2frac (problem 3.3.1)

Percentage Accurate: 77.3% → 99.9%

Time: 4.5s

Alternatives: 8

Speedup: 1.3×

Specification

Math

\[\begin{array}{l} \\ \frac{1}{x + 1} - \frac{1}{x} \end{array} \]

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 77.3% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{1}{x + 1} - \frac{1}{x} \end{array} \]

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 99.9% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \frac{\frac{-1}{x + 1}}{x} \end{array} \]

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 77.8%

   \[\frac{1}{x + 1} - \frac{1}{x} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. frac-sub 79.4%

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

   2. *-rgt-identity 79.4%

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

   3. metadata-eval 79.4%

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

   4. div-inv 79.4%

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

   5. associate-/r* 79.4%

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

   6. *-un-lft-identity 79.4%

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

   7. *-rgt-identity 79.4%

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

   8. +-commutative 79.4%

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

   9. div-inv 79.4%

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

   10. metadata-eval 79.4%

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

   11. *-rgt-identity 79.4%

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

   12. +-commutative 79.4%

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

4. Applied egg-rr 79.4%

   \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
5. Step-by-step derivation

   1. div-sub 77.8%

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

   2. *-inverses 77.8%

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

   3. sub-neg 77.8%

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

   4. +-commutative 77.8%

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

   5. metadata-eval 77.8%

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

6. Applied egg-rr 77.8%

   \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
7. Step-by-step derivation

   1. metadata-eval 77.8%

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

   2. sub-neg 77.8%

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

   3. *-inverses 77.8%

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

   4. div-sub 79.4%

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

   5. associate--r+ 99.9%

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

   6. +-inverses 99.9%

      \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

   7. metadata-eval 99.9%

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

8. Simplified 99.9%

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

9. Final simplification 99.9%

   \[\leadsto \frac{\frac{-1}{x + 1}}{x} \]
10. Add Preprocessing

Alternative 2: 75.4% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;0\\ \mathbf{elif}\;x \leq 3.8 \cdot 10^{+61}:\\ \;\;\;\;\left(1 - x\right) + \frac{-1}{x}\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (if (<= x -1.0) 0.0 (if (<= x 3.8e+61) (+ (- 1.0 x) (/ -1.0 x)) 0.0)))

C

double code(double x) {
	double tmp;
	if (x <= -1.0) {
		tmp = 0.0;
	} else if (x <= 3.8e+61) {
		tmp = (1.0 - x) + (-1.0 / x);
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    real(8) :: tmp
    if (x <= (-1.0d0)) then
        tmp = 0.0d0
    else if (x <= 3.8d+61) then
        tmp = (1.0d0 - x) + ((-1.0d0) / x)
    else
        tmp = 0.0d0
    end if
    code = tmp
end function

Java

public static double code(double x) {
	double tmp;
	if (x <= -1.0) {
		tmp = 0.0;
	} else if (x <= 3.8e+61) {
		tmp = (1.0 - x) + (-1.0 / x);
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Python

def code(x):
	tmp = 0
	if x <= -1.0:
		tmp = 0.0
	elif x <= 3.8e+61:
		tmp = (1.0 - x) + (-1.0 / x)
	else:
		tmp = 0.0
	return tmp

Julia

function code(x)
	tmp = 0.0
	if (x <= -1.0)
		tmp = 0.0;
	elseif (x <= 3.8e+61)
		tmp = Float64(Float64(1.0 - x) + Float64(-1.0 / x));
	else
		tmp = 0.0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x)
	tmp = 0.0;
	if (x <= -1.0)
		tmp = 0.0;
	elseif (x <= 3.8e+61)
		tmp = (1.0 - x) + (-1.0 / x);
	else
		tmp = 0.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_] := If[LessEqual[x, -1.0], 0.0, If[LessEqual[x, 3.8e+61], N[(N[(1.0 - x), $MachinePrecision] + N[(-1.0 / x), $MachinePrecision]), $MachinePrecision], 0.0]]

Derivation

1. Split input into 2 regimes

2. if x < -1 or 3.79999999999999995e61 < x

   1. Initial program 61.7%

      \[\frac{1}{x + 1} - \frac{1}{x} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. frac-sub 63.4%

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

      2. *-rgt-identity 63.4%

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

      3. metadata-eval 63.4%

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

      4. div-inv 63.4%

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

      5. associate-/r* 63.4%

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

      6. *-un-lft-identity 63.4%

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

      7. *-rgt-identity 63.4%

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

      8. +-commutative 63.4%

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

      9. div-inv 63.4%

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

      10. metadata-eval 63.4%

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

      11. *-rgt-identity 63.4%

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

      12. +-commutative 63.4%

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

   4. Applied egg-rr 63.4%

      \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
   5. Step-by-step derivation

      1. div-sub 61.8%

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

      2. *-inverses 61.8%

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

      3. sub-neg 61.8%

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

      4. +-commutative 61.8%

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

      5. metadata-eval 61.8%

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

   6. Applied egg-rr 61.8%

      \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
   7. Step-by-step derivation

      1. metadata-eval 61.8%

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

      2. sub-neg 61.8%

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

      3. *-inverses 61.8%

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

      4. div-sub 63.4%

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

      5. associate--r+ 99.8%

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

      6. +-inverses 99.8%

         \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

      7. metadata-eval 99.8%

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

   8. Simplified 99.8%

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

   10. Applied egg-rr 59.3%

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

   if -1 < x < 3.79999999999999995e61

   1. Initial program 91.5%

      \[\frac{1}{x + 1} - \frac{1}{x} \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 89.6%

      \[\leadsto \color{blue}{\left(1 + -1 \cdot x\right)} - \frac{1}{x} \]
   4. Step-by-step derivation

      1. neg-mul-1 89.6%

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

      2. unsub-neg 89.6%

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

   5. Simplified 89.6%

      \[\leadsto \color{blue}{\left(1 - x\right)} - \frac{1}{x} \]
3. Recombined 2 regimes into one program.

4. Final simplification 75.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;0\\ \mathbf{elif}\;x \leq 3.8 \cdot 10^{+61}:\\ \;\;\;\;\left(1 - x\right) + \frac{-1}{x}\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 75.1% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;0\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;1 + \frac{-1}{x}\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (if (<= x -1.0) 0.0 (if (<= x 1.0) (+ 1.0 (/ -1.0 x)) 0.0)))

C

double code(double x) {
	double tmp;
	if (x <= -1.0) {
		tmp = 0.0;
	} else if (x <= 1.0) {
		tmp = 1.0 + (-1.0 / x);
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    real(8) :: tmp
    if (x <= (-1.0d0)) then
        tmp = 0.0d0
    else if (x <= 1.0d0) then
        tmp = 1.0d0 + ((-1.0d0) / x)
    else
        tmp = 0.0d0
    end if
    code = tmp
end function

Java

public static double code(double x) {
	double tmp;
	if (x <= -1.0) {
		tmp = 0.0;
	} else if (x <= 1.0) {
		tmp = 1.0 + (-1.0 / x);
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Python

def code(x):
	tmp = 0
	if x <= -1.0:
		tmp = 0.0
	elif x <= 1.0:
		tmp = 1.0 + (-1.0 / x)
	else:
		tmp = 0.0
	return tmp

Julia

function code(x)
	tmp = 0.0
	if (x <= -1.0)
		tmp = 0.0;
	elseif (x <= 1.0)
		tmp = Float64(1.0 + Float64(-1.0 / x));
	else
		tmp = 0.0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x)
	tmp = 0.0;
	if (x <= -1.0)
		tmp = 0.0;
	elseif (x <= 1.0)
		tmp = 1.0 + (-1.0 / x);
	else
		tmp = 0.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_] := If[LessEqual[x, -1.0], 0.0, If[LessEqual[x, 1.0], N[(1.0 + N[(-1.0 / x), $MachinePrecision]), $MachinePrecision], 0.0]]

Derivation

1. Split input into 2 regimes

2. if x < -1 or 1 < x

   1. Initial program 57.3%

      \[\frac{1}{x + 1} - \frac{1}{x} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. frac-sub 60.3%

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

      2. *-rgt-identity 60.3%

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

      3. metadata-eval 60.3%

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

      4. div-inv 60.3%

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

      5. associate-/r* 60.3%

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

      6. *-un-lft-identity 60.3%

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

      7. *-rgt-identity 60.3%

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

      8. +-commutative 60.3%

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

      9. div-inv 60.3%

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

      10. metadata-eval 60.3%

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

      11. *-rgt-identity 60.3%

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

      12. +-commutative 60.3%

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

   4. Applied egg-rr 60.3%

      \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
   5. Step-by-step derivation

      1. div-sub 57.3%

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

      2. *-inverses 57.3%

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

      3. sub-neg 57.3%

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

      4. +-commutative 57.3%

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

      5. metadata-eval 57.3%

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

   6. Applied egg-rr 57.3%

      \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
   7. Step-by-step derivation

      1. metadata-eval 57.3%

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

      2. sub-neg 57.3%

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

      3. *-inverses 57.3%

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

      4. div-sub 60.3%

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

      5. associate--r+ 99.8%

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

      6. +-inverses 99.8%

         \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

      7. metadata-eval 99.8%

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

   8. Simplified 99.8%

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

   10. Applied egg-rr 53.1%

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

   if -1 < x < 1

   1. Initial program 100.0%

      \[\frac{1}{x + 1} - \frac{1}{x} \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 99.6%

      \[\leadsto \color{blue}{\frac{x - 1}{x}} \]
   4. Step-by-step derivation

      1. div-sub 99.6%

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

      2. *-inverses 99.6%

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

   5. Simplified 99.6%

      \[\leadsto \color{blue}{1 - \frac{1}{x}} \]
3. Recombined 2 regimes into one program.

4. Final simplification 75.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;0\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;1 + \frac{-1}{x}\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 74.9% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;0\\ \mathbf{elif}\;x \leq 4.45 \cdot 10^{+102}:\\ \;\;\;\;\frac{-1}{x}\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (if (<= x -1.0) 0.0 (if (<= x 4.45e+102) (/ -1.0 x) 0.0)))

C

double code(double x) {
	double tmp;
	if (x <= -1.0) {
		tmp = 0.0;
	} else if (x <= 4.45e+102) {
		tmp = -1.0 / x;
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    real(8) :: tmp
    if (x <= (-1.0d0)) then
        tmp = 0.0d0
    else if (x <= 4.45d+102) then
        tmp = (-1.0d0) / x
    else
        tmp = 0.0d0
    end if
    code = tmp
end function

Java

public static double code(double x) {
	double tmp;
	if (x <= -1.0) {
		tmp = 0.0;
	} else if (x <= 4.45e+102) {
		tmp = -1.0 / x;
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Python

def code(x):
	tmp = 0
	if x <= -1.0:
		tmp = 0.0
	elif x <= 4.45e+102:
		tmp = -1.0 / x
	else:
		tmp = 0.0
	return tmp

Julia

function code(x)
	tmp = 0.0
	if (x <= -1.0)
		tmp = 0.0;
	elseif (x <= 4.45e+102)
		tmp = Float64(-1.0 / x);
	else
		tmp = 0.0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x)
	tmp = 0.0;
	if (x <= -1.0)
		tmp = 0.0;
	elseif (x <= 4.45e+102)
		tmp = -1.0 / x;
	else
		tmp = 0.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_] := If[LessEqual[x, -1.0], 0.0, If[LessEqual[x, 4.45e+102], N[(-1.0 / x), $MachinePrecision], 0.0]]

Derivation

1. Split input into 2 regimes

2. if x < -1 or 4.4499999999999999e102 < x

   1. Initial program 67.0%

      \[\frac{1}{x + 1} - \frac{1}{x} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. frac-sub 68.9%

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

      2. *-rgt-identity 68.9%

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

      3. metadata-eval 68.9%

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

      4. div-inv 68.9%

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

      5. associate-/r* 68.8%

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

      6. *-un-lft-identity 68.8%

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

      7. *-rgt-identity 68.8%

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

      8. +-commutative 68.8%

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

      9. div-inv 68.8%

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

      10. metadata-eval 68.8%

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

      11. *-rgt-identity 68.8%

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

      12. +-commutative 68.8%

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

   4. Applied egg-rr 68.8%

      \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
   5. Step-by-step derivation

      1. div-sub 67.1%

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

      2. *-inverses 67.1%

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

      3. sub-neg 67.1%

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

      4. +-commutative 67.1%

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

      5. metadata-eval 67.1%

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

   6. Applied egg-rr 67.1%

      \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
   7. Step-by-step derivation

      1. metadata-eval 67.1%

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

      2. sub-neg 67.1%

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

      3. *-inverses 67.1%

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

      4. div-sub 68.8%

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

      5. associate--r+ 99.9%

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

      6. +-inverses 99.9%

         \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

      7. metadata-eval 99.9%

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

   8. Simplified 99.9%

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

   10. Applied egg-rr 64.4%

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

   if -1 < x < 4.4499999999999999e102

   1. Initial program 85.7%

      \[\frac{1}{x + 1} - \frac{1}{x} \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0 83.4%

      \[\leadsto \color{blue}{\frac{-1}{x}} \]
3. Recombined 2 regimes into one program.

4. Final simplification 75.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;0\\ \mathbf{elif}\;x \leq 4.45 \cdot 10^{+102}:\\ \;\;\;\;\frac{-1}{x}\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 99.5% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \frac{-1}{x \cdot \left(x + 1\right)} \end{array} \]

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 77.8%

   \[\frac{1}{x + 1} - \frac{1}{x} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. clear-num 77.8%

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

   2. frac-sub 79.4%

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

   3. *-un-lft-identity 79.4%

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

   4. div-inv 79.4%

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

   5. metadata-eval 79.4%

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

   6. *-rgt-identity 79.4%

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

   7. *-rgt-identity 79.4%

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

   8. +-commutative 79.4%

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

   9. *-commutative 79.4%

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

   10. div-inv 79.4%

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

   11. metadata-eval 79.4%

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

   12. *-rgt-identity 79.4%

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

   13. +-commutative 79.4%

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

4. Applied egg-rr 79.4%

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

5. Taylor expanded in x around 0 99.3%

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

6. Final simplification 99.3%

   \[\leadsto \frac{-1}{x \cdot \left(x + 1\right)} \]
7. Add Preprocessing

Alternative 6: 3.7% accurate, 9.0× speedup

Math

\[\begin{array}{l} \\ -2 \end{array} \]

FPCore

(FPCore (x) :precision binary64 -2.0)

C

double code(double x) {
	return -2.0;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = -2.0d0
end function

Java

public static double code(double x) {
	return -2.0;
}

Python

def code(x):
	return -2.0

Julia

function code(x)
	return -2.0
end

MATLAB

function tmp = code(x)
	tmp = -2.0;
end

Wolfram

code[x_] := -2.0

Derivation

1. Initial program 77.8%

   \[\frac{1}{x + 1} - \frac{1}{x} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. frac-sub 79.4%

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

   2. *-rgt-identity 79.4%

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

   3. metadata-eval 79.4%

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

   4. div-inv 79.4%

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

   5. associate-/r* 79.4%

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

   6. *-un-lft-identity 79.4%

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

   7. *-rgt-identity 79.4%

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

   8. +-commutative 79.4%

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

   9. div-inv 79.4%

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

   10. metadata-eval 79.4%

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

   11. *-rgt-identity 79.4%

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

   12. +-commutative 79.4%

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

4. Applied egg-rr 79.4%

   \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
5. Step-by-step derivation

   1. div-sub 77.8%

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

   2. *-inverses 77.8%

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

   3. sub-neg 77.8%

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

   4. +-commutative 77.8%

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

   5. metadata-eval 77.8%

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

6. Applied egg-rr 77.8%

   \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
7. Step-by-step derivation

   1. metadata-eval 77.8%

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

   2. sub-neg 77.8%

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

   3. *-inverses 77.8%

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

   4. div-sub 79.4%

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

   5. associate--r+ 99.9%

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

   6. +-inverses 99.9%

      \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

   7. metadata-eval 99.9%

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

8. Simplified 99.9%

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

10. Applied egg-rr 3.7%

    \[\leadsto \color{blue}{-2} \]

11. Final simplification 3.7%

    \[\leadsto -2 \]
12. Add Preprocessing

Alternative 7: 3.7% accurate, 9.0× speedup

Math

\[\begin{array}{l} \\ -0.5 \end{array} \]

FPCore

(FPCore (x) :precision binary64 -0.5)

C

double code(double x) {
	return -0.5;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = -0.5d0
end function

Java

public static double code(double x) {
	return -0.5;
}

Python

def code(x):
	return -0.5

Julia

function code(x)
	return -0.5
end

MATLAB

function tmp = code(x)
	tmp = -0.5;
end

Wolfram

code[x_] := -0.5

Derivation

1. Initial program 77.8%

   \[\frac{1}{x + 1} - \frac{1}{x} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. frac-sub 79.4%

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

   2. *-rgt-identity 79.4%

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

   3. metadata-eval 79.4%

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

   4. div-inv 79.4%

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

   5. associate-/r* 79.4%

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

   6. *-un-lft-identity 79.4%

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

   7. *-rgt-identity 79.4%

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

   8. +-commutative 79.4%

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

   9. div-inv 79.4%

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

   10. metadata-eval 79.4%

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

   11. *-rgt-identity 79.4%

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

   12. +-commutative 79.4%

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

4. Applied egg-rr 79.4%

   \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
5. Step-by-step derivation

   1. div-sub 77.8%

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

   2. *-inverses 77.8%

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

   3. sub-neg 77.8%

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

   4. +-commutative 77.8%

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

   5. metadata-eval 77.8%

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

6. Applied egg-rr 77.8%

   \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
7. Step-by-step derivation

   1. metadata-eval 77.8%

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

   2. sub-neg 77.8%

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

   3. *-inverses 77.8%

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

   4. div-sub 79.4%

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

   5. associate--r+ 99.9%

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

   6. +-inverses 99.9%

      \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

   7. metadata-eval 99.9%

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

8. Simplified 99.9%

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

10. Applied egg-rr 3.7%

    \[\leadsto \color{blue}{-0.5} \]

11. Final simplification 3.7%

    \[\leadsto -0.5 \]
12. Add Preprocessing

Alternative 8: 26.6% accurate, 9.0× speedup

Math

\[\begin{array}{l} \\ 0 \end{array} \]

FPCore

(FPCore (x) :precision binary64 0.0)

C

double code(double x) {
	return 0.0;
}

Fortran

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

Java

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

Python

def code(x):
	return 0.0

Julia

function code(x)
	return 0.0
end

MATLAB

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

Wolfram

code[x_] := 0.0

Derivation

1. Initial program 77.8%

   \[\frac{1}{x + 1} - \frac{1}{x} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. frac-sub 79.4%

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

   2. *-rgt-identity 79.4%

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

   3. metadata-eval 79.4%

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

   4. div-inv 79.4%

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

   5. associate-/r* 79.4%

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

   6. *-un-lft-identity 79.4%

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

   7. *-rgt-identity 79.4%

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

   8. +-commutative 79.4%

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

   9. div-inv 79.4%

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

   10. metadata-eval 79.4%

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

   11. *-rgt-identity 79.4%

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

   12. +-commutative 79.4%

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

4. Applied egg-rr 79.4%

   \[\leadsto \color{blue}{\frac{\frac{x - \left(1 + x\right)}{1 + x}}{x}} \]
5. Step-by-step derivation

   1. div-sub 77.8%

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

   2. *-inverses 77.8%

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

   3. sub-neg 77.8%

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

   4. +-commutative 77.8%

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

   5. metadata-eval 77.8%

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

6. Applied egg-rr 77.8%

   \[\leadsto \frac{\color{blue}{\frac{x}{x + 1} + -1}}{x} \]
7. Step-by-step derivation

   1. metadata-eval 77.8%

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

   2. sub-neg 77.8%

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

   3. *-inverses 77.8%

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

   4. div-sub 79.4%

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

   5. associate--r+ 99.9%

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

   6. +-inverses 99.9%

      \[\leadsto \frac{\frac{\color{blue}{0} - 1}{x + 1}}{x} \]

   7. metadata-eval 99.9%

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

8. Simplified 99.9%

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

10. Applied egg-rr 28.6%

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

11. Final simplification 28.6%

    \[\leadsto 0 \]
12. Add Preprocessing

Reproduce

herbie shell --seed 2024079 
(FPCore (x)
  :name "2frac (problem 3.3.1)"
  :precision binary64
  (- (/ 1.0 (+ x 1.0)) (/ 1.0 x)))