Average Error: 0.0 → 0.0
Time: 1.8s
Precision: 64
\[e^{\left(x \cdot y\right) \cdot y}\]
↓
\[{e}^{\left(\left(x \cdot y\right) \cdot y\right)}\]
e^{\left(x \cdot y\right) \cdot y}
↓
{e}^{\left(\left(x \cdot y\right) \cdot y\right)}
double code(double x, double y) {
	return ((double) exp(((double) (((double) (x * y)) * y))));
}
↓
double code(double x, double y) {
	return ((double) pow(((double) M_E), ((double) (((double) (x * y)) * y))));
}

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 0.0

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

  3. Applied *-un-lft-identity0.0

    \[\leadsto e^{\color{blue}{1 \cdot \left(\left(x \cdot y\right) \cdot y\right)}}\]

  4. Applied exp-prod0.0

    \[\leadsto \color{blue}{{\left(e^{1}\right)}^{\left(\left(x \cdot y\right) \cdot y\right)}}\]

  5. Simplified0.0

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

  6. Final simplification0.0

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

Reproduce

herbie shell --seed 2020113 +o rules:numerics
(FPCore (x y)
  :name "Data.Random.Distribution.Normal:normalF from random-fu-0.2.6.2"
  :precision binary64
  (exp (* (* x y) y)))