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 r2469250 = 1.7e+308;
        double r2469251 = t;
        double r2469252 = r2469250 * r2469251;
        double r2469253 = r2469252 - r2469250;
        return r2469253;
}
↓
double f(double t) {
        double r2469254 = 1.7e+308;
        double r2469255 = t;
        double r2469256 = r2469254 * r2469255;
        double r2469257 = r2469256 - r2469254;
        return r2469257;
}

Error

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

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

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 2019146 
(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))