Average Error: 0.0 → 0
Time: 876.0ms
Precision: 64
\[x \cdot \left(x - 1\right)\]
\[\mathsf{fma}\left({x}^{1}, {x}^{1}, x \cdot \left(-1\right)\right)\]
x \cdot \left(x - 1\right)
\mathsf{fma}\left({x}^{1}, {x}^{1}, x \cdot \left(-1\right)\right)
double f(double x) {
        double r301442 = x;
        double r301443 = 1.0;
        double r301444 = r301442 - r301443;
        double r301445 = r301442 * r301444;
        return r301445;
}

double f(double x) {
        double r301446 = x;
        double r301447 = 1.0;
        double r301448 = pow(r301446, r301447);
        double r301449 = 1.0;
        double r301450 = -r301449;
        double r301451 = r301446 * r301450;
        double r301452 = fma(r301448, r301448, r301451);
        return r301452;
}

Error

Bits error versus x

Target

Original0.0
Target0.0
Herbie0
\[x \cdot x - x\]

Derivation

  1. Initial program 0.0

    \[x \cdot \left(x - 1\right)\]
  2. Using strategy rm
  3. Applied sub-neg0.0

    \[\leadsto x \cdot \color{blue}{\left(x + \left(-1\right)\right)}\]
  4. Applied distribute-lft-in0.0

    \[\leadsto \color{blue}{x \cdot x + x \cdot \left(-1\right)}\]
  5. Simplified0.0

    \[\leadsto \color{blue}{{x}^{2}} + x \cdot \left(-1\right)\]
  6. Using strategy rm
  7. Applied sqr-pow0.0

    \[\leadsto \color{blue}{{x}^{\left(\frac{2}{2}\right)} \cdot {x}^{\left(\frac{2}{2}\right)}} + x \cdot \left(-1\right)\]
  8. Applied fma-def0

    \[\leadsto \color{blue}{\mathsf{fma}\left({x}^{\left(\frac{2}{2}\right)}, {x}^{\left(\frac{2}{2}\right)}, x \cdot \left(-1\right)\right)}\]
  9. Final simplification0

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

Reproduce

herbie shell --seed 2019353 +o rules:numerics
(FPCore (x)
  :name "Statistics.Correlation.Kendall:numOfTiesBy from math-functions-0.1.5.2"
  :precision binary64

  :herbie-target
  (- (* x x) x)

  (* x (- x 1)))