Diagrams.TwoD.Segment.Bernstein:evaluateBernstein from diagrams-lib-1.3.0.3

Percentage Accurate: 87.8% → 99.4%

Time: 8.6s

Alternatives: 9

Speedup: 0.6×

• 20.9% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (/ (* x (+ (- y z) 1.0)) z))

C

double code(double x, double y, double z) {
	return (x * ((y - z) + 1.0)) / z;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = (x * ((y - z) + 1.0d0)) / z
end function

Java

public static double code(double x, double y, double z) {
	return (x * ((y - z) + 1.0)) / z;
}

Python

def code(x, y, z):
	return (x * ((y - z) + 1.0)) / z

Julia

function code(x, y, z)
	return Float64(Float64(x * Float64(Float64(y - z) + 1.0)) / z)
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * ((y - z) + 1.0)) / z;
end

Wolfram

code[x_, y_, z_] := N[(N[(x * N[(N[(y - z), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision]

Initial Program: 87.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (/ (* x (+ (- y z) 1.0)) z))

C

double code(double x, double y, double z) {
	return (x * ((y - z) + 1.0)) / z;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = (x * ((y - z) + 1.0d0)) / z
end function

Java

public static double code(double x, double y, double z) {
	return (x * ((y - z) + 1.0)) / z;
}

Python

def code(x, y, z):
	return (x * ((y - z) + 1.0)) / z

Julia

function code(x, y, z)
	return Float64(Float64(x * Float64(Float64(y - z) + 1.0)) / z)
end

MATLAB

function tmp = code(x, y, z)
	tmp = (x * ((y - z) + 1.0)) / z;
end

Wolfram

code[x_, y_, z_] := N[(N[(x * N[(N[(y - z), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision]

Alternative 1: 99.4% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := x \cdot \left(-1 + \frac{y + 1}{z}\right)\\ \mathbf{if}\;z \leq -8 \cdot 10^{-20}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;z \leq 1.42 \cdot 10^{-99}:\\ \;\;\;\;\frac{x \cdot \left(y + 1\right)}{z}\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* x (+ -1.0 (/ (+ y 1.0) z)))))
   (if (<= z -8e-20) t_0 (if (<= z 1.42e-99) (/ (* x (+ y 1.0)) z) t_0))))

C

double code(double x, double y, double z) {
	double t_0 = x * (-1.0 + ((y + 1.0) / z));
	double tmp;
	if (z <= -8e-20) {
		tmp = t_0;
	} else if (z <= 1.42e-99) {
		tmp = (x * (y + 1.0)) / z;
	} else {
		tmp = t_0;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = x * ((-1.0d0) + ((y + 1.0d0) / z))
    if (z <= (-8d-20)) then
        tmp = t_0
    else if (z <= 1.42d-99) then
        tmp = (x * (y + 1.0d0)) / z
    else
        tmp = t_0
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double t_0 = x * (-1.0 + ((y + 1.0) / z));
	double tmp;
	if (z <= -8e-20) {
		tmp = t_0;
	} else if (z <= 1.42e-99) {
		tmp = (x * (y + 1.0)) / z;
	} else {
		tmp = t_0;
	}
	return tmp;
}

Python

def code(x, y, z):
	t_0 = x * (-1.0 + ((y + 1.0) / z))
	tmp = 0
	if z <= -8e-20:
		tmp = t_0
	elif z <= 1.42e-99:
		tmp = (x * (y + 1.0)) / z
	else:
		tmp = t_0
	return tmp

Julia

function code(x, y, z)
	t_0 = Float64(x * Float64(-1.0 + Float64(Float64(y + 1.0) / z)))
	tmp = 0.0
	if (z <= -8e-20)
		tmp = t_0;
	elseif (z <= 1.42e-99)
		tmp = Float64(Float64(x * Float64(y + 1.0)) / z);
	else
		tmp = t_0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	t_0 = x * (-1.0 + ((y + 1.0) / z));
	tmp = 0.0;
	if (z <= -8e-20)
		tmp = t_0;
	elseif (z <= 1.42e-99)
		tmp = (x * (y + 1.0)) / z;
	else
		tmp = t_0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(x * N[(-1.0 + N[(N[(y + 1.0), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -8e-20], t$95$0, If[LessEqual[z, 1.42e-99], N[(N[(x * N[(y + 1.0), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision], t$95$0]]]

Derivation

1. Split input into 2 regimes

2. if z < -7.99999999999999956e-20 or 1.42e-99 < z

   1. Initial program 74.5%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.9%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.9%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   if -7.99999999999999956e-20 < z < 1.42e-99

   1. Initial program 100.0%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \mathsf{/.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\color{blue}{y}, 1\right)\right), z\right) \]
   4. Step-by-step derivation

   5. Simplified 100.0%

      \[\leadsto \frac{x \cdot \left(\color{blue}{y} + 1\right)}{z} \]
3. Recombined 2 regimes into one program.

4. Final simplification 99.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -8 \cdot 10^{-20}:\\ \;\;\;\;x \cdot \left(-1 + \frac{y + 1}{z}\right)\\ \mathbf{elif}\;z \leq 1.42 \cdot 10^{-99}:\\ \;\;\;\;\frac{x \cdot \left(y + 1\right)}{z}\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(-1 + \frac{y + 1}{z}\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 64.9% accurate, 0.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := y \cdot \frac{x}{z}\\ \mathbf{if}\;z \leq -4.6 \cdot 10^{+21}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq -9.5 \cdot 10^{-70}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;z \leq -5.5 \cdot 10^{-301}:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{elif}\;z \leq 4.6 \cdot 10^{-124}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;z \leq 5.2:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;0 - x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* y (/ x z))))
   (if (<= z -4.6e+21)
     (- 0.0 x)
     (if (<= z -9.5e-70)
       t_0
       (if (<= z -5.5e-301)
         (/ x z)
         (if (<= z 4.6e-124) t_0 (if (<= z 5.2) (/ x z) (- 0.0 x))))))))

C

double code(double x, double y, double z) {
	double t_0 = y * (x / z);
	double tmp;
	if (z <= -4.6e+21) {
		tmp = 0.0 - x;
	} else if (z <= -9.5e-70) {
		tmp = t_0;
	} else if (z <= -5.5e-301) {
		tmp = x / z;
	} else if (z <= 4.6e-124) {
		tmp = t_0;
	} else if (z <= 5.2) {
		tmp = x / z;
	} else {
		tmp = 0.0 - x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = y * (x / z)
    if (z <= (-4.6d+21)) then
        tmp = 0.0d0 - x
    else if (z <= (-9.5d-70)) then
        tmp = t_0
    else if (z <= (-5.5d-301)) then
        tmp = x / z
    else if (z <= 4.6d-124) then
        tmp = t_0
    else if (z <= 5.2d0) then
        tmp = x / z
    else
        tmp = 0.0d0 - x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double t_0 = y * (x / z);
	double tmp;
	if (z <= -4.6e+21) {
		tmp = 0.0 - x;
	} else if (z <= -9.5e-70) {
		tmp = t_0;
	} else if (z <= -5.5e-301) {
		tmp = x / z;
	} else if (z <= 4.6e-124) {
		tmp = t_0;
	} else if (z <= 5.2) {
		tmp = x / z;
	} else {
		tmp = 0.0 - x;
	}
	return tmp;
}

Python

def code(x, y, z):
	t_0 = y * (x / z)
	tmp = 0
	if z <= -4.6e+21:
		tmp = 0.0 - x
	elif z <= -9.5e-70:
		tmp = t_0
	elif z <= -5.5e-301:
		tmp = x / z
	elif z <= 4.6e-124:
		tmp = t_0
	elif z <= 5.2:
		tmp = x / z
	else:
		tmp = 0.0 - x
	return tmp

Julia

function code(x, y, z)
	t_0 = Float64(y * Float64(x / z))
	tmp = 0.0
	if (z <= -4.6e+21)
		tmp = Float64(0.0 - x);
	elseif (z <= -9.5e-70)
		tmp = t_0;
	elseif (z <= -5.5e-301)
		tmp = Float64(x / z);
	elseif (z <= 4.6e-124)
		tmp = t_0;
	elseif (z <= 5.2)
		tmp = Float64(x / z);
	else
		tmp = Float64(0.0 - x);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	t_0 = y * (x / z);
	tmp = 0.0;
	if (z <= -4.6e+21)
		tmp = 0.0 - x;
	elseif (z <= -9.5e-70)
		tmp = t_0;
	elseif (z <= -5.5e-301)
		tmp = x / z;
	elseif (z <= 4.6e-124)
		tmp = t_0;
	elseif (z <= 5.2)
		tmp = x / z;
	else
		tmp = 0.0 - x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(y * N[(x / z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -4.6e+21], N[(0.0 - x), $MachinePrecision], If[LessEqual[z, -9.5e-70], t$95$0, If[LessEqual[z, -5.5e-301], N[(x / z), $MachinePrecision], If[LessEqual[z, 4.6e-124], t$95$0, If[LessEqual[z, 5.2], N[(x / z), $MachinePrecision], N[(0.0 - x), $MachinePrecision]]]]]]]

Derivation

1. Split input into 3 regimes

2. if z < -4.6e21 or 5.20000000000000018 < z

   1. Initial program 68.5%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.9%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.9%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in z around inf

      \[\leadsto \color{blue}{-1 \cdot x} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-sub0 N/A

         \[\leadsto 0 - \color{blue}{x} \]

      3. --lowering--.f64 76.7%

         \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{x}\right) \]

   7. Simplified 76.7%

      \[\leadsto \color{blue}{0 - x} \]
   8. Step-by-step derivation

      1. sub0-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-lowering-neg.f64 76.7%

         \[\leadsto \mathsf{neg.f64}\left(x\right) \]

   9. Applied egg-rr 76.7%

      \[\leadsto \color{blue}{-x} \]

   if -4.6e21 < z < -9.4999999999999994e-70 or -5.50000000000000005e-301 < z < 4.60000000000000024e-124

   1. Initial program 99.9%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto \frac{\left(\left(y - z\right) + 1\right) \cdot x}{z} \]

      2. associate-/l* N/A

         \[\leadsto \left(\left(y - z\right) + 1\right) \cdot \color{blue}{\frac{x}{z}} \]

      3. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\left(\left(y - z\right) + 1\right), \color{blue}{\left(\frac{x}{z}\right)}\right) \]

      4. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\left(y - z\right), 1\right), \left(\frac{\color{blue}{x}}{z}\right)\right) \]

      5. --lowering--.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right), \left(\frac{x}{z}\right)\right) \]

      6. /-lowering-/.f64 99.8%

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right), \mathsf{/.f64}\left(x, \color{blue}{z}\right)\right) \]

   4. Applied egg-rr 99.8%

      \[\leadsto \color{blue}{\left(\left(y - z\right) + 1\right) \cdot \frac{x}{z}} \]

   5. Taylor expanded in y around inf

      \[\leadsto \mathsf{*.f64}\left(\color{blue}{y}, \mathsf{/.f64}\left(x, z\right)\right) \]
   6. Step-by-step derivation

   7. Simplified 68.4%

      \[\leadsto \color{blue}{y} \cdot \frac{x}{z} \]

   if -9.4999999999999994e-70 < z < -5.50000000000000005e-301 or 4.60000000000000024e-124 < z < 5.20000000000000018

   1. Initial program 100.0%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 97.4%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 97.4%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around 0

      \[\leadsto \color{blue}{-1 \cdot \left(x \cdot \left(1 - \frac{1}{z}\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x \cdot \left(1 - \frac{1}{z}\right)\right) \]

      2. distribute-lft-out-- N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - x \cdot \frac{1}{z}\right)\right) \]

      3. associate-*r/ N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x \cdot 1}{z}\right)\right) \]

      4. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x}{z}\right)\right) \]

      5. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x - \frac{x}{z}\right)\right) \]

      6. unsub-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + \left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) \]

      7. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + -1 \cdot \frac{x}{z}\right)\right) \]

      8. +-commutative N/A

         \[\leadsto \mathsf{neg}\left(\left(-1 \cdot \frac{x}{z} + x\right)\right) \]

      9. distribute-neg-in N/A

         \[\leadsto \left(\mathsf{neg}\left(-1 \cdot \frac{x}{z}\right)\right) + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]

      10. mul-1-neg N/A

          \[\leadsto \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) + \left(\mathsf{neg}\left(x\right)\right) \]

      11. remove-double-neg N/A

          \[\leadsto \frac{x}{z} + \left(\mathsf{neg}\left(\color{blue}{x}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \frac{x}{z} - \color{blue}{x} \]

      13. --lowering--.f64 N/A

          \[\leadsto \mathsf{\_.f64}\left(\left(\frac{x}{z}\right), \color{blue}{x}\right) \]

      14. /-lowering-/.f64 68.7%

          \[\leadsto \mathsf{\_.f64}\left(\mathsf{/.f64}\left(x, z\right), x\right) \]

   7. Simplified 68.7%

      \[\leadsto \color{blue}{\frac{x}{z} - x} \]

   8. Taylor expanded in z around 0

      \[\leadsto \color{blue}{\frac{x}{z}} \]
   9. Step-by-step derivation

      1. /-lowering-/.f64 68.4%

         \[\leadsto \mathsf{/.f64}\left(x, \color{blue}{z}\right) \]

   10. Simplified 68.4%

       \[\leadsto \color{blue}{\frac{x}{z}} \]
3. Recombined 3 regimes into one program.

4. Final simplification 72.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -4.6 \cdot 10^{+21}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq -9.5 \cdot 10^{-70}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{elif}\;z \leq -5.5 \cdot 10^{-301}:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{elif}\;z \leq 4.6 \cdot 10^{-124}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{elif}\;z \leq 5.2:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;0 - x\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 64.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -3.6 \cdot 10^{+22}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq -1.95 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \mathbf{elif}\;z \leq 5.2:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;0 - x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (if (<= z -3.6e+22)
   (- 0.0 x)
   (if (<= z -1.95e-70) (* x (/ y z)) (if (<= z 5.2) (/ x z) (- 0.0 x)))))

C

double code(double x, double y, double z) {
	double tmp;
	if (z <= -3.6e+22) {
		tmp = 0.0 - x;
	} else if (z <= -1.95e-70) {
		tmp = x * (y / z);
	} else if (z <= 5.2) {
		tmp = x / z;
	} else {
		tmp = 0.0 - x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (z <= (-3.6d+22)) then
        tmp = 0.0d0 - x
    else if (z <= (-1.95d-70)) then
        tmp = x * (y / z)
    else if (z <= 5.2d0) then
        tmp = x / z
    else
        tmp = 0.0d0 - x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double tmp;
	if (z <= -3.6e+22) {
		tmp = 0.0 - x;
	} else if (z <= -1.95e-70) {
		tmp = x * (y / z);
	} else if (z <= 5.2) {
		tmp = x / z;
	} else {
		tmp = 0.0 - x;
	}
	return tmp;
}

Python

def code(x, y, z):
	tmp = 0
	if z <= -3.6e+22:
		tmp = 0.0 - x
	elif z <= -1.95e-70:
		tmp = x * (y / z)
	elif z <= 5.2:
		tmp = x / z
	else:
		tmp = 0.0 - x
	return tmp

Julia

function code(x, y, z)
	tmp = 0.0
	if (z <= -3.6e+22)
		tmp = Float64(0.0 - x);
	elseif (z <= -1.95e-70)
		tmp = Float64(x * Float64(y / z));
	elseif (z <= 5.2)
		tmp = Float64(x / z);
	else
		tmp = Float64(0.0 - x);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	tmp = 0.0;
	if (z <= -3.6e+22)
		tmp = 0.0 - x;
	elseif (z <= -1.95e-70)
		tmp = x * (y / z);
	elseif (z <= 5.2)
		tmp = x / z;
	else
		tmp = 0.0 - x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := If[LessEqual[z, -3.6e+22], N[(0.0 - x), $MachinePrecision], If[LessEqual[z, -1.95e-70], N[(x * N[(y / z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.2], N[(x / z), $MachinePrecision], N[(0.0 - x), $MachinePrecision]]]]

Derivation

1. Split input into 3 regimes

2. if z < -3.6e22 or 5.20000000000000018 < z

   1. Initial program 68.5%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.9%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.9%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in z around inf

      \[\leadsto \color{blue}{-1 \cdot x} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-sub0 N/A

         \[\leadsto 0 - \color{blue}{x} \]

      3. --lowering--.f64 76.7%

         \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{x}\right) \]

   7. Simplified 76.7%

      \[\leadsto \color{blue}{0 - x} \]
   8. Step-by-step derivation

      1. sub0-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-lowering-neg.f64 76.7%

         \[\leadsto \mathsf{neg.f64}\left(x\right) \]

   9. Applied egg-rr 76.7%

      \[\leadsto \color{blue}{-x} \]

   if -3.6e22 < z < -1.9500000000000001e-70

   1. Initial program 99.8%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 94.5%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 94.5%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around inf

      \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{y}{z}\right)}\right) \]
   6. Step-by-step derivation

      1. /-lowering-/.f64 57.1%

         \[\leadsto \mathsf{*.f64}\left(x, \mathsf{/.f64}\left(y, \color{blue}{z}\right)\right) \]

   7. Simplified 57.1%

      \[\leadsto x \cdot \color{blue}{\frac{y}{z}} \]

   if -1.9500000000000001e-70 < z < 5.20000000000000018

   1. Initial program 100.0%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 92.2%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 92.2%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around 0

      \[\leadsto \color{blue}{-1 \cdot \left(x \cdot \left(1 - \frac{1}{z}\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x \cdot \left(1 - \frac{1}{z}\right)\right) \]

      2. distribute-lft-out-- N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - x \cdot \frac{1}{z}\right)\right) \]

      3. associate-*r/ N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x \cdot 1}{z}\right)\right) \]

      4. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x}{z}\right)\right) \]

      5. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x - \frac{x}{z}\right)\right) \]

      6. unsub-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + \left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) \]

      7. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + -1 \cdot \frac{x}{z}\right)\right) \]

      8. +-commutative N/A

         \[\leadsto \mathsf{neg}\left(\left(-1 \cdot \frac{x}{z} + x\right)\right) \]

      9. distribute-neg-in N/A

         \[\leadsto \left(\mathsf{neg}\left(-1 \cdot \frac{x}{z}\right)\right) + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]

      10. mul-1-neg N/A

          \[\leadsto \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) + \left(\mathsf{neg}\left(x\right)\right) \]

      11. remove-double-neg N/A

          \[\leadsto \frac{x}{z} + \left(\mathsf{neg}\left(\color{blue}{x}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \frac{x}{z} - \color{blue}{x} \]

      13. --lowering--.f64 N/A

          \[\leadsto \mathsf{\_.f64}\left(\left(\frac{x}{z}\right), \color{blue}{x}\right) \]

      14. /-lowering-/.f64 61.2%

          \[\leadsto \mathsf{\_.f64}\left(\mathsf{/.f64}\left(x, z\right), x\right) \]

   7. Simplified 61.2%

      \[\leadsto \color{blue}{\frac{x}{z} - x} \]

   8. Taylor expanded in z around 0

      \[\leadsto \color{blue}{\frac{x}{z}} \]
   9. Step-by-step derivation

      1. /-lowering-/.f64 61.1%

         \[\leadsto \mathsf{/.f64}\left(x, \color{blue}{z}\right) \]

   10. Simplified 61.1%

       \[\leadsto \color{blue}{\frac{x}{z}} \]
3. Recombined 3 regimes into one program.

4. Final simplification 67.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.6 \cdot 10^{+22}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq -1.95 \cdot 10^{-70}:\\ \;\;\;\;x \cdot \frac{y}{z}\\ \mathbf{elif}\;z \leq 5.2:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;0 - x\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 86.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -6.5 \cdot 10^{+20}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq 3400:\\ \;\;\;\;\frac{x \cdot \left(y + 1\right)}{z}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{z} - x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (if (<= z -6.5e+20)
   (- 0.0 x)
   (if (<= z 3400.0) (/ (* x (+ y 1.0)) z) (- (/ x z) x))))

C

double code(double x, double y, double z) {
	double tmp;
	if (z <= -6.5e+20) {
		tmp = 0.0 - x;
	} else if (z <= 3400.0) {
		tmp = (x * (y + 1.0)) / z;
	} else {
		tmp = (x / z) - x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (z <= (-6.5d+20)) then
        tmp = 0.0d0 - x
    else if (z <= 3400.0d0) then
        tmp = (x * (y + 1.0d0)) / z
    else
        tmp = (x / z) - x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double tmp;
	if (z <= -6.5e+20) {
		tmp = 0.0 - x;
	} else if (z <= 3400.0) {
		tmp = (x * (y + 1.0)) / z;
	} else {
		tmp = (x / z) - x;
	}
	return tmp;
}

Python

def code(x, y, z):
	tmp = 0
	if z <= -6.5e+20:
		tmp = 0.0 - x
	elif z <= 3400.0:
		tmp = (x * (y + 1.0)) / z
	else:
		tmp = (x / z) - x
	return tmp

Julia

function code(x, y, z)
	tmp = 0.0
	if (z <= -6.5e+20)
		tmp = Float64(0.0 - x);
	elseif (z <= 3400.0)
		tmp = Float64(Float64(x * Float64(y + 1.0)) / z);
	else
		tmp = Float64(Float64(x / z) - x);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	tmp = 0.0;
	if (z <= -6.5e+20)
		tmp = 0.0 - x;
	elseif (z <= 3400.0)
		tmp = (x * (y + 1.0)) / z;
	else
		tmp = (x / z) - x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := If[LessEqual[z, -6.5e+20], N[(0.0 - x), $MachinePrecision], If[LessEqual[z, 3400.0], N[(N[(x * N[(y + 1.0), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision], N[(N[(x / z), $MachinePrecision] - x), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if z < -6.5e20

   1. Initial program 63.8%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.9%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.9%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in z around inf

      \[\leadsto \color{blue}{-1 \cdot x} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-sub0 N/A

         \[\leadsto 0 - \color{blue}{x} \]

      3. --lowering--.f64 80.1%

         \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{x}\right) \]

   7. Simplified 80.1%

      \[\leadsto \color{blue}{0 - x} \]
   8. Step-by-step derivation

      1. sub0-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-lowering-neg.f64 80.1%

         \[\leadsto \mathsf{neg.f64}\left(x\right) \]

   9. Applied egg-rr 80.1%

      \[\leadsto \color{blue}{-x} \]

   if -6.5e20 < z < 3400

   1. Initial program 99.9%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf

      \[\leadsto \mathsf{/.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\color{blue}{y}, 1\right)\right), z\right) \]
   4. Step-by-step derivation

   5. Simplified 98.9%

      \[\leadsto \frac{x \cdot \left(\color{blue}{y} + 1\right)}{z} \]

   if 3400 < z

   1. Initial program 74.1%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.9%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.9%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around 0

      \[\leadsto \color{blue}{-1 \cdot \left(x \cdot \left(1 - \frac{1}{z}\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x \cdot \left(1 - \frac{1}{z}\right)\right) \]

      2. distribute-lft-out-- N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - x \cdot \frac{1}{z}\right)\right) \]

      3. associate-*r/ N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x \cdot 1}{z}\right)\right) \]

      4. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x}{z}\right)\right) \]

      5. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x - \frac{x}{z}\right)\right) \]

      6. unsub-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + \left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) \]

      7. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + -1 \cdot \frac{x}{z}\right)\right) \]

      8. +-commutative N/A

         \[\leadsto \mathsf{neg}\left(\left(-1 \cdot \frac{x}{z} + x\right)\right) \]

      9. distribute-neg-in N/A

         \[\leadsto \left(\mathsf{neg}\left(-1 \cdot \frac{x}{z}\right)\right) + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]

      10. mul-1-neg N/A

          \[\leadsto \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) + \left(\mathsf{neg}\left(x\right)\right) \]

      11. remove-double-neg N/A

          \[\leadsto \frac{x}{z} + \left(\mathsf{neg}\left(\color{blue}{x}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \frac{x}{z} - \color{blue}{x} \]

      13. --lowering--.f64 N/A

          \[\leadsto \mathsf{\_.f64}\left(\left(\frac{x}{z}\right), \color{blue}{x}\right) \]

      14. /-lowering-/.f64 73.5%

          \[\leadsto \mathsf{\_.f64}\left(\mathsf{/.f64}\left(x, z\right), x\right) \]

   7. Simplified 73.5%

      \[\leadsto \color{blue}{\frac{x}{z} - x} \]
3. Recombined 3 regimes into one program.

4. Final simplification 89.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -6.5 \cdot 10^{+20}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq 3400:\\ \;\;\;\;\frac{x \cdot \left(y + 1\right)}{z}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{z} - x\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 85.1% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -116:\\ \;\;\;\;\frac{x \cdot y}{z}\\ \mathbf{elif}\;y \leq 8.4 \cdot 10^{+17}:\\ \;\;\;\;\frac{x}{z} - x\\ \mathbf{else}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (if (<= y -116.0)
   (/ (* x y) z)
   (if (<= y 8.4e+17) (- (/ x z) x) (* y (/ x z)))))

C

double code(double x, double y, double z) {
	double tmp;
	if (y <= -116.0) {
		tmp = (x * y) / z;
	} else if (y <= 8.4e+17) {
		tmp = (x / z) - x;
	} else {
		tmp = y * (x / z);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (y <= (-116.0d0)) then
        tmp = (x * y) / z
    else if (y <= 8.4d+17) then
        tmp = (x / z) - x
    else
        tmp = y * (x / z)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double tmp;
	if (y <= -116.0) {
		tmp = (x * y) / z;
	} else if (y <= 8.4e+17) {
		tmp = (x / z) - x;
	} else {
		tmp = y * (x / z);
	}
	return tmp;
}

Python

def code(x, y, z):
	tmp = 0
	if y <= -116.0:
		tmp = (x * y) / z
	elif y <= 8.4e+17:
		tmp = (x / z) - x
	else:
		tmp = y * (x / z)
	return tmp

Julia

function code(x, y, z)
	tmp = 0.0
	if (y <= -116.0)
		tmp = Float64(Float64(x * y) / z);
	elseif (y <= 8.4e+17)
		tmp = Float64(Float64(x / z) - x);
	else
		tmp = Float64(y * Float64(x / z));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	tmp = 0.0;
	if (y <= -116.0)
		tmp = (x * y) / z;
	elseif (y <= 8.4e+17)
		tmp = (x / z) - x;
	else
		tmp = y * (x / z);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := If[LessEqual[y, -116.0], N[(N[(x * y), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[y, 8.4e+17], N[(N[(x / z), $MachinePrecision] - x), $MachinePrecision], N[(y * N[(x / z), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if y < -116

   1. Initial program 87.7%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 92.3%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 92.3%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around inf

      \[\leadsto \color{blue}{\frac{x \cdot y}{z}} \]
   6. Step-by-step derivation

      1. /-lowering-/.f64 N/A

         \[\leadsto \mathsf{/.f64}\left(\left(x \cdot y\right), \color{blue}{z}\right) \]

      2. *-lowering-*.f64 74.7%

         \[\leadsto \mathsf{/.f64}\left(\mathsf{*.f64}\left(x, y\right), z\right) \]

   7. Simplified 74.7%

      \[\leadsto \color{blue}{\frac{x \cdot y}{z}} \]

   if -116 < y < 8.4e17

   1. Initial program 84.7%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.8%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.8%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around 0

      \[\leadsto \color{blue}{-1 \cdot \left(x \cdot \left(1 - \frac{1}{z}\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x \cdot \left(1 - \frac{1}{z}\right)\right) \]

      2. distribute-lft-out-- N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - x \cdot \frac{1}{z}\right)\right) \]

      3. associate-*r/ N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x \cdot 1}{z}\right)\right) \]

      4. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x}{z}\right)\right) \]

      5. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x - \frac{x}{z}\right)\right) \]

      6. unsub-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + \left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) \]

      7. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + -1 \cdot \frac{x}{z}\right)\right) \]

      8. +-commutative N/A

         \[\leadsto \mathsf{neg}\left(\left(-1 \cdot \frac{x}{z} + x\right)\right) \]

      9. distribute-neg-in N/A

         \[\leadsto \left(\mathsf{neg}\left(-1 \cdot \frac{x}{z}\right)\right) + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]

      10. mul-1-neg N/A

          \[\leadsto \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) + \left(\mathsf{neg}\left(x\right)\right) \]

      11. remove-double-neg N/A

          \[\leadsto \frac{x}{z} + \left(\mathsf{neg}\left(\color{blue}{x}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \frac{x}{z} - \color{blue}{x} \]

      13. --lowering--.f64 N/A

          \[\leadsto \mathsf{\_.f64}\left(\left(\frac{x}{z}\right), \color{blue}{x}\right) \]

      14. /-lowering-/.f64 96.7%

          \[\leadsto \mathsf{\_.f64}\left(\mathsf{/.f64}\left(x, z\right), x\right) \]

   7. Simplified 96.7%

      \[\leadsto \color{blue}{\frac{x}{z} - x} \]

   if 8.4e17 < y

   1. Initial program 87.6%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto \frac{\left(\left(y - z\right) + 1\right) \cdot x}{z} \]

      2. associate-/l* N/A

         \[\leadsto \left(\left(y - z\right) + 1\right) \cdot \color{blue}{\frac{x}{z}} \]

      3. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\left(\left(y - z\right) + 1\right), \color{blue}{\left(\frac{x}{z}\right)}\right) \]

      4. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\left(y - z\right), 1\right), \left(\frac{\color{blue}{x}}{z}\right)\right) \]

      5. --lowering--.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right), \left(\frac{x}{z}\right)\right) \]

      6. /-lowering-/.f64 92.9%

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right), \mathsf{/.f64}\left(x, \color{blue}{z}\right)\right) \]

   4. Applied egg-rr 92.9%

      \[\leadsto \color{blue}{\left(\left(y - z\right) + 1\right) \cdot \frac{x}{z}} \]

   5. Taylor expanded in y around inf

      \[\leadsto \mathsf{*.f64}\left(\color{blue}{y}, \mathsf{/.f64}\left(x, z\right)\right) \]
   6. Step-by-step derivation

   7. Simplified 77.5%

      \[\leadsto \color{blue}{y} \cdot \frac{x}{z} \]
3. Recombined 3 regimes into one program.
4. Add Preprocessing

Alternative 6: 85.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := y \cdot \frac{x}{z}\\ \mathbf{if}\;y \leq -6600:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;y \leq 1.15 \cdot 10^{+28}:\\ \;\;\;\;\frac{x}{z} - x\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* y (/ x z))))
   (if (<= y -6600.0) t_0 (if (<= y 1.15e+28) (- (/ x z) x) t_0))))

C

double code(double x, double y, double z) {
	double t_0 = y * (x / z);
	double tmp;
	if (y <= -6600.0) {
		tmp = t_0;
	} else if (y <= 1.15e+28) {
		tmp = (x / z) - x;
	} else {
		tmp = t_0;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = y * (x / z)
    if (y <= (-6600.0d0)) then
        tmp = t_0
    else if (y <= 1.15d+28) then
        tmp = (x / z) - x
    else
        tmp = t_0
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double t_0 = y * (x / z);
	double tmp;
	if (y <= -6600.0) {
		tmp = t_0;
	} else if (y <= 1.15e+28) {
		tmp = (x / z) - x;
	} else {
		tmp = t_0;
	}
	return tmp;
}

Python

def code(x, y, z):
	t_0 = y * (x / z)
	tmp = 0
	if y <= -6600.0:
		tmp = t_0
	elif y <= 1.15e+28:
		tmp = (x / z) - x
	else:
		tmp = t_0
	return tmp

Julia

function code(x, y, z)
	t_0 = Float64(y * Float64(x / z))
	tmp = 0.0
	if (y <= -6600.0)
		tmp = t_0;
	elseif (y <= 1.15e+28)
		tmp = Float64(Float64(x / z) - x);
	else
		tmp = t_0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	t_0 = y * (x / z);
	tmp = 0.0;
	if (y <= -6600.0)
		tmp = t_0;
	elseif (y <= 1.15e+28)
		tmp = (x / z) - x;
	else
		tmp = t_0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(y * N[(x / z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -6600.0], t$95$0, If[LessEqual[y, 1.15e+28], N[(N[(x / z), $MachinePrecision] - x), $MachinePrecision], t$95$0]]]

Derivation

1. Split input into 2 regimes

2. if y < -6600 or 1.14999999999999992e28 < y

   1. Initial program 87.6%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto \frac{\left(\left(y - z\right) + 1\right) \cdot x}{z} \]

      2. associate-/l* N/A

         \[\leadsto \left(\left(y - z\right) + 1\right) \cdot \color{blue}{\frac{x}{z}} \]

      3. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\left(\left(y - z\right) + 1\right), \color{blue}{\left(\frac{x}{z}\right)}\right) \]

      4. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\left(y - z\right), 1\right), \left(\frac{\color{blue}{x}}{z}\right)\right) \]

      5. --lowering--.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right), \left(\frac{x}{z}\right)\right) \]

      6. /-lowering-/.f64 90.8%

         \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right), \mathsf{/.f64}\left(x, \color{blue}{z}\right)\right) \]

   4. Applied egg-rr 90.8%

      \[\leadsto \color{blue}{\left(\left(y - z\right) + 1\right) \cdot \frac{x}{z}} \]

   5. Taylor expanded in y around inf

      \[\leadsto \mathsf{*.f64}\left(\color{blue}{y}, \mathsf{/.f64}\left(x, z\right)\right) \]
   6. Step-by-step derivation

   7. Simplified 75.0%

      \[\leadsto \color{blue}{y} \cdot \frac{x}{z} \]

   if -6600 < y < 1.14999999999999992e28

   1. Initial program 84.7%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.8%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.8%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around 0

      \[\leadsto \color{blue}{-1 \cdot \left(x \cdot \left(1 - \frac{1}{z}\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x \cdot \left(1 - \frac{1}{z}\right)\right) \]

      2. distribute-lft-out-- N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - x \cdot \frac{1}{z}\right)\right) \]

      3. associate-*r/ N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x \cdot 1}{z}\right)\right) \]

      4. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x}{z}\right)\right) \]

      5. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x - \frac{x}{z}\right)\right) \]

      6. unsub-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + \left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) \]

      7. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + -1 \cdot \frac{x}{z}\right)\right) \]

      8. +-commutative N/A

         \[\leadsto \mathsf{neg}\left(\left(-1 \cdot \frac{x}{z} + x\right)\right) \]

      9. distribute-neg-in N/A

         \[\leadsto \left(\mathsf{neg}\left(-1 \cdot \frac{x}{z}\right)\right) + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]

      10. mul-1-neg N/A

          \[\leadsto \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) + \left(\mathsf{neg}\left(x\right)\right) \]

      11. remove-double-neg N/A

          \[\leadsto \frac{x}{z} + \left(\mathsf{neg}\left(\color{blue}{x}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \frac{x}{z} - \color{blue}{x} \]

      13. --lowering--.f64 N/A

          \[\leadsto \mathsf{\_.f64}\left(\left(\frac{x}{z}\right), \color{blue}{x}\right) \]

      14. /-lowering-/.f64 96.7%

          \[\leadsto \mathsf{\_.f64}\left(\mathsf{/.f64}\left(x, z\right), x\right) \]

   7. Simplified 96.7%

      \[\leadsto \color{blue}{\frac{x}{z} - x} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 7: 93.9% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(y - z\right) + 1\\ \mathbf{if}\;x \leq 2 \cdot 10^{+14}:\\ \;\;\;\;\frac{x \cdot t\_0}{z}\\ \mathbf{else}:\\ \;\;\;\;\frac{x}{\frac{z}{t\_0}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (+ (- y z) 1.0)))
   (if (<= x 2e+14) (/ (* x t_0) z) (/ x (/ z t_0)))))

C

double code(double x, double y, double z) {
	double t_0 = (y - z) + 1.0;
	double tmp;
	if (x <= 2e+14) {
		tmp = (x * t_0) / z;
	} else {
		tmp = x / (z / t_0);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = (y - z) + 1.0d0
    if (x <= 2d+14) then
        tmp = (x * t_0) / z
    else
        tmp = x / (z / t_0)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double t_0 = (y - z) + 1.0;
	double tmp;
	if (x <= 2e+14) {
		tmp = (x * t_0) / z;
	} else {
		tmp = x / (z / t_0);
	}
	return tmp;
}

Python

def code(x, y, z):
	t_0 = (y - z) + 1.0
	tmp = 0
	if x <= 2e+14:
		tmp = (x * t_0) / z
	else:
		tmp = x / (z / t_0)
	return tmp

Julia

function code(x, y, z)
	t_0 = Float64(Float64(y - z) + 1.0)
	tmp = 0.0
	if (x <= 2e+14)
		tmp = Float64(Float64(x * t_0) / z);
	else
		tmp = Float64(x / Float64(z / t_0));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	t_0 = (y - z) + 1.0;
	tmp = 0.0;
	if (x <= 2e+14)
		tmp = (x * t_0) / z;
	else
		tmp = x / (z / t_0);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(N[(y - z), $MachinePrecision] + 1.0), $MachinePrecision]}, If[LessEqual[x, 2e+14], N[(N[(x * t$95$0), $MachinePrecision] / z), $MachinePrecision], N[(x / N[(z / t$95$0), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if x < 2e14

   1. Initial program 91.1%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing

   if 2e14 < x

   1. Initial program 71.2%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. clear-num N/A

         \[\leadsto x \cdot \frac{1}{\color{blue}{\frac{z}{\left(y - z\right) + 1}}} \]

      3. un-div-inv N/A

         \[\leadsto \frac{x}{\color{blue}{\frac{z}{\left(y - z\right) + 1}}} \]

      4. /-lowering-/.f64 N/A

         \[\leadsto \mathsf{/.f64}\left(x, \color{blue}{\left(\frac{z}{\left(y - z\right) + 1}\right)}\right) \]

      5. /-lowering-/.f64 N/A

         \[\leadsto \mathsf{/.f64}\left(x, \mathsf{/.f64}\left(z, \color{blue}{\left(\left(y - z\right) + 1\right)}\right)\right) \]

      6. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{/.f64}\left(x, \mathsf{/.f64}\left(z, \mathsf{+.f64}\left(\left(y - z\right), \color{blue}{1}\right)\right)\right) \]

      7. --lowering--.f64 99.9%

         \[\leadsto \mathsf{/.f64}\left(x, \mathsf{/.f64}\left(z, \mathsf{+.f64}\left(\mathsf{\_.f64}\left(y, z\right), 1\right)\right)\right) \]

   4. Applied egg-rr 99.9%

      \[\leadsto \color{blue}{\frac{x}{\frac{z}{\left(y - z\right) + 1}}} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 8: 64.4% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.6 \cdot 10^{+20}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq 5.2:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;0 - x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (if (<= z -1.6e+20) (- 0.0 x) (if (<= z 5.2) (/ x z) (- 0.0 x))))

C

double code(double x, double y, double z) {
	double tmp;
	if (z <= -1.6e+20) {
		tmp = 0.0 - x;
	} else if (z <= 5.2) {
		tmp = x / z;
	} else {
		tmp = 0.0 - x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (z <= (-1.6d+20)) then
        tmp = 0.0d0 - x
    else if (z <= 5.2d0) then
        tmp = x / z
    else
        tmp = 0.0d0 - x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double tmp;
	if (z <= -1.6e+20) {
		tmp = 0.0 - x;
	} else if (z <= 5.2) {
		tmp = x / z;
	} else {
		tmp = 0.0 - x;
	}
	return tmp;
}

Python

def code(x, y, z):
	tmp = 0
	if z <= -1.6e+20:
		tmp = 0.0 - x
	elif z <= 5.2:
		tmp = x / z
	else:
		tmp = 0.0 - x
	return tmp

Julia

function code(x, y, z)
	tmp = 0.0
	if (z <= -1.6e+20)
		tmp = Float64(0.0 - x);
	elseif (z <= 5.2)
		tmp = Float64(x / z);
	else
		tmp = Float64(0.0 - x);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	tmp = 0.0;
	if (z <= -1.6e+20)
		tmp = 0.0 - x;
	elseif (z <= 5.2)
		tmp = x / z;
	else
		tmp = 0.0 - x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := If[LessEqual[z, -1.6e+20], N[(0.0 - x), $MachinePrecision], If[LessEqual[z, 5.2], N[(x / z), $MachinePrecision], N[(0.0 - x), $MachinePrecision]]]

Derivation

1. Split input into 2 regimes

2. if z < -1.6e20 or 5.20000000000000018 < z

   1. Initial program 68.7%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 99.9%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 99.9%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in z around inf

      \[\leadsto \color{blue}{-1 \cdot x} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-sub0 N/A

         \[\leadsto 0 - \color{blue}{x} \]

      3. --lowering--.f64 76.1%

         \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{x}\right) \]

   7. Simplified 76.1%

      \[\leadsto \color{blue}{0 - x} \]
   8. Step-by-step derivation

      1. sub0-neg N/A

         \[\leadsto \mathsf{neg}\left(x\right) \]

      2. neg-lowering-neg.f64 76.1%

         \[\leadsto \mathsf{neg.f64}\left(x\right) \]

   9. Applied egg-rr 76.1%

      \[\leadsto \color{blue}{-x} \]

   if -1.6e20 < z < 5.20000000000000018

   1. Initial program 99.9%

      \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
   2. Step-by-step derivation

      1. associate-/l* N/A

         \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

      2. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

      3. associate-+l- N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

      4. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

      5. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

      6. +-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

      7. div-sub N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      8. sub-neg N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      9. *-inverses N/A

         \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

      10. distribute-neg-frac N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

      11. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

      13. associate-+l- N/A

          \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      14. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

      15. metadata-eval N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

      16. div-sub N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

      17. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

      18. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

      19. /-lowering-/.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

      20. distribute-neg-in N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

      21. sub-neg N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

      22. --lowering--.f64 N/A

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

      23. metadata-eval 92.5%

          \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

   3. Simplified 92.5%

      \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
   4. Add Preprocessing

   5. Taylor expanded in y around 0

      \[\leadsto \color{blue}{-1 \cdot \left(x \cdot \left(1 - \frac{1}{z}\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(x \cdot \left(1 - \frac{1}{z}\right)\right) \]

      2. distribute-lft-out-- N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - x \cdot \frac{1}{z}\right)\right) \]

      3. associate-*r/ N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x \cdot 1}{z}\right)\right) \]

      4. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x \cdot 1 - \frac{x}{z}\right)\right) \]

      5. *-rgt-identity N/A

         \[\leadsto \mathsf{neg}\left(\left(x - \frac{x}{z}\right)\right) \]

      6. unsub-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + \left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) \]

      7. mul-1-neg N/A

         \[\leadsto \mathsf{neg}\left(\left(x + -1 \cdot \frac{x}{z}\right)\right) \]

      8. +-commutative N/A

         \[\leadsto \mathsf{neg}\left(\left(-1 \cdot \frac{x}{z} + x\right)\right) \]

      9. distribute-neg-in N/A

         \[\leadsto \left(\mathsf{neg}\left(-1 \cdot \frac{x}{z}\right)\right) + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]

      10. mul-1-neg N/A

          \[\leadsto \left(\mathsf{neg}\left(\left(\mathsf{neg}\left(\frac{x}{z}\right)\right)\right)\right) + \left(\mathsf{neg}\left(x\right)\right) \]

      11. remove-double-neg N/A

          \[\leadsto \frac{x}{z} + \left(\mathsf{neg}\left(\color{blue}{x}\right)\right) \]

      12. sub-neg N/A

          \[\leadsto \frac{x}{z} - \color{blue}{x} \]

      13. --lowering--.f64 N/A

          \[\leadsto \mathsf{\_.f64}\left(\left(\frac{x}{z}\right), \color{blue}{x}\right) \]

      14. /-lowering-/.f64 58.2%

          \[\leadsto \mathsf{\_.f64}\left(\mathsf{/.f64}\left(x, z\right), x\right) \]

   7. Simplified 58.2%

      \[\leadsto \color{blue}{\frac{x}{z} - x} \]

   8. Taylor expanded in z around 0

      \[\leadsto \color{blue}{\frac{x}{z}} \]
   9. Step-by-step derivation

      1. /-lowering-/.f64 57.2%

         \[\leadsto \mathsf{/.f64}\left(x, \color{blue}{z}\right) \]

   10. Simplified 57.2%

       \[\leadsto \color{blue}{\frac{x}{z}} \]
3. Recombined 2 regimes into one program.

4. Final simplification 65.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.6 \cdot 10^{+20}:\\ \;\;\;\;0 - x\\ \mathbf{elif}\;z \leq 5.2:\\ \;\;\;\;\frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;0 - x\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 38.9% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ 0 - x \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (- 0.0 x))

C

double code(double x, double y, double z) {
	return 0.0 - x;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = 0.0d0 - x
end function

Java

public static double code(double x, double y, double z) {
	return 0.0 - x;
}

Python

def code(x, y, z):
	return 0.0 - x

Julia

function code(x, y, z)
	return Float64(0.0 - x)
end

MATLAB

function tmp = code(x, y, z)
	tmp = 0.0 - x;
end

Wolfram

code[x_, y_, z_] := N[(0.0 - x), $MachinePrecision]

Derivation

1. Initial program 86.0%

   \[\frac{x \cdot \left(\left(y - z\right) + 1\right)}{z} \]
2. Step-by-step derivation

   1. associate-/l* N/A

      \[\leadsto x \cdot \color{blue}{\frac{\left(y - z\right) + 1}{z}} \]

   2. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{\left(y - z\right) + 1}{z}\right)}\right) \]

   3. associate-+l- N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y - \left(z - 1\right)}{z}\right)\right) \]

   4. div-sub N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} - \color{blue}{\frac{z - 1}{z}}\right)\right) \]

   5. sub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\frac{y}{z} + \color{blue}{\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right)}\right)\right) \]

   6. +-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\frac{z - 1}{z}\right)\right) + \color{blue}{\frac{y}{z}}\right)\right) \]

   7. div-sub N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} - \frac{1}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

   8. sub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(\frac{z}{z} + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

   9. *-inverses N/A

      \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \left(\mathsf{neg}\left(\frac{1}{z}\right)\right)\right)\right)\right) + \frac{y}{z}\right)\right) \]

   10. distribute-neg-frac N/A

       \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(\left(1 + \frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{y}{z}\right)\right) \]

   11. distribute-neg-in N/A

       \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(\frac{\mathsf{neg}\left(1\right)}{z}\right)\right)\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

   12. sub-neg N/A

       \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\left(\mathsf{neg}\left(1\right)\right) - \frac{\mathsf{neg}\left(1\right)}{z}\right) + \frac{\color{blue}{y}}{z}\right)\right) \]

   13. associate-+l- N/A

       \[\leadsto \mathsf{*.f64}\left(x, \left(\left(\mathsf{neg}\left(1\right)\right) - \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

   14. --lowering--.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), \color{blue}{\left(\frac{\mathsf{neg}\left(1\right)}{z} - \frac{y}{z}\right)}\right)\right) \]

   15. metadata-eval N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\color{blue}{\frac{\mathsf{neg}\left(1\right)}{z}} - \frac{y}{z}\right)\right)\right) \]

   16. div-sub N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) - y}{\color{blue}{z}}\right)\right)\right) \]

   17. sub-neg N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)}{z}\right)\right)\right) \]

   18. distribute-neg-in N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \left(\frac{\mathsf{neg}\left(\left(1 + y\right)\right)}{z}\right)\right)\right) \]

   19. /-lowering-/.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\mathsf{neg}\left(\left(1 + y\right)\right)\right), \color{blue}{z}\right)\right)\right) \]

   20. distribute-neg-in N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) + \left(\mathsf{neg}\left(y\right)\right)\right), z\right)\right)\right) \]

   21. sub-neg N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\left(\left(\mathsf{neg}\left(1\right)\right) - y\right), z\right)\right)\right) \]

   22. --lowering--.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(\mathsf{neg}\left(1\right)\right), y\right), z\right)\right)\right) \]

   23. metadata-eval 95.8%

       \[\leadsto \mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(-1, \mathsf{/.f64}\left(\mathsf{\_.f64}\left(-1, y\right), z\right)\right)\right) \]

3. Simplified 95.8%

   \[\leadsto \color{blue}{x \cdot \left(-1 - \frac{-1 - y}{z}\right)} \]
4. Add Preprocessing

5. Taylor expanded in z around inf

   \[\leadsto \color{blue}{-1 \cdot x} \]
6. Step-by-step derivation

   1. mul-1-neg N/A

      \[\leadsto \mathsf{neg}\left(x\right) \]

   2. neg-sub0 N/A

      \[\leadsto 0 - \color{blue}{x} \]

   3. --lowering--.f64 35.8%

      \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{x}\right) \]

7. Simplified 35.8%

   \[\leadsto \color{blue}{0 - x} \]
8. Step-by-step derivation

   1. sub0-neg N/A

      \[\leadsto \mathsf{neg}\left(x\right) \]

   2. neg-lowering-neg.f64 35.8%

      \[\leadsto \mathsf{neg.f64}\left(x\right) \]

9. Applied egg-rr 35.8%

   \[\leadsto \color{blue}{-x} \]

10. Final simplification 35.8%

    \[\leadsto 0 - x \]
11. Add Preprocessing

Developer Target 1: 99.5% accurate, 0.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 + y\right) \cdot \frac{x}{z} - x\\ \mathbf{if}\;x < -2.71483106713436 \cdot 10^{-162}:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;x < 3.874108816439546 \cdot 10^{-197}:\\ \;\;\;\;\left(x \cdot \left(\left(y - z\right) + 1\right)\right) \cdot \frac{1}{z}\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (- (* (+ 1.0 y) (/ x z)) x)))
   (if (< x -2.71483106713436e-162)
     t_0
     (if (< x 3.874108816439546e-197)
       (* (* x (+ (- y z) 1.0)) (/ 1.0 z))
       t_0))))

C

double code(double x, double y, double z) {
	double t_0 = ((1.0 + y) * (x / z)) - x;
	double tmp;
	if (x < -2.71483106713436e-162) {
		tmp = t_0;
	} else if (x < 3.874108816439546e-197) {
		tmp = (x * ((y - z) + 1.0)) * (1.0 / z);
	} else {
		tmp = t_0;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = ((1.0d0 + y) * (x / z)) - x
    if (x < (-2.71483106713436d-162)) then
        tmp = t_0
    else if (x < 3.874108816439546d-197) then
        tmp = (x * ((y - z) + 1.0d0)) * (1.0d0 / z)
    else
        tmp = t_0
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	double t_0 = ((1.0 + y) * (x / z)) - x;
	double tmp;
	if (x < -2.71483106713436e-162) {
		tmp = t_0;
	} else if (x < 3.874108816439546e-197) {
		tmp = (x * ((y - z) + 1.0)) * (1.0 / z);
	} else {
		tmp = t_0;
	}
	return tmp;
}

Python

def code(x, y, z):
	t_0 = ((1.0 + y) * (x / z)) - x
	tmp = 0
	if x < -2.71483106713436e-162:
		tmp = t_0
	elif x < 3.874108816439546e-197:
		tmp = (x * ((y - z) + 1.0)) * (1.0 / z)
	else:
		tmp = t_0
	return tmp

Julia

function code(x, y, z)
	t_0 = Float64(Float64(Float64(1.0 + y) * Float64(x / z)) - x)
	tmp = 0.0
	if (x < -2.71483106713436e-162)
		tmp = t_0;
	elseif (x < 3.874108816439546e-197)
		tmp = Float64(Float64(x * Float64(Float64(y - z) + 1.0)) * Float64(1.0 / z));
	else
		tmp = t_0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z)
	t_0 = ((1.0 + y) * (x / z)) - x;
	tmp = 0.0;
	if (x < -2.71483106713436e-162)
		tmp = t_0;
	elseif (x < 3.874108816439546e-197)
		tmp = (x * ((y - z) + 1.0)) * (1.0 / z);
	else
		tmp = t_0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := Block[{t$95$0 = N[(N[(N[(1.0 + y), $MachinePrecision] * N[(x / z), $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision]}, If[Less[x, -2.71483106713436e-162], t$95$0, If[Less[x, 3.874108816439546e-197], N[(N[(x * N[(N[(y - z), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] * N[(1.0 / z), $MachinePrecision]), $MachinePrecision], t$95$0]]]

Reproduce

herbie shell --seed 2024161 
(FPCore (x y z)
  :name "Diagrams.TwoD.Segment.Bernstein:evaluateBernstein from diagrams-lib-1.3.0.3"
  :precision binary64

  :alt
  (! :herbie-platform default (if (< x -67870776678359/25000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (- (* (+ 1 y) (/ x z)) x) (if (< x 1937054408219773/50000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (* (* x (+ (- y z) 1)) (/ 1 z)) (- (* (+ 1 y) (/ x z)) x))))

  (/ (* x (+ (- y z) 1.0)) z))