	else
		tmp = (j * k) * -27.0;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[N[(b * c), $MachinePrecision], -8.8e+144], N[Not[LessEqual[N[(b * c), $MachinePrecision], 9.8e+36]], $MachinePrecision]], N[(b * c), $MachinePrecision], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 b c) < -8.79999999999999952e144 or 9.79999999999999962e36 < (*.f64 b c)

   1. Initial program 86.0%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 84.8%

      \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
   4. Add Preprocessing
   5. Step-by-step derivation

      1. associate--l+ 84.8%

         \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      2. *-commutative 84.8%

         \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      3. fma-def 84.8%

         \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

      4. associate-*l* 84.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      5. fma-neg 84.8%

         \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      6. associate-*r* 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

      7. associate-*r* 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

      8. +-commutative 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

      9. fma-def 84.8%

         \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

      10. *-commutative 84.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

      11. *-commutative 84.8%

          \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

   6. Applied egg-rr 84.8%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

   7. Taylor expanded in b around inf 55.5%

      \[\leadsto \color{blue}{b \cdot c} \]

   if -8.79999999999999952e144 < (*.f64 b c) < 9.79999999999999962e36

   1. Initial program 93.7%

      \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

   3. Simplified 93.2%

      \[\leadsto \color{blue}{\mathsf{fma}\left(t, \mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), a \cdot -4\right), \mathsf{fma}\left(b, c, x \cdot \left(i \cdot -4\right)\right)\right) + j \cdot \left(k \cdot -27\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in j around inf 33.9%

      \[\leadsto \color{blue}{-27 \cdot \left(j \cdot k\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 40.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \cdot c \leq -8.8 \cdot 10^{+144} \lor \neg \left(b \cdot c \leq 9.8 \cdot 10^{+36}\right):\\ \;\;\;\;b \cdot c\\ \mathbf{else}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \end{array} \]
5. Add Preprocessing

Alternative 24: 24.2% accurate, 10.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c, i, j, k] = \mathsf{sort}([x, y, z, t, a, b, c, i, j, k])\\ \\ b \cdot c \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c i j k) :precision binary64 (* b c))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k);
double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return b * c;
}

Fortran

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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
    code = b * c
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c && c < i && i < j && j < k;
public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return b * c;
}

Python

[x, y, z, t, a, b, c, i, j, k] = sort([x, y, z, t, a, b, c, i, j, k])
def code(x, y, z, t, a, b, c, i, j, k):
	return b * c

Julia

x, y, z, t, a, b, c, i, j, k = sort([x, y, z, t, a, b, c, i, j, k])
function code(x, y, z, t, a, b, c, i, j, k)
	return Float64(b * c)
end

MATLAB

x, y, z, t, a, b, c, i, j, k = num2cell(sort([x, y, z, t, a, b, c, i, j, k])){:}
function tmp = code(x, y, z, t, a, b, c, i, j, k)
	tmp = b * c;
end

Wolfram

NOTE: x, y, z, t, a, b, c, i, j, and k should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := N[(b * c), $MachinePrecision]

Derivation

1. Initial program 91.3%

   \[\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \]

3. Simplified 90.3%

   \[\leadsto \color{blue}{\left(t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + b \cdot c\right) - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)} \]
4. Add Preprocessing
5. Step-by-step derivation

   1. associate--l+ 90.3%

      \[\leadsto \color{blue}{t \cdot \left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

   2. *-commutative 90.3%

      \[\leadsto \color{blue}{\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4\right) \cdot t} + \left(b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

   3. fma-def 90.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\left(x \cdot 18\right) \cdot \left(y \cdot z\right) - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right)} \]

   4. associate-*l* 90.7%

      \[\leadsto \mathsf{fma}\left(\color{blue}{x \cdot \left(18 \cdot \left(y \cdot z\right)\right)} - a \cdot 4, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

   5. fma-neg 90.7%

      \[\leadsto \mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(x, 18 \cdot \left(y \cdot z\right), -a \cdot 4\right)}, t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

   6. associate-*r* 90.6%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \color{blue}{\left(18 \cdot y\right) \cdot z}, -a \cdot 4\right), t, b \cdot c - \left(x \cdot \left(4 \cdot i\right) + j \cdot \left(27 \cdot k\right)\right)\right) \]

   7. associate-*r* 91.0%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \left(\color{blue}{\left(x \cdot 4\right) \cdot i} + j \cdot \left(27 \cdot k\right)\right)\right) \]

   8. +-commutative 91.0%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\left(j \cdot \left(27 \cdot k\right) + \left(x \cdot 4\right) \cdot i\right)}\right) \]

   9. fma-def 91.0%

      \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \color{blue}{\mathsf{fma}\left(j, 27 \cdot k, \left(x \cdot 4\right) \cdot i\right)}\right) \]

   10. *-commutative 91.0%

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, \color{blue}{k \cdot 27}, \left(x \cdot 4\right) \cdot i\right)\right) \]

   11. *-commutative 91.0%

       \[\leadsto \mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, \color{blue}{i \cdot \left(x \cdot 4\right)}\right)\right) \]

6. Applied egg-rr 91.0%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(x, \left(18 \cdot y\right) \cdot z, -a \cdot 4\right), t, b \cdot c - \mathsf{fma}\left(j, k \cdot 27, i \cdot \left(x \cdot 4\right)\right)\right)} \]

7. Taylor expanded in b around inf 20.3%

   \[\leadsto \color{blue}{b \cdot c} \]

8. Final simplification 20.3%

   \[\leadsto b \cdot c \]
9. Add Preprocessing

Developer target: 89.3% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(a \cdot t + i \cdot x\right) \cdot 4\\ t_2 := \left(\left(18 \cdot t\right) \cdot \left(\left(x \cdot y\right) \cdot z\right) - t\_1\right) - \left(\left(k \cdot j\right) \cdot 27 - c \cdot b\right)\\ \mathbf{if}\;t < -1.6210815397541398 \cdot 10^{-69}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t < 165.68027943805222:\\ \;\;\;\;\left(\left(18 \cdot y\right) \cdot \left(x \cdot \left(z \cdot t\right)\right) - t\_1\right) + \left(c \cdot b - 27 \cdot \left(k \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* (+ (* a t) (* i x)) 4.0))
        (t_2
         (-
          (- (* (* 18.0 t) (* (* x y) z)) t_1)
          (- (* (* k j) 27.0) (* c b)))))
   (if (< t -1.6210815397541398e-69)
     t_2
     (if (< t 165.68027943805222)
       (+ (- (* (* 18.0 y) (* x (* z t))) t_1) (- (* c b) (* 27.0 (* k j))))
       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 t_1 = ((a * t) + (i * x)) * 4.0;
	double t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b));
	double tmp;
	if (t < -1.6210815397541398e-69) {
		tmp = t_2;
	} else if (t < 165.68027943805222) {
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = ((a * t) + (i * x)) * 4.0d0
    t_2 = (((18.0d0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0d0) - (c * b))
    if (t < (-1.6210815397541398d-69)) then
        tmp = t_2
    else if (t < 165.68027943805222d0) then
        tmp = (((18.0d0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0d0 * (k * j)))
    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 t_1 = ((a * t) + (i * x)) * 4.0;
	double t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b));
	double tmp;
	if (t < -1.6210815397541398e-69) {
		tmp = t_2;
	} else if (t < 165.68027943805222) {
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = ((a * t) + (i * x)) * 4.0
	t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b))
	tmp = 0
	if t < -1.6210815397541398e-69:
		tmp = t_2
	elif t < 165.68027943805222:
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(Float64(a * t) + Float64(i * x)) * 4.0)
	t_2 = Float64(Float64(Float64(Float64(18.0 * t) * Float64(Float64(x * y) * z)) - t_1) - Float64(Float64(Float64(k * j) * 27.0) - Float64(c * b)))
	tmp = 0.0
	if (t < -1.6210815397541398e-69)
		tmp = t_2;
	elseif (t < 165.68027943805222)
		tmp = Float64(Float64(Float64(Float64(18.0 * y) * Float64(x * Float64(z * t))) - t_1) + Float64(Float64(c * b) - Float64(27.0 * Float64(k * j))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = ((a * t) + (i * x)) * 4.0;
	t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b));
	tmp = 0.0;
	if (t < -1.6210815397541398e-69)
		tmp = t_2;
	elseif (t < 165.68027943805222)
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(N[(a * t), $MachinePrecision] + N[(i * x), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[(18.0 * t), $MachinePrecision] * N[(N[(x * y), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision] - N[(N[(N[(k * j), $MachinePrecision] * 27.0), $MachinePrecision] - N[(c * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Less[t, -1.6210815397541398e-69], t$95$2, If[Less[t, 165.68027943805222], N[(N[(N[(N[(18.0 * y), $MachinePrecision] * N[(x * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision] + N[(N[(c * b), $MachinePrecision] - N[(27.0 * N[(k * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]

Reproduce

herbie shell --seed 2024027 
(FPCore (x y z t a b c i j k)
  :name "Diagrams.Solve.Polynomial:cubForm  from diagrams-solve-0.1, E"
  :precision binary64

  :herbie-target
  (if (< t -1.6210815397541398e-69) (- (- (* (* 18.0 t) (* (* x y) z)) (* (+ (* a t) (* i x)) 4.0)) (- (* (* k j) 27.0) (* c b))) (if (< t 165.68027943805222) (+ (- (* (* 18.0 y) (* x (* z t))) (* (+ (* a t) (* i x)) 4.0)) (- (* c b) (* 27.0 (* k j)))) (- (- (* (* 18.0 t) (* (* x y) z)) (* (+ (* a t) (* i x)) 4.0)) (- (* (* k j) 27.0) (* c b)))))

  (- (- (+ (- (* (* (* (* x 18.0) y) z) t) (* (* a 4.0) t)) (* b c)) (* (* x 4.0) i)) (* (* j 27.0) k)))