Average Error: 0.1 → 0.1
Time: 1.8s
Precision: 64
\[x \cdot \left(1 - x \cdot y\right)\]
\[\left(x \cdot 1 + x \cdot \left(-x \cdot y\right)\right) + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)\]
x \cdot \left(1 - x \cdot y\right)
\left(x \cdot 1 + x \cdot \left(-x \cdot y\right)\right) + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)
double code(double x, double y) {
	return ((double) (x * ((double) (1.0 - ((double) (x * y))))));
}
double code(double x, double y) {
	return ((double) (((double) (((double) (x * 1.0)) + ((double) (x * ((double) -(((double) (x * y)))))))) + ((double) (x * ((double) fma(((double) -(y)), x, ((double) (y * x))))))));
}

Error

Bits error versus x

Bits error versus y

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Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.1

    \[x \cdot \left(1 - x \cdot y\right)\]
  2. Using strategy rm
  3. Applied add-sqr-sqrt0.1

    \[\leadsto x \cdot \left(\color{blue}{\sqrt{1} \cdot \sqrt{1}} - x \cdot y\right)\]
  4. Applied prod-diff0.1

    \[\leadsto x \cdot \color{blue}{\left(\mathsf{fma}\left(\sqrt{1}, \sqrt{1}, -y \cdot x\right) + \mathsf{fma}\left(-y, x, y \cdot x\right)\right)}\]
  5. Applied distribute-lft-in0.1

    \[\leadsto \color{blue}{x \cdot \mathsf{fma}\left(\sqrt{1}, \sqrt{1}, -y \cdot x\right) + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)}\]
  6. Simplified0.1

    \[\leadsto \color{blue}{x \cdot \left(1 - x \cdot y\right)} + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)\]
  7. Using strategy rm
  8. Applied sub-neg0.1

    \[\leadsto x \cdot \color{blue}{\left(1 + \left(-x \cdot y\right)\right)} + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)\]
  9. Applied distribute-lft-in0.1

    \[\leadsto \color{blue}{\left(x \cdot 1 + x \cdot \left(-x \cdot y\right)\right)} + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)\]
  10. Final simplification0.1

    \[\leadsto \left(x \cdot 1 + x \cdot \left(-x \cdot y\right)\right) + x \cdot \mathsf{fma}\left(-y, x, y \cdot x\right)\]

Reproduce

herbie shell --seed 2020114 +o rules:numerics
(FPCore (x y)
  :name "Numeric.SpecFunctions:log1p from math-functions-0.1.5.2, A"
  :precision binary64
  (* x (- 1 (* x y))))