Average Error: 49.1 → 49.1
Time: 1.7s
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 r796776 = 1.7e+308;
        double r796777 = t;
        double r796778 = r796776 * r796777;
        double r796779 = r796778 - r796776;
        return r796779;
}
↓
double f(double t) {
        double r796780 = 1.7e+308;
        double r796781 = t;
        double r796782 = r796780 * r796781;
        double r796783 = r796782 - r796780;
        return r796783;
}

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

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))