Graphics.Rendering.Chart.Plot.Pie:renderPie from Chart-1.5.3

Average Accuracy: 53.3% → 100.0%

Time: 2.1s

Precision: binary64

Cost: 64

Math

\[\left(x + y\right) - x \]

↓

\[y \]

FPCore

(FPCore (x y) :precision binary64 (- (+ x y) x))

↓

(FPCore (x y) :precision binary64 y)

C

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

↓

double code(double x, double y) {
	return y;
}

Fortran

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

↓

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

Java

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

↓

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

Python

def code(x, y):
	return (x + y) - x

↓

def code(x, y):
	return y

Julia

function code(x, y)
	return Float64(Float64(x + y) - x)
end

↓

function code(x, y)
	return y
end

MATLAB

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

↓

function tmp = code(x, y)
	tmp = y;
end

Wolfram

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

↓

code[x_, y_] := y

Target

Original	53.3%
Target	100.0%
Herbie	100.0%

\[y - 0 \]

Derivation

1. Initial program 53.5%

   \[\left(x + y\right) - x \]

2. Simplified 100.0%

   \[\leadsto \color{blue}{y} \]
   Proof

   [Start] 53.5	\[ \left(x + y\right) - x \]
   +-commutative [=>] 53.5	\[ \color{blue}{\left(y + x\right)} - x \]
   associate--l+ [=>] 100.0	\[ \color{blue}{y + \left(x - x\right)} \]
   +-inverses [=>] 100.0	\[ y + \color{blue}{0} \]
   +-rgt-identity [=>] 100.0	\[ \color{blue}{y} \]

3. Final simplification 100.0%

   \[\leadsto y \]

Reproduce

herbie shell --seed 2023160 
(FPCore (x y)
  :name "Graphics.Rendering.Chart.Plot.Pie:renderPie from Chart-1.5.3"
  :precision binary64

  :herbie-target
  (- y 0.0)

  (- (+ x y) x))