Cancel like terms

Average Accuracy: 54.4% → 100.0%

Time: 801.0ms

Precision: binary64

Cost: 64

Math

\[\left(1 + x\right) - x \]

↓

\[1 \]

FPCore

(FPCore (x) :precision binary64 (- (+ 1.0 x) x))

↓

(FPCore (x) :precision binary64 1.0)

C

double code(double x) {
	return (1.0 + x) - x;
}

↓

double code(double x) {
	return 1.0;
}

Fortran

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

↓

real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0
end function

Java

public static double code(double x) {
	return (1.0 + x) - x;
}

↓

public static double code(double x) {
	return 1.0;
}

Python

def code(x):
	return (1.0 + x) - x

↓

def code(x):
	return 1.0

Julia

function code(x)
	return Float64(Float64(1.0 + x) - x)
end

↓

function code(x)
	return 1.0
end

MATLAB

function tmp = code(x)
	tmp = (1.0 + x) - x;
end

↓

function tmp = code(x)
	tmp = 1.0;
end

Wolfram

code[x_] := N[(N[(1.0 + x), $MachinePrecision] - x), $MachinePrecision]

↓

code[x_] := 1.0

Derivation

1. Initial program 54.4%

   \[\left(1 + x\right) - x \]

2. Simplified 100.0%

   \[\leadsto \color{blue}{1} \]
   Proof

   [Start] 54.4	\[ \left(1 + x\right) - x \]
   associate--l+ [=>] 100.0	\[ \color{blue}{1 + \left(x - x\right)} \]
   +-inverses [=>] 100.0	\[ 1 + \color{blue}{0} \]
   metadata-eval [=>] 100.0	\[ \color{blue}{1} \]

3. Final simplification 100.0%

   \[\leadsto 1 \]

Reproduce

herbie shell --seed 2023143 
(FPCore (x)
  :name "Cancel like terms"
  :precision binary64
  (- (+ 1.0 x) x))