Average Error: 0.0 → 0.0
Time: 2.0s
Precision: binary64
\[\frac{-\left(f + n\right)}{f - n} \]
↓
\[\sqrt[3]{{\left(\frac{f + n}{n - f}\right)}^{3}} \]
(FPCore (f n) :precision binary64 (/ (- (+ f n)) (- f n)))
↓
(FPCore (f n) :precision binary64 (cbrt (pow (/ (+ f n) (- n f)) 3.0)))
double code(double f, double n) {
	return -(f + n) / (f - n);
}
↓
double code(double f, double n) {
	return cbrt(pow(((f + n) / (n - f)), 3.0));
}

public static double code(double f, double n) {
	return -(f + n) / (f - n);
}
↓
public static double code(double f, double n) {
	return Math.cbrt(Math.pow(((f + n) / (n - f)), 3.0));
}

function code(f, n)
	return Float64(Float64(-Float64(f + n)) / Float64(f - n))
end
↓
function code(f, n)
	return cbrt((Float64(Float64(f + n) / Float64(n - f)) ^ 3.0))
end

code[f_, n_] := N[((-N[(f + n), $MachinePrecision]) / N[(f - n), $MachinePrecision]), $MachinePrecision]
↓
code[f_, n_] := N[Power[N[Power[N[(N[(f + n), $MachinePrecision] / N[(n - f), $MachinePrecision]), $MachinePrecision], 3.0], $MachinePrecision], 1/3], $MachinePrecision]

\frac{-\left(f + n\right)}{f - n}
↓
\sqrt[3]{{\left(\frac{f + n}{n - f}\right)}^{3}}

Error

Bits error versus f

Bits error versus n

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[\frac{-\left(f + n\right)}{f - n} \]

  2. Simplified0.0

    \[\leadsto \color{blue}{\frac{f + n}{n - f}} \]

  3. Applied egg-rr0.0

    \[\leadsto \color{blue}{\sqrt[3]{{\left(\frac{f + n}{n - f}\right)}^{3}}} \]

  4. Final simplification0.0

    \[\leadsto \sqrt[3]{{\left(\frac{f + n}{n - f}\right)}^{3}} \]

Reproduce

herbie shell --seed 2022148 
(FPCore (f n)
  :name "subtraction fraction"
  :precision binary64
  (/ (- (+ f n)) (- f n)))