Average Error: 0.0 → 0.0
Time: 2.9s
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 r30992 = x;
        double r30993 = y;
        double r30994 = r30992 + r30993;
        double r30995 = z;
        double r30996 = 1.0;
        double r30997 = r30995 + r30996;
        double r30998 = r30994 * r30997;
        return r30998;
}
↓
double f(double x, double y, double z) {
        double r30999 = x;
        double r31000 = y;
        double r31001 = r30999 + r31000;
        double r31002 = z;
        double r31003 = r31001 * r31002;
        double r31004 = 1.0;
        double r31005 = r31004 * r31001;
        double r31006 = r31003 + r31005;
        return r31006;
}

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 2019350 +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)))