Average Error: 9.7 → 0.3
Time: 3.9s
Precision: binary64
\[\left(\frac{1}{x + 1} - \frac{2}{x}\right) + \frac{1}{x - 1} \]
\[\frac{2}{{x}^{3} - x} \]
(FPCore (x)
 :precision binary64
 (+ (- (/ 1.0 (+ x 1.0)) (/ 2.0 x)) (/ 1.0 (- x 1.0))))
(FPCore (x) :precision binary64 (/ 2.0 (- (pow x 3.0) x)))
double code(double x) {
	return ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0));
}
double code(double x) {
	return 2.0 / (pow(x, 3.0) - x);
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = ((1.0d0 / (x + 1.0d0)) - (2.0d0 / x)) + (1.0d0 / (x - 1.0d0))
end function
real(8) function code(x)
    real(8), intent (in) :: x
    code = 2.0d0 / ((x ** 3.0d0) - x)
end function
public static double code(double x) {
	return ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0));
}
public static double code(double x) {
	return 2.0 / (Math.pow(x, 3.0) - x);
}
def code(x):
	return ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0))
def code(x):
	return 2.0 / (math.pow(x, 3.0) - x)
function code(x)
	return Float64(Float64(Float64(1.0 / Float64(x + 1.0)) - Float64(2.0 / x)) + Float64(1.0 / Float64(x - 1.0)))
end
function code(x)
	return Float64(2.0 / Float64((x ^ 3.0) - x))
end
function tmp = code(x)
	tmp = ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0));
end
function tmp = code(x)
	tmp = 2.0 / ((x ^ 3.0) - x);
end
code[x_] := N[(N[(N[(1.0 / N[(x + 1.0), $MachinePrecision]), $MachinePrecision] - N[(2.0 / x), $MachinePrecision]), $MachinePrecision] + N[(1.0 / N[(x - 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := N[(2.0 / N[(N[Power[x, 3.0], $MachinePrecision] - x), $MachinePrecision]), $MachinePrecision]
\left(\frac{1}{x + 1} - \frac{2}{x}\right) + \frac{1}{x - 1}
\frac{2}{{x}^{3} - x}

Error

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original9.7
Target0.3
Herbie0.3
\[\frac{2}{x \cdot \left(x \cdot x - 1\right)} \]

Derivation

  1. Initial program 9.7

    \[\left(\frac{1}{x + 1} - \frac{2}{x}\right) + \frac{1}{x - 1} \]
  2. Applied egg-rr25.1

    \[\leadsto \color{blue}{\frac{x \cdot \left(1 + x\right) + \left(x + -1\right) \cdot \left(x - \left(1 + x\right) \cdot 2\right)}{\left(x + -1\right) \cdot \left(x \cdot \left(1 + x\right)\right)}} \]
  3. Taylor expanded in x around 0 0.3

    \[\leadsto \frac{\color{blue}{2}}{\left(x + -1\right) \cdot \left(x \cdot \left(1 + x\right)\right)} \]
  4. Taylor expanded in x around 0 0.3

    \[\leadsto \frac{2}{\color{blue}{-1 \cdot x + {x}^{3}}} \]
  5. Simplified0.3

    \[\leadsto \frac{2}{\color{blue}{{x}^{3} - x}} \]
  6. Final simplification0.3

    \[\leadsto \frac{2}{{x}^{3} - x} \]

Reproduce

herbie shell --seed 2022211 
(FPCore (x)
  :name "3frac (problem 3.3.3)"
  :precision binary64

  :herbie-target
  (/ 2.0 (* x (- (* x x) 1.0)))

  (+ (- (/ 1.0 (+ x 1.0)) (/ 2.0 x)) (/ 1.0 (- x 1.0))))