Average Error: 0.0 → 0.0
Time: 2.0s
Precision: 64
\[\left(x + y\right) \cdot \left(z + 1\right)\]
↓
\[\left(z + 1\right) \cdot \left(x + y\right)\]
\left(x + y\right) \cdot \left(z + 1\right)
↓
\left(z + 1\right) \cdot \left(x + y\right)
double code(double x, double y, double z) {
	return ((x + y) * (z + 1.0));
}
↓
double code(double x, double y, double z) {
	return ((z + 1.0) * (x + y));
}

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 *-commutative0.0

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

  4. Final simplification0.0

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

Reproduce

herbie shell --seed 2020057 +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)))