Average Error: 0.0 → 0.0
Time: 2.5s
Precision: 64
\[e^{\left(x \cdot y\right) \cdot y}\]
↓
\[e^{x \cdot {y}^{2}}\]
e^{\left(x \cdot y\right) \cdot y}
↓
e^{x \cdot {y}^{2}}
double f(double x, double y) {
        double r241893 = x;
        double r241894 = y;
        double r241895 = r241893 * r241894;
        double r241896 = r241895 * r241894;
        double r241897 = exp(r241896);
        return r241897;
}
↓
double f(double x, double y) {
        double r241898 = x;
        double r241899 = y;
        double r241900 = 2.0;
        double r241901 = pow(r241899, r241900);
        double r241902 = r241898 * r241901;
        double r241903 = exp(r241902);
        return r241903;
}

Error

Bits error versus x

Bits error versus y

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Your Program's Arguments

Results

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Derivation

  1. Initial program 0.0

    \[e^{\left(x \cdot y\right) \cdot y}\]
  2. Using strategy rm

  3. Applied associate-*l*0.0

    \[\leadsto e^{\color{blue}{x \cdot \left(y \cdot y\right)}}\]

  4. Simplified0.0

    \[\leadsto e^{x \cdot \color{blue}{{y}^{2}}}\]

  5. Final simplification0.0

    \[\leadsto e^{x \cdot {y}^{2}}\]

Reproduce

herbie shell --seed 2020064 
(FPCore (x y)
  :name "Data.Random.Distribution.Normal:normalF from random-fu-0.2.6.2"
  :precision binary64
  (exp (* (* x y) y)))