Numeric.SpecFunctions:choose from math-functions-0.1.5.2

Percentage Accurate: 84.1% → 96.6%

Time: 7.1s

Alternatives: 6

Speedup: 1.0×

Specification

Math

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

FPCore

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

C

double code(double x, double y, double z) {
	return (x * (y + z)) / 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)) / z
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 84.1% accurate, 1.0× speedup

Math

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

FPCore

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

C

double code(double x, double y, double z) {
	return (x * (y + z)) / 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)) / z
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 96.6% accurate, 0.4× speedup

Math

\[\begin{array}{l} x\_m = \left|x\right| \\ x\_s = \mathsf{copysign}\left(1, x\right) \\ x\_s \cdot \begin{array}{l} \mathbf{if}\;\frac{x\_m \cdot \left(y + z\right)}{z} \leq -1 \cdot 10^{+87}:\\ \;\;\;\;\left(y + z\right) \cdot \frac{x\_m}{z}\\ \mathbf{else}:\\ \;\;\;\;x\_m \cdot \left(1 + \frac{y}{z}\right)\\ \end{array} \end{array} \]

FPCore

x\_m = (fabs.f64 x)
x\_s = (copysign.f64 #s(literal 1 binary64) x)
(FPCore (x_s x_m y z)
 :precision binary64
 (*
  x_s
  (if (<= (/ (* x_m (+ y z)) z) -1e+87)
    (* (+ y z) (/ x_m z))
    (* x_m (+ 1.0 (/ y z))))))

C

x\_m = fabs(x);
x\_s = copysign(1.0, x);
double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (((x_m * (y + z)) / z) <= -1e+87) {
		tmp = (y + z) * (x_m / z);
	} else {
		tmp = x_m * (1.0 + (y / z));
	}
	return x_s * tmp;
}

Fortran

x\_m = abs(x)
x\_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m, y, z)
    real(8), intent (in) :: x_s
    real(8), intent (in) :: x_m
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (((x_m * (y + z)) / z) <= (-1d+87)) then
        tmp = (y + z) * (x_m / z)
    else
        tmp = x_m * (1.0d0 + (y / z))
    end if
    code = x_s * tmp
end function

Java

x\_m = Math.abs(x);
x\_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (((x_m * (y + z)) / z) <= -1e+87) {
		tmp = (y + z) * (x_m / z);
	} else {
		tmp = x_m * (1.0 + (y / z));
	}
	return x_s * tmp;
}

Python

x\_m = math.fabs(x)
x\_s = math.copysign(1.0, x)
def code(x_s, x_m, y, z):
	tmp = 0
	if ((x_m * (y + z)) / z) <= -1e+87:
		tmp = (y + z) * (x_m / z)
	else:
		tmp = x_m * (1.0 + (y / z))
	return x_s * tmp

Julia

x\_m = abs(x)
x\_s = copysign(1.0, x)
function code(x_s, x_m, y, z)
	tmp = 0.0
	if (Float64(Float64(x_m * Float64(y + z)) / z) <= -1e+87)
		tmp = Float64(Float64(y + z) * Float64(x_m / z));
	else
		tmp = Float64(x_m * Float64(1.0 + Float64(y / z)));
	end
	return Float64(x_s * tmp)
end

MATLAB

x\_m = abs(x);
x\_s = sign(x) * abs(1.0);
function tmp_2 = code(x_s, x_m, y, z)
	tmp = 0.0;
	if (((x_m * (y + z)) / z) <= -1e+87)
		tmp = (y + z) * (x_m / z);
	else
		tmp = x_m * (1.0 + (y / z));
	end
	tmp_2 = x_s * tmp;
end

Wolfram

x\_m = N[Abs[x], $MachinePrecision]
x\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_, y_, z_] := N[(x$95$s * If[LessEqual[N[(N[(x$95$m * N[(y + z), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision], -1e+87], N[(N[(y + z), $MachinePrecision] * N[(x$95$m / z), $MachinePrecision]), $MachinePrecision], N[(x$95$m * N[(1.0 + N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]), $MachinePrecision]

Derivation

1. Split input into 2 regimes

2. if (/.f64 (*.f64 x (+.f64 y z)) z) < -9.9999999999999996e86

   1. Initial program 73.7%

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

      1. clear-num N/A

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

      2. associate-/r/ N/A

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

      3. associate-*r* N/A

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

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

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

      5. associate-*l/ N/A

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

      6. *-lft-identity N/A

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

      7. /-lowering-/.f64 N/A

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

      8. +-lowering-+.f64 92.9%

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

   4. Applied egg-rr 92.9%

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

   if -9.9999999999999996e86 < (/.f64 (*.f64 x (+.f64 y z)) z)

   1. Initial program 86.7%

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

      1. associate-/l* N/A

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

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

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

      3. *-lft-identity N/A

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

      4. *-inverses N/A

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

      5. associate-*l/ N/A

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

      6. distribute-lft-in N/A

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

      7. associate-*l/ N/A

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

      8. *-inverses N/A

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

      9. *-lft-identity N/A

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

      10. *-inverses N/A

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

      11. lft-mult-inverse N/A

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

      12. *-inverses N/A

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

      13. +-commutative N/A

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

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

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

      15. *-inverses N/A

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

      16. *-rgt-identity N/A

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

      17. *-inverses N/A

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

      18. associate-/l* N/A

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

      19. associate-*l/ N/A

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

      20. *-commutative N/A

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

      21. /-lowering-/.f64 N/A

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

      22. *-commutative N/A

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

      23. associate-*l/ N/A

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

      24. associate-/l* N/A

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

      25. *-inverses N/A

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

      26. *-rgt-identity 97.3%

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

   3. Simplified 97.3%

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

4. Final simplification 96.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x \cdot \left(y + z\right)}{z} \leq -1 \cdot 10^{+87}:\\ \;\;\;\;\left(y + z\right) \cdot \frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(1 + \frac{y}{z}\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 72.8% accurate, 0.5× speedup

Math

\[\begin{array}{l} x\_m = \left|x\right| \\ x\_s = \mathsf{copysign}\left(1, x\right) \\ x\_s \cdot \begin{array}{l} \mathbf{if}\;z \leq -1.16 \cdot 10^{+21}:\\ \;\;\;\;x\_m\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{-61}:\\ \;\;\;\;\frac{x\_m \cdot y}{z}\\ \mathbf{else}:\\ \;\;\;\;x\_m\\ \end{array} \end{array} \]

FPCore

x\_m = (fabs.f64 x)
x\_s = (copysign.f64 #s(literal 1 binary64) x)
(FPCore (x_s x_m y z)
 :precision binary64
 (* x_s (if (<= z -1.16e+21) x_m (if (<= z 1.05e-61) (/ (* x_m y) z) x_m))))

C

x\_m = fabs(x);
x\_s = copysign(1.0, x);
double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (z <= -1.16e+21) {
		tmp = x_m;
	} else if (z <= 1.05e-61) {
		tmp = (x_m * y) / z;
	} else {
		tmp = x_m;
	}
	return x_s * tmp;
}

Fortran

x\_m = abs(x)
x\_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m, y, z)
    real(8), intent (in) :: x_s
    real(8), intent (in) :: x_m
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (z <= (-1.16d+21)) then
        tmp = x_m
    else if (z <= 1.05d-61) then
        tmp = (x_m * y) / z
    else
        tmp = x_m
    end if
    code = x_s * tmp
end function

Java

x\_m = Math.abs(x);
x\_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (z <= -1.16e+21) {
		tmp = x_m;
	} else if (z <= 1.05e-61) {
		tmp = (x_m * y) / z;
	} else {
		tmp = x_m;
	}
	return x_s * tmp;
}

Python

x\_m = math.fabs(x)
x\_s = math.copysign(1.0, x)
def code(x_s, x_m, y, z):
	tmp = 0
	if z <= -1.16e+21:
		tmp = x_m
	elif z <= 1.05e-61:
		tmp = (x_m * y) / z
	else:
		tmp = x_m
	return x_s * tmp

Julia

x\_m = abs(x)
x\_s = copysign(1.0, x)
function code(x_s, x_m, y, z)
	tmp = 0.0
	if (z <= -1.16e+21)
		tmp = x_m;
	elseif (z <= 1.05e-61)
		tmp = Float64(Float64(x_m * y) / z);
	else
		tmp = x_m;
	end
	return Float64(x_s * tmp)
end

MATLAB

x\_m = abs(x);
x\_s = sign(x) * abs(1.0);
function tmp_2 = code(x_s, x_m, y, z)
	tmp = 0.0;
	if (z <= -1.16e+21)
		tmp = x_m;
	elseif (z <= 1.05e-61)
		tmp = (x_m * y) / z;
	else
		tmp = x_m;
	end
	tmp_2 = x_s * tmp;
end

Wolfram

x\_m = N[Abs[x], $MachinePrecision]
x\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_, y_, z_] := N[(x$95$s * If[LessEqual[z, -1.16e+21], x$95$m, If[LessEqual[z, 1.05e-61], N[(N[(x$95$m * y), $MachinePrecision] / z), $MachinePrecision], x$95$m]]), $MachinePrecision]

Derivation

1. Split input into 2 regimes

2. if z < -1.16e21 or 1.05e-61 < z

   1. Initial program 70.1%

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

      1. associate-/l* N/A

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

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

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

      3. *-lft-identity N/A

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

      4. *-inverses N/A

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

      5. associate-*l/ N/A

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

      6. distribute-lft-in N/A

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

      7. associate-*l/ N/A

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

      8. *-inverses N/A

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

      9. *-lft-identity N/A

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

      10. *-inverses N/A

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

      11. lft-mult-inverse N/A

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

      12. *-inverses N/A

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

      13. +-commutative N/A

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

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

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

      15. *-inverses N/A

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

      16. *-rgt-identity N/A

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

      17. *-inverses N/A

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

      18. associate-/l* N/A

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

      19. associate-*l/ N/A

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

      20. *-commutative N/A

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

      21. /-lowering-/.f64 N/A

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

      22. *-commutative N/A

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

      23. associate-*l/ N/A

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

      24. associate-/l* N/A

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

      25. *-inverses N/A

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

      26. *-rgt-identity 99.9%

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

   3. Simplified 99.9%

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

   5. Taylor expanded in y around 0

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

   7. Simplified 77.8%

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

   if -1.16e21 < z < 1.05e-61

   1. Initial program 95.3%

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

   3. Taylor expanded in y around inf

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

      1. *-lowering-*.f64 76.6%

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

   5. Simplified 76.6%

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

Alternative 3: 72.5% accurate, 0.5× speedup

Math

\[\begin{array}{l} x\_m = \left|x\right| \\ x\_s = \mathsf{copysign}\left(1, x\right) \\ x\_s \cdot \begin{array}{l} \mathbf{if}\;z \leq -7 \cdot 10^{+20}:\\ \;\;\;\;x\_m\\ \mathbf{elif}\;z \leq 4.6 \cdot 10^{-63}:\\ \;\;\;\;y \cdot \frac{x\_m}{z}\\ \mathbf{else}:\\ \;\;\;\;x\_m\\ \end{array} \end{array} \]

FPCore

x\_m = (fabs.f64 x)
x\_s = (copysign.f64 #s(literal 1 binary64) x)
(FPCore (x_s x_m y z)
 :precision binary64
 (* x_s (if (<= z -7e+20) x_m (if (<= z 4.6e-63) (* y (/ x_m z)) x_m))))

C

x\_m = fabs(x);
x\_s = copysign(1.0, x);
double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (z <= -7e+20) {
		tmp = x_m;
	} else if (z <= 4.6e-63) {
		tmp = y * (x_m / z);
	} else {
		tmp = x_m;
	}
	return x_s * tmp;
}

Fortran

x\_m = abs(x)
x\_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m, y, z)
    real(8), intent (in) :: x_s
    real(8), intent (in) :: x_m
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (z <= (-7d+20)) then
        tmp = x_m
    else if (z <= 4.6d-63) then
        tmp = y * (x_m / z)
    else
        tmp = x_m
    end if
    code = x_s * tmp
end function

Java

x\_m = Math.abs(x);
x\_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (z <= -7e+20) {
		tmp = x_m;
	} else if (z <= 4.6e-63) {
		tmp = y * (x_m / z);
	} else {
		tmp = x_m;
	}
	return x_s * tmp;
}

Python

x\_m = math.fabs(x)
x\_s = math.copysign(1.0, x)
def code(x_s, x_m, y, z):
	tmp = 0
	if z <= -7e+20:
		tmp = x_m
	elif z <= 4.6e-63:
		tmp = y * (x_m / z)
	else:
		tmp = x_m
	return x_s * tmp

Julia

x\_m = abs(x)
x\_s = copysign(1.0, x)
function code(x_s, x_m, y, z)
	tmp = 0.0
	if (z <= -7e+20)
		tmp = x_m;
	elseif (z <= 4.6e-63)
		tmp = Float64(y * Float64(x_m / z));
	else
		tmp = x_m;
	end
	return Float64(x_s * tmp)
end

MATLAB

x\_m = abs(x);
x\_s = sign(x) * abs(1.0);
function tmp_2 = code(x_s, x_m, y, z)
	tmp = 0.0;
	if (z <= -7e+20)
		tmp = x_m;
	elseif (z <= 4.6e-63)
		tmp = y * (x_m / z);
	else
		tmp = x_m;
	end
	tmp_2 = x_s * tmp;
end

Wolfram

x\_m = N[Abs[x], $MachinePrecision]
x\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_, y_, z_] := N[(x$95$s * If[LessEqual[z, -7e+20], x$95$m, If[LessEqual[z, 4.6e-63], N[(y * N[(x$95$m / z), $MachinePrecision]), $MachinePrecision], x$95$m]]), $MachinePrecision]

Derivation

1. Split input into 2 regimes

2. if z < -7e20 or 4.6e-63 < z

   1. Initial program 70.1%

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

      1. associate-/l* N/A

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

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

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

      3. *-lft-identity N/A

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

      4. *-inverses N/A

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

      5. associate-*l/ N/A

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

      6. distribute-lft-in N/A

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

      7. associate-*l/ N/A

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

      8. *-inverses N/A

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

      9. *-lft-identity N/A

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

      10. *-inverses N/A

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

      11. lft-mult-inverse N/A

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

      12. *-inverses N/A

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

      13. +-commutative N/A

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

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

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

      15. *-inverses N/A

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

      16. *-rgt-identity N/A

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

      17. *-inverses N/A

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

      18. associate-/l* N/A

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

      19. associate-*l/ N/A

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

      20. *-commutative N/A

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

      21. /-lowering-/.f64 N/A

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

      22. *-commutative N/A

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

      23. associate-*l/ N/A

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

      24. associate-/l* N/A

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

      25. *-inverses N/A

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

      26. *-rgt-identity 99.9%

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

   3. Simplified 99.9%

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

   5. Taylor expanded in y around 0

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

   7. Simplified 77.8%

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

   if -7e20 < z < 4.6e-63

   1. Initial program 95.3%

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

      1. associate-/l* N/A

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

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

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

      3. *-lft-identity N/A

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

      4. *-inverses N/A

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

      5. associate-*l/ N/A

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

      6. distribute-lft-in N/A

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

      7. associate-*l/ N/A

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

      8. *-inverses N/A

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

      9. *-lft-identity N/A

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

      10. *-inverses N/A

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

      11. lft-mult-inverse N/A

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

      12. *-inverses N/A

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

      13. +-commutative N/A

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

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

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

      15. *-inverses N/A

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

      16. *-rgt-identity N/A

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

      17. *-inverses N/A

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

      18. associate-/l* N/A

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

      19. associate-*l/ N/A

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

      20. *-commutative N/A

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

      21. /-lowering-/.f64 N/A

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

      22. *-commutative N/A

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

      23. associate-*l/ N/A

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

      24. associate-/l* N/A

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

      25. *-inverses N/A

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

      26. *-rgt-identity 92.1%

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

   3. Simplified 92.1%

      \[\leadsto \color{blue}{x \cdot \left(1 + \frac{y}{z}\right)} \]
   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 70.5%

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

   7. Simplified 70.5%

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

      1. associate-*r/ N/A

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

      2. associate-*l/ N/A

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

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

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

      4. /-lowering-/.f64 76.2%

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

   9. Applied egg-rr 76.2%

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

4. Final simplification 76.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7 \cdot 10^{+20}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 4.6 \cdot 10^{-63}:\\ \;\;\;\;y \cdot \frac{x}{z}\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 70.5% accurate, 0.5× speedup

Math

\[\begin{array}{l} x\_m = \left|x\right| \\ x\_s = \mathsf{copysign}\left(1, x\right) \\ x\_s \cdot \begin{array}{l} \mathbf{if}\;z \leq -1.8 \cdot 10^{+21}:\\ \;\;\;\;x\_m\\ \mathbf{elif}\;z \leq 4.5 \cdot 10^{-64}:\\ \;\;\;\;x\_m \cdot \frac{y}{z}\\ \mathbf{else}:\\ \;\;\;\;x\_m\\ \end{array} \end{array} \]

FPCore

x\_m = (fabs.f64 x)
x\_s = (copysign.f64 #s(literal 1 binary64) x)
(FPCore (x_s x_m y z)
 :precision binary64
 (* x_s (if (<= z -1.8e+21) x_m (if (<= z 4.5e-64) (* x_m (/ y z)) x_m))))

C

x\_m = fabs(x);
x\_s = copysign(1.0, x);
double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (z <= -1.8e+21) {
		tmp = x_m;
	} else if (z <= 4.5e-64) {
		tmp = x_m * (y / z);
	} else {
		tmp = x_m;
	}
	return x_s * tmp;
}

Fortran

x\_m = abs(x)
x\_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m, y, z)
    real(8), intent (in) :: x_s
    real(8), intent (in) :: x_m
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (z <= (-1.8d+21)) then
        tmp = x_m
    else if (z <= 4.5d-64) then
        tmp = x_m * (y / z)
    else
        tmp = x_m
    end if
    code = x_s * tmp
end function

Java

x\_m = Math.abs(x);
x\_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m, double y, double z) {
	double tmp;
	if (z <= -1.8e+21) {
		tmp = x_m;
	} else if (z <= 4.5e-64) {
		tmp = x_m * (y / z);
	} else {
		tmp = x_m;
	}
	return x_s * tmp;
}

Python

x\_m = math.fabs(x)
x\_s = math.copysign(1.0, x)
def code(x_s, x_m, y, z):
	tmp = 0
	if z <= -1.8e+21:
		tmp = x_m
	elif z <= 4.5e-64:
		tmp = x_m * (y / z)
	else:
		tmp = x_m
	return x_s * tmp

Julia

x\_m = abs(x)
x\_s = copysign(1.0, x)
function code(x_s, x_m, y, z)
	tmp = 0.0
	if (z <= -1.8e+21)
		tmp = x_m;
	elseif (z <= 4.5e-64)
		tmp = Float64(x_m * Float64(y / z));
	else
		tmp = x_m;
	end
	return Float64(x_s * tmp)
end

MATLAB

x\_m = abs(x);
x\_s = sign(x) * abs(1.0);
function tmp_2 = code(x_s, x_m, y, z)
	tmp = 0.0;
	if (z <= -1.8e+21)
		tmp = x_m;
	elseif (z <= 4.5e-64)
		tmp = x_m * (y / z);
	else
		tmp = x_m;
	end
	tmp_2 = x_s * tmp;
end

Wolfram

x\_m = N[Abs[x], $MachinePrecision]
x\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_, y_, z_] := N[(x$95$s * If[LessEqual[z, -1.8e+21], x$95$m, If[LessEqual[z, 4.5e-64], N[(x$95$m * N[(y / z), $MachinePrecision]), $MachinePrecision], x$95$m]]), $MachinePrecision]

Derivation

1. Split input into 2 regimes

2. if z < -1.8e21 or 4.5000000000000001e-64 < z

   1. Initial program 70.1%

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

      1. associate-/l* N/A

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

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

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

      3. *-lft-identity N/A

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

      4. *-inverses N/A

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

      5. associate-*l/ N/A

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

      6. distribute-lft-in N/A

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

      7. associate-*l/ N/A

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

      8. *-inverses N/A

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

      9. *-lft-identity N/A

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

      10. *-inverses N/A

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

      11. lft-mult-inverse N/A

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

      12. *-inverses N/A

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

      13. +-commutative N/A

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

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

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

      15. *-inverses N/A

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

      16. *-rgt-identity N/A

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

      17. *-inverses N/A

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

      18. associate-/l* N/A

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

      19. associate-*l/ N/A

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

      20. *-commutative N/A

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

      21. /-lowering-/.f64 N/A

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

      22. *-commutative N/A

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

      23. associate-*l/ N/A

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

      24. associate-/l* N/A

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

      25. *-inverses N/A

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

      26. *-rgt-identity 99.9%

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

   3. Simplified 99.9%

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

   5. Taylor expanded in y around 0

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

   7. Simplified 77.8%

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

   if -1.8e21 < z < 4.5000000000000001e-64

   1. Initial program 95.3%

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

      1. associate-/l* N/A

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

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

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

      3. *-lft-identity N/A

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

      4. *-inverses N/A

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

      5. associate-*l/ N/A

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

      6. distribute-lft-in N/A

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

      7. associate-*l/ N/A

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

      8. *-inverses N/A

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

      9. *-lft-identity N/A

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

      10. *-inverses N/A

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

      11. lft-mult-inverse N/A

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

      12. *-inverses N/A

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

      13. +-commutative N/A

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

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

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

      15. *-inverses N/A

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

      16. *-rgt-identity N/A

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

      17. *-inverses N/A

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

      18. associate-/l* N/A

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

      19. associate-*l/ N/A

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

      20. *-commutative N/A

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

      21. /-lowering-/.f64 N/A

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

      22. *-commutative N/A

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

      23. associate-*l/ N/A

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

      24. associate-/l* N/A

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

      25. *-inverses N/A

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

      26. *-rgt-identity 92.1%

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

   3. Simplified 92.1%

      \[\leadsto \color{blue}{x \cdot \left(1 + \frac{y}{z}\right)} \]
   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 70.5%

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

   7. Simplified 70.5%

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

Alternative 5: 95.7% accurate, 1.0× speedup

Math

\[\begin{array}{l} x\_m = \left|x\right| \\ x\_s = \mathsf{copysign}\left(1, x\right) \\ x\_s \cdot \left(x\_m \cdot \left(1 + \frac{y}{z}\right)\right) \end{array} \]

FPCore

x\_m = (fabs.f64 x)
x\_s = (copysign.f64 #s(literal 1 binary64) x)
(FPCore (x_s x_m y z) :precision binary64 (* x_s (* x_m (+ 1.0 (/ y z)))))

C

x\_m = fabs(x);
x\_s = copysign(1.0, x);
double code(double x_s, double x_m, double y, double z) {
	return x_s * (x_m * (1.0 + (y / z)));
}

Fortran

x\_m = abs(x)
x\_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m, y, z)
    real(8), intent (in) :: x_s
    real(8), intent (in) :: x_m
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x_s * (x_m * (1.0d0 + (y / z)))
end function

Java

x\_m = Math.abs(x);
x\_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m, double y, double z) {
	return x_s * (x_m * (1.0 + (y / z)));
}

Python

x\_m = math.fabs(x)
x\_s = math.copysign(1.0, x)
def code(x_s, x_m, y, z):
	return x_s * (x_m * (1.0 + (y / z)))

Julia

x\_m = abs(x)
x\_s = copysign(1.0, x)
function code(x_s, x_m, y, z)
	return Float64(x_s * Float64(x_m * Float64(1.0 + Float64(y / z))))
end

MATLAB

x\_m = abs(x);
x\_s = sign(x) * abs(1.0);
function tmp = code(x_s, x_m, y, z)
	tmp = x_s * (x_m * (1.0 + (y / z)));
end

Wolfram

x\_m = N[Abs[x], $MachinePrecision]
x\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_, y_, z_] := N[(x$95$s * N[(x$95$m * N[(1.0 + N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 83.3%

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

   1. associate-/l* N/A

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

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

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

   3. *-lft-identity N/A

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

   4. *-inverses N/A

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

   5. associate-*l/ N/A

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

   6. distribute-lft-in N/A

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

   7. associate-*l/ N/A

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

   8. *-inverses N/A

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

   9. *-lft-identity N/A

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

   10. *-inverses N/A

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

   11. lft-mult-inverse N/A

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

   12. *-inverses N/A

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

   13. +-commutative N/A

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

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

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

   15. *-inverses N/A

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

   16. *-rgt-identity N/A

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

   17. *-inverses N/A

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

   18. associate-/l* N/A

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

   19. associate-*l/ N/A

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

   20. *-commutative N/A

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

   21. /-lowering-/.f64 N/A

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

   22. *-commutative N/A

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

   23. associate-*l/ N/A

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

   24. associate-/l* N/A

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

   25. *-inverses N/A

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

   26. *-rgt-identity 95.8%

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

3. Simplified 95.8%

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

Alternative 6: 51.4% accurate, 7.0× speedup

Math

\[\begin{array}{l} x\_m = \left|x\right| \\ x\_s = \mathsf{copysign}\left(1, x\right) \\ x\_s \cdot x\_m \end{array} \]

FPCore

x\_m = (fabs.f64 x)
x\_s = (copysign.f64 #s(literal 1 binary64) x)
(FPCore (x_s x_m y z) :precision binary64 (* x_s x_m))

C

x\_m = fabs(x);
x\_s = copysign(1.0, x);
double code(double x_s, double x_m, double y, double z) {
	return x_s * x_m;
}

Fortran

x\_m = abs(x)
x\_s = copysign(1.0d0, x)
real(8) function code(x_s, x_m, y, z)
    real(8), intent (in) :: x_s
    real(8), intent (in) :: x_m
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x_s * x_m
end function

Java

x\_m = Math.abs(x);
x\_s = Math.copySign(1.0, x);
public static double code(double x_s, double x_m, double y, double z) {
	return x_s * x_m;
}

Python

x\_m = math.fabs(x)
x\_s = math.copysign(1.0, x)
def code(x_s, x_m, y, z):
	return x_s * x_m

Julia

x\_m = abs(x)
x\_s = copysign(1.0, x)
function code(x_s, x_m, y, z)
	return Float64(x_s * x_m)
end

MATLAB

x\_m = abs(x);
x\_s = sign(x) * abs(1.0);
function tmp = code(x_s, x_m, y, z)
	tmp = x_s * x_m;
end

Wolfram

x\_m = N[Abs[x], $MachinePrecision]
x\_s = N[With[{TMP1 = Abs[1.0], TMP2 = Sign[x]}, TMP1 * If[TMP2 == 0, 1, TMP2]], $MachinePrecision]
code[x$95$s_, x$95$m_, y_, z_] := N[(x$95$s * x$95$m), $MachinePrecision]

Derivation

1. Initial program 83.3%

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

   1. associate-/l* N/A

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

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

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

   3. *-lft-identity N/A

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

   4. *-inverses N/A

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

   5. associate-*l/ N/A

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

   6. distribute-lft-in N/A

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

   7. associate-*l/ N/A

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

   8. *-inverses N/A

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

   9. *-lft-identity N/A

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

   10. *-inverses N/A

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

   11. lft-mult-inverse N/A

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

   12. *-inverses N/A

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

   13. +-commutative N/A

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

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

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

   15. *-inverses N/A

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

   16. *-rgt-identity N/A

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

   17. *-inverses N/A

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

   18. associate-/l* N/A

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

   19. associate-*l/ N/A

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

   20. *-commutative N/A

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

   21. /-lowering-/.f64 N/A

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

   22. *-commutative N/A

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

   23. associate-*l/ N/A

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

   24. associate-/l* N/A

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

   25. *-inverses N/A

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

   26. *-rgt-identity 95.8%

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

3. Simplified 95.8%

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

5. Taylor expanded in y around 0

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

7. Simplified 49.4%

   \[\leadsto \color{blue}{x} \]
8. Add Preprocessing

Developer Target 1: 96.0% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{x}{\frac{z}{y + z}} \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (/ x (/ z (+ y z))))

C

double code(double x, double y, double z) {
	return x / (z / (y + 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 / (z / (y + z))
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Reproduce

herbie shell --seed 2024161 
(FPCore (x y z)
  :name "Numeric.SpecFunctions:choose from math-functions-0.1.5.2"
  :precision binary64

  :alt
  (! :herbie-platform default (/ x (/ z (+ y z))))

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