ReportTypes:explainFloat from gipeda-0.1.2.1

Average Accuracy: 100.0% → 100.0%

Time: 975.0ms

Precision: binary64

Cost: 64

Math

\[100 \cdot \frac{x - x}{x} \]

↓

\[0 \]

FPCore

(FPCore (x) :precision binary64 (* 100.0 (/ (- x x) x)))

↓

(FPCore (x) :precision binary64 0.0)

C

double code(double x) {
	return 100.0 * ((x - x) / x);
}

↓

double code(double x) {
	return 0.0;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = 100.0d0 * ((x - x) / x)
end function

↓

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

Java

public static double code(double x) {
	return 100.0 * ((x - x) / x);
}

↓

public static double code(double x) {
	return 0.0;
}

Python

def code(x):
	return 100.0 * ((x - x) / x)

↓

def code(x):
	return 0.0

Julia

function code(x)
	return Float64(100.0 * Float64(Float64(x - x) / x))
end

↓

function code(x)
	return 0.0
end

MATLAB

function tmp = code(x)
	tmp = 100.0 * ((x - x) / x);
end

↓

function tmp = code(x)
	tmp = 0.0;
end

Wolfram

code[x_] := N[(100.0 * N[(N[(x - x), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]

↓

code[x_] := 0.0

Target

Original	100.0%
Target	100.0%
Herbie	100.0%

\[0 \]

Derivation

1. Initial program 100.0%

   \[100 \cdot \frac{x - x}{x} \]

2. Simplified 100.0%

   \[\leadsto \color{blue}{0} \]
   Proof

   [Start] 100.0	\[ 100 \cdot \frac{x - x}{x} \]
   div-sub [=>] 100.0	\[ 100 \cdot \color{blue}{\left(\frac{x}{x} - \frac{x}{x}\right)} \]
   +-inverses [=>] 100.0	\[ 100 \cdot \color{blue}{0} \]
   metadata-eval [=>] 100.0	\[ \color{blue}{0} \]

3. Final simplification 100.0%

   \[\leadsto 0 \]

Reproduce

herbie shell --seed 2023151 
(FPCore (x)
  :name "ReportTypes:explainFloat from gipeda-0.1.2.1"
  :precision binary64

  :herbie-target
  0.0

  (* 100.0 (/ (- x x) x)))