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 r25801 = x;
        double r25802 = y;
        double r25803 = r25801 + r25802;
        double r25804 = z;
        double r25805 = 1.0;
        double r25806 = r25804 + r25805;
        double r25807 = r25803 * r25806;
        return r25807;
}
↓
double f(double x, double y, double z) {
        double r25808 = x;
        double r25809 = y;
        double r25810 = r25808 + r25809;
        double r25811 = z;
        double r25812 = r25810 * r25811;
        double r25813 = 1.0;
        double r25814 = r25813 * r25810;
        double r25815 = r25812 + r25814;
        return r25815;
}

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 2019351 +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)))