Average Error: 0.0 → 0.0
Time: 1.8s
Precision: 64
\[x + y \cdot \left(z + x\right)\]
↓
\[x + \left(y \cdot z + y \cdot x\right)\]
x + y \cdot \left(z + x\right)
↓
x + \left(y \cdot z + y \cdot x\right)
double f(double x, double y, double z) {
        double r132564 = x;
        double r132565 = y;
        double r132566 = z;
        double r132567 = r132566 + r132564;
        double r132568 = r132565 * r132567;
        double r132569 = r132564 + r132568;
        return r132569;
}
↓
double f(double x, double y, double z) {
        double r132570 = x;
        double r132571 = y;
        double r132572 = z;
        double r132573 = r132571 * r132572;
        double r132574 = r132571 * r132570;
        double r132575 = r132573 + r132574;
        double r132576 = r132570 + r132575;
        return r132576;
}

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

    \[x + y \cdot \left(z + x\right)\]
  2. Using strategy rm

  3. Applied distribute-lft-in0.0

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

  4. Final simplification0.0

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

Reproduce

herbie shell --seed 2020049 
(FPCore (x y z)
  :name "Main:bigenough2 from A"
  :precision binary64
  (+ x (* y (+ z x))))