Average Error: 0.0 → 0.0
Time: 6.4s
Precision: 64
\[x + x \cdot x\]
↓
\[x \cdot \left(1 + x\right)\]
x + x \cdot x
↓
x \cdot \left(1 + x\right)
double f(double x) {
        double r77133 = x;
        double r77134 = r77133 * r77133;
        double r77135 = r77133 + r77134;
        return r77135;
}
↓
double f(double x) {
        double r77136 = x;
        double r77137 = 1.0;
        double r77138 = r77137 + r77136;
        double r77139 = r77136 * r77138;
        return r77139;
}

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. Final simplification0.0

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

Reproduce

herbie shell --seed 2019322 
(FPCore (x)
  :name "Main:bigenough1 from B"
  :precision binary64
  (+ x (* x x)))