2frac (problem 3.3.1)

Average Accuracy: 77.6% → 99.9%

Time: 4.5s

Precision: binary64

Cost: 448

Math

\[\frac{1}{x + 1} - \frac{1}{x} \]

↓

\[\frac{\frac{1}{-1 - x}}{x} \]

FPCore

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

↓

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

C

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

↓

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

Fortran

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

↓

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

Java

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

↓

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

Python

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

↓

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

Julia

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

↓

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

MATLAB

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

↓

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

Wolfram

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

↓

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

Derivation

1. Initial program 77.6%

   \[\frac{1}{x + 1} - \frac{1}{x} \]

2. Applied egg-rr 78.6%

   \[\leadsto \color{blue}{\frac{\frac{x + \left(-1 - x\right)}{1 + x}}{x}} \]
   Proof

   [Start] 77.6	\[ \frac{1}{x + 1} - \frac{1}{x} \]
   frac-sub [=>] 78.6	\[ \color{blue}{\frac{1 \cdot x - \left(x + 1\right) \cdot 1}{\left(x + 1\right) \cdot x}} \]
   associate-/r* [=>] 78.6	\[ \color{blue}{\frac{\frac{1 \cdot x - \left(x + 1\right) \cdot 1}{x + 1}}{x}} \]
   *-un-lft-identity [<=] 78.6	\[ \frac{\frac{\color{blue}{x} - \left(x + 1\right) \cdot 1}{x + 1}}{x} \]
   cancel-sign-sub-inv [=>] 78.6	\[ \frac{\frac{\color{blue}{x + \left(-\left(x + 1\right)\right) \cdot 1}}{x + 1}}{x} \]
   *-commutative [<=] 78.6	\[ \frac{\frac{x + \color{blue}{1 \cdot \left(-\left(x + 1\right)\right)}}{x + 1}}{x} \]
   *-un-lft-identity [<=] 78.6	\[ \frac{\frac{x + \color{blue}{\left(-\left(x + 1\right)\right)}}{x + 1}}{x} \]
   +-commutative [=>] 78.6	\[ \frac{\frac{x + \left(-\color{blue}{\left(1 + x\right)}\right)}{x + 1}}{x} \]
   distribute-neg-in [=>] 78.6	\[ \frac{\frac{x + \color{blue}{\left(\left(-1\right) + \left(-x\right)\right)}}{x + 1}}{x} \]
   neg-sub0 [=>] 78.6	\[ \frac{\frac{x + \left(\left(-1\right) + \color{blue}{\left(0 - x\right)}\right)}{x + 1}}{x} \]
   metadata-eval [<=] 78.6	\[ \frac{\frac{x + \left(\left(-1\right) + \left(\color{blue}{\log 1} - x\right)\right)}{x + 1}}{x} \]
   associate-+r- [=>] 78.6	\[ \frac{\frac{x + \color{blue}{\left(\left(\left(-1\right) + \log 1\right) - x\right)}}{x + 1}}{x} \]
   metadata-eval [=>] 78.6	\[ \frac{\frac{x + \left(\left(\color{blue}{-1} + \log 1\right) - x\right)}{x + 1}}{x} \]
   metadata-eval [=>] 78.6	\[ \frac{\frac{x + \left(\left(-1 + \color{blue}{0}\right) - x\right)}{x + 1}}{x} \]
   metadata-eval [=>] 78.6	\[ \frac{\frac{x + \left(\color{blue}{-1} - x\right)}{x + 1}}{x} \]
   +-commutative [=>] 78.6	\[ \frac{\frac{x + \left(-1 - x\right)}{\color{blue}{1 + x}}}{x} \]

3. Applied egg-rr 99.9%

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

   [Start] 78.6	\[ \frac{\frac{x + \left(-1 - x\right)}{1 + x}}{x} \]
   frac-2neg [=>] 78.6	\[ \frac{\color{blue}{\frac{-\left(x + \left(-1 - x\right)\right)}{-\left(1 + x\right)}}}{x} \]
   distribute-neg-in [=>] 78.6	\[ \frac{\frac{-\left(x + \left(-1 - x\right)\right)}{\color{blue}{\left(-1\right) + \left(-x\right)}}}{x} \]
   metadata-eval [=>] 78.6	\[ \frac{\frac{-\left(x + \left(-1 - x\right)\right)}{\color{blue}{-1} + \left(-x\right)}}{x} \]
   sub-neg [<=] 78.6	\[ \frac{\frac{-\left(x + \left(-1 - x\right)\right)}{\color{blue}{-1 - x}}}{x} \]
   div-inv [=>] 78.6	\[ \frac{\color{blue}{\left(-\left(x + \left(-1 - x\right)\right)\right) \cdot \frac{1}{-1 - x}}}{x} \]
   neg-sub0 [=>] 78.6	\[ \frac{\color{blue}{\left(0 - \left(x + \left(-1 - x\right)\right)\right)} \cdot \frac{1}{-1 - x}}{x} \]
   metadata-eval [<=] 78.6	\[ \frac{\left(\color{blue}{\log 1} - \left(x + \left(-1 - x\right)\right)\right) \cdot \frac{1}{-1 - x}}{x} \]
   +-commutative [=>] 78.6	\[ \frac{\left(\log 1 - \color{blue}{\left(\left(-1 - x\right) + x\right)}\right) \cdot \frac{1}{-1 - x}}{x} \]
   associate-+l- [=>] 99.9	\[ \frac{\left(\log 1 - \color{blue}{\left(-1 - \left(x - x\right)\right)}\right) \cdot \frac{1}{-1 - x}}{x} \]
   associate--r- [=>] 99.9	\[ \frac{\color{blue}{\left(\left(\log 1 - -1\right) + \left(x - x\right)\right)} \cdot \frac{1}{-1 - x}}{x} \]
   metadata-eval [=>] 99.9	\[ \frac{\left(\left(\color{blue}{0} - -1\right) + \left(x - x\right)\right) \cdot \frac{1}{-1 - x}}{x} \]
   metadata-eval [=>] 99.9	\[ \frac{\left(\color{blue}{1} + \left(x - x\right)\right) \cdot \frac{1}{-1 - x}}{x} \]

4. Simplified 99.9%

   \[\leadsto \frac{\color{blue}{\frac{1}{-1 - x}}}{x} \]
   Proof

   [Start] 99.9	\[ \frac{\left(1 + \left(x - x\right)\right) \cdot \frac{1}{-1 - x}}{x} \]
   +-commutative [=>] 99.9	\[ \frac{\color{blue}{\left(\left(x - x\right) + 1\right)} \cdot \frac{1}{-1 - x}}{x} \]
   +-inverses [=>] 99.9	\[ \frac{\left(\color{blue}{0} + 1\right) \cdot \frac{1}{-1 - x}}{x} \]
   metadata-eval [=>] 99.9	\[ \frac{\color{blue}{1} \cdot \frac{1}{-1 - x}}{x} \]
   *-lft-identity [=>] 99.9	\[ \frac{\color{blue}{\frac{1}{-1 - x}}}{x} \]

5. Final simplification 99.9%

   \[\leadsto \frac{\frac{1}{-1 - x}}{x} \]

Alternatives

Alternative 1
Accuracy	98.4%
Cost	713

\[\begin{array}{l} \mathbf{if}\;x \leq -1 \lor \neg \left(x \leq 1\right):\\ \;\;\;\;\frac{\frac{-1}{x}}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(1 - x\right) - \frac{1}{x}\\ \end{array} \]

Alternative 2
Accuracy	97.8%
Cost	585

\[\begin{array}{l} \mathbf{if}\;x \leq -1 \lor \neg \left(x \leq 0.76\right):\\ \;\;\;\;\frac{-1}{x \cdot x}\\ \mathbf{else}:\\ \;\;\;\;1 + \frac{-1}{x}\\ \end{array} \]

Alternative 3
Accuracy	98.2%
Cost	585

\[\begin{array}{l} \mathbf{if}\;x \leq -1 \lor \neg \left(x \leq 0.76\right):\\ \;\;\;\;\frac{\frac{-1}{x}}{x}\\ \mathbf{else}:\\ \;\;\;\;1 + \frac{-1}{x}\\ \end{array} \]

Alternative 4
Accuracy	51.9%
Cost	192

\[\frac{-1}{x} \]

Alternative 5
Accuracy	3.2%
Cost	128

\[-x \]

Alternative 6
Accuracy	2.9%
Cost	64

\[1 \]

Reproduce

herbie shell --seed 2023140 
(FPCore (x)
  :name "2frac (problem 3.3.1)"
  :precision binary64
  (- (/ 1.0 (+ x 1.0)) (/ 1.0 x)))