Average Error: 0.0 → 0.0
Time: 4.1s
Precision: 64
\[\left(x + y\right) \cdot \left(z + 1\right)\]
↓
\[z \cdot \left(x + y\right) + \left(x + y\right) \cdot 1\]
\left(x + y\right) \cdot \left(z + 1\right)
↓
z \cdot \left(x + y\right) + \left(x + y\right) \cdot 1
double f(double x, double y, double z) {
        double r52264 = x;
        double r52265 = y;
        double r52266 = r52264 + r52265;
        double r52267 = z;
        double r52268 = 1.0;
        double r52269 = r52267 + r52268;
        double r52270 = r52266 * r52269;
        return r52270;
}
↓
double f(double x, double y, double z) {
        double r52271 = z;
        double r52272 = x;
        double r52273 = y;
        double r52274 = r52272 + r52273;
        double r52275 = r52271 * r52274;
        double r52276 = 1.0;
        double r52277 = r52274 * r52276;
        double r52278 = r52275 + r52277;
        return r52278;
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[\left(x + y\right) \cdot \left(z + 1\right)\]
  2. Using strategy rm

  3. Applied distribute-lft-in0.0

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

  4. Simplified0.0

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

  5. Final simplification0.0

    \[\leadsto z \cdot \left(x + y\right) + \left(x + y\right) \cdot 1\]

Reproduce

herbie shell --seed 2019208 +o rules:numerics
(FPCore (x y z)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, G"
  :precision binary64
  (* (+ x y) (+ z 1)))