Average Error: 0.3 → 0
Time: 479.0ms
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 r257903 = d;
        double r257904 = 10.0;
        double r257905 = r257903 * r257904;
        double r257906 = 20.0;
        double r257907 = r257903 * r257906;
        double r257908 = r257905 + r257907;
        return r257908;
}
↓
double f(double d) {
        double r257909 = 30.0;
        double r257910 = d;
        double r257911 = r257909 * r257910;
        return r257911;
}

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 2020100 +o rules:numerics
(FPCore (d)
  :name "FastMath test1"
  :precision binary64

  :herbie-target
  (* d 30)

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