Average Error: 49.2 → 49.2
Time: 4.8s
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 r3008123 = 1.7e+308;
        double r3008124 = t;
        double r3008125 = r3008123 * r3008124;
        double r3008126 = r3008125 - r3008123;
        return r3008126;
}
↓
double f(double t) {
        double r3008127 = 1.7e+308;
        double r3008128 = t;
        double r3008129 = r3008127 * r3008128;
        double r3008130 = r3008129 - r3008127;
        return r3008130;
}

Error

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original49.2
Target0
Herbie49.2
\[\mathsf{fma}\left(1.7 \cdot 10^{+308}, t, -1.7 \cdot 10^{+308}\right)\]

Derivation

  1. Initial program 49.2

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

  2. Final simplification49.2

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

Reproduce

herbie shell --seed 2019162 
(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))