Text.Parsec.Token:makeTokenParser from parsec-3.1.9, B

Average Accuracy: 100.0% → 100.0%

Time: 2.4s

Precision: binary64

Cost: 448

Math

\[\left(x + y\right) \cdot z \]

↓

\[z \cdot x + z \cdot y \]

FPCore

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

↓

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

C

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

↓

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

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
end function

↓

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

Java

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

↓

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

Python

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

↓

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

Julia

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

↓

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

MATLAB

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

↓

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

Wolfram

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

↓

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

Derivation

1. Initial program 100.0%

   \[\left(x + y\right) \cdot z \]

2. Applied egg-rr 100.0%

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

   [Start] 100.0	\[ \left(x + y\right) \cdot z \]
   *-commutative [=>] 100.0	\[ \color{blue}{z \cdot \left(x + y\right)} \]
   +-commutative [=>] 100.0	\[ z \cdot \color{blue}{\left(y + x\right)} \]
   distribute-lft-in [=>] 100.0	\[ \color{blue}{z \cdot y + z \cdot x} \]

3. Final simplification 100.0%

   \[\leadsto z \cdot x + z \cdot y \]

Alternatives

Alternative 1
Accuracy	63.6%
Cost	854

\[\begin{array}{l} \mathbf{if}\;y \leq 2 \cdot 10^{-94} \lor \neg \left(y \leq 1.85 \cdot 10^{-56}\right) \land \left(y \leq 2.8 \cdot 10^{-40} \lor \neg \left(y \leq 3.3 \cdot 10^{+27}\right) \land y \leq 3.8 \cdot 10^{+48}\right):\\ \;\;\;\;z \cdot x\\ \mathbf{else}:\\ \;\;\;\;z \cdot y\\ \end{array} \]

Alternative 2
Accuracy	100.0%
Cost	320

\[z \cdot \left(y + x\right) \]

Alternative 3
Accuracy	52.8%
Cost	192

\[z \cdot y \]

Reproduce

herbie shell --seed 2023147 
(FPCore (x y z)
  :name "Text.Parsec.Token:makeTokenParser from parsec-3.1.9, B"
  :precision binary64
  (* (+ x y) z))