Average Error: 0.0 → 0.0
Time: 7.5s
Precision: 64
\[x + x \cdot x\]
↓
\[x \cdot \left(x + 1\right)\]
x + x \cdot x
↓
x \cdot \left(x + 1\right)
double f(double x) {
        double r157516 = x;
        double r157517 = r157516 * r157516;
        double r157518 = r157516 + r157517;
        return r157518;
}
↓
double f(double x) {
        double r157519 = x;
        double r157520 = 1.0;
        double r157521 = r157519 + r157520;
        double r157522 = r157519 * r157521;
        return r157522;
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[x + x \cdot x\]
  2. Using strategy rm

  3. Applied *-un-lft-identity0.0

    \[\leadsto \color{blue}{1 \cdot x} + x \cdot x\]

  4. Applied distribute-rgt-out0.0

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

  5. Simplified0.0

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

  6. Final simplification0.0

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

Reproduce

herbie shell --seed 2020042 
(FPCore (x)
  :name "Main:bigenough1 from B"
  :precision binary64
  (+ x (* x x)))