Average Error: 49.1 → 49.1
Time: 2.8s
Precision: 64
\[1.9 \le t \le 2.1\]
\[1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]
↓
\[1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]
1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}
↓
1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}
double f(double t) {
        double r15456159 = 1.7e+308;
        double r15456160 = t;
        double r15456161 = r15456159 * r15456160;
        double r15456162 = r15456161 - r15456159;
        return r15456162;
}
↓
double f(double t) {
        double r15456163 = 1.7e+308;
        double r15456164 = t;
        double r15456165 = r15456163 * r15456164;
        double r15456166 = r15456165 - r15456163;
        return r15456166;
}

Error

Bits error versus t

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Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original49.1
Target0
Herbie49.1
\[\mathsf{fma}\left(\left( 1.7 \cdot 10^{+308} \right), t, \left(-1.7 \cdot 10^{+308}\right)\right)\]

Derivation

  1. Initial program 49.1

    \[1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]

  2. Final simplification49.1

    \[\leadsto 1.7 \cdot 10^{+308} \cdot t - 1.7 \cdot 10^{+308}\]

Reproduce

herbie shell --seed 2019128 
(FPCore (t)
  :name "fma_test2"
  :pre (<= 1.9 t 2.1)

  :herbie-target
  (fma 1.7e+308 t (- 1.7e+308))

  (- (* 1.7e+308 t) 1.7e+308))