Average Error: 61.8 → 0.4
Time: 17.5s
Precision: 64
\[0.9000000000000000222044604925031308084726 \le t \le 1.100000000000000088817841970012523233891\]
\[\left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right) \cdot \left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right) + \left(-1 - 2 \cdot \left(t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right)\right)\]
↓
\[3.999999999999999676487027278085939408227 \cdot 10^{-32} \cdot \left(t \cdot t\right)\]
\left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right) \cdot \left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right) + \left(-1 - 2 \cdot \left(t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right)\right)
↓
3.999999999999999676487027278085939408227 \cdot 10^{-32} \cdot \left(t \cdot t\right)
double f(double t) {
        double r3716938 = 1.0;
        double r3716939 = t;
        double r3716940 = 2e-16;
        double r3716941 = r3716939 * r3716940;
        double r3716942 = r3716938 + r3716941;
        double r3716943 = r3716942 * r3716942;
        double r3716944 = -1.0;
        double r3716945 = 2.0;
        double r3716946 = r3716945 * r3716941;
        double r3716947 = r3716944 - r3716946;
        double r3716948 = r3716943 + r3716947;
        return r3716948;
}
↓
double f(double t) {
        double r3716949 = 3.9999999999999997e-32;
        double r3716950 = t;
        double r3716951 = r3716950 * r3716950;
        double r3716952 = r3716949 * r3716951;
        return r3716952;
}

Error

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original61.8
Target50.6
Herbie0.4
\[\mathsf{fma}\left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}, 1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}, -1 - 2 \cdot \left(t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right)\right)\]

Derivation

  1. Initial program 61.8

    \[\left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right) \cdot \left(1 + t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right) + \left(-1 - 2 \cdot \left(t \cdot 1.999999999999999958195573448069207123682 \cdot 10^{-16}\right)\right)\]

  2. Simplified50.6

    \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(t, 1.999999999999999958195573448069207123682 \cdot 10^{-16}, 1\right), \mathsf{fma}\left(t, 1.999999999999999958195573448069207123682 \cdot 10^{-16}, 1\right), -1 - \left(1.999999999999999958195573448069207123682 \cdot 10^{-16} \cdot t\right) \cdot 2\right)}\]

  3. Taylor expanded around 0 0.4

    \[\leadsto \color{blue}{3.999999999999999676487027278085939408227 \cdot 10^{-32} \cdot {t}^{2}}\]

  4. Simplified0.3

    \[\leadsto \color{blue}{\left(t \cdot 3.999999999999999676487027278085939408227 \cdot 10^{-32}\right) \cdot t}\]
  5. Using strategy rm

  6. Applied add-sqr-sqrt0.6

    \[\leadsto \color{blue}{\sqrt{\left(t \cdot 3.999999999999999676487027278085939408227 \cdot 10^{-32}\right) \cdot t} \cdot \sqrt{\left(t \cdot 3.999999999999999676487027278085939408227 \cdot 10^{-32}\right) \cdot t}}\]

  7. Taylor expanded around 0 0.4

    \[\leadsto \color{blue}{{t}^{2} \cdot {\left(\sqrt{3.999999999999999676487027278085939408227 \cdot 10^{-32}}\right)}^{2}}\]

  8. Simplified0.4

    \[\leadsto \color{blue}{3.999999999999999676487027278085939408227 \cdot 10^{-32} \cdot \left(t \cdot t\right)}\]

  9. Final simplification0.4

    \[\leadsto 3.999999999999999676487027278085939408227 \cdot 10^{-32} \cdot \left(t \cdot t\right)\]

Reproduce

herbie shell --seed 2019171 +o rules:numerics
(FPCore (t)
  :name "fma_test1"
  :pre (<= 0.9 t 1.1)

  :herbie-target
  (fma (+ 1.0 (* t 2e-16)) (+ 1.0 (* t 2e-16)) (- -1.0 (* 2.0 (* t 2e-16))))

  (+ (* (+ 1.0 (* t 2e-16)) (+ 1.0 (* t 2e-16))) (- -1.0 (* 2.0 (* t 2e-16)))))