Average Error: 0.3 → 0
Time: 458.0ms
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 r305740 = d;
        double r305741 = 10.0;
        double r305742 = r305740 * r305741;
        double r305743 = 20.0;
        double r305744 = r305740 * r305743;
        double r305745 = r305742 + r305744;
        return r305745;
}

double f(double d) {
        double r305746 = 30.0;
        double r305747 = d;
        double r305748 = r305746 * r305747;
        return r305748;
}

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 2020020 +o rules:numerics
(FPCore (d)
  :name "FastMath test1"
  :precision binary64

  :herbie-target
  (* d 30)

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