Average Error: 0.3 → 0
Time: 640.0ms
Precision: 64
\[d \cdot 10 + d \cdot 20\]
\[30 \cdot d\]
d \cdot 10 + d \cdot 20
30 \cdot d
double f(double d) {
        double r280129 = d;
        double r280130 = 10.0;
        double r280131 = r280129 * r280130;
        double r280132 = 20.0;
        double r280133 = r280129 * r280132;
        double r280134 = r280131 + r280133;
        return r280134;
}

double f(double d) {
        double r280135 = 30.0;
        double r280136 = d;
        double r280137 = r280135 * r280136;
        return r280137;
}

Error

Bits error versus d

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original0.3
Target0
Herbie0
\[d \cdot 30\]

Derivation

  1. Initial program 0.3

    \[d \cdot 10 + d \cdot 20\]
  2. Simplified0.1

    \[\leadsto \color{blue}{\mathsf{fma}\left(d, 10, d \cdot 20\right)}\]
  3. Taylor expanded around 0 0

    \[\leadsto \color{blue}{30 \cdot d}\]
  4. Final simplification0

    \[\leadsto 30 \cdot d\]

Reproduce

herbie shell --seed 2020065 +o rules:numerics
(FPCore (d)
  :name "FastMath test1"
  :precision binary64

  :herbie-target
  (* d 30)

  (+ (* d 10) (* d 20)))