Average Error: 0.0 → 0.0
Time: 10.4s
Precision: 64
\[\left(x + y\right) \cdot \left(z + 1\right)\]
↓
\[\left(x + y\right) \cdot z + 1 \cdot \left(x + y\right)\]
\left(x + y\right) \cdot \left(z + 1\right)
↓
\left(x + y\right) \cdot z + 1 \cdot \left(x + y\right)
double f(double x, double y, double z) {
        double r41348 = x;
        double r41349 = y;
        double r41350 = r41348 + r41349;
        double r41351 = z;
        double r41352 = 1.0;
        double r41353 = r41351 + r41352;
        double r41354 = r41350 * r41353;
        return r41354;
}
↓
double f(double x, double y, double z) {
        double r41355 = x;
        double r41356 = y;
        double r41357 = r41355 + r41356;
        double r41358 = z;
        double r41359 = r41357 * r41358;
        double r41360 = 1.0;
        double r41361 = r41360 * r41357;
        double r41362 = r41359 + r41361;
        return r41362;
}

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

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

  5. Final simplification0.0

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

Reproduce

herbie shell --seed 2019323 +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)))