Average Error: 0.0 → 0.0
Time: 6.5s
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 r27394 = x;
        double r27395 = y;
        double r27396 = r27394 + r27395;
        double r27397 = z;
        double r27398 = 1.0;
        double r27399 = r27397 + r27398;
        double r27400 = r27396 * r27399;
        return r27400;
}
↓
double f(double x, double y, double z) {
        double r27401 = x;
        double r27402 = y;
        double r27403 = r27401 + r27402;
        double r27404 = z;
        double r27405 = r27403 * r27404;
        double r27406 = 1.0;
        double r27407 = r27406 * r27403;
        double r27408 = r27405 + r27407;
        return r27408;
}

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 2020042 +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)))