Average Error: 0.0 → 0.0
Time: 6.6s
Precision: 64
\[x \cdot y + z \cdot t\]
↓
\[x \cdot y + z \cdot t\]
x \cdot y + z \cdot t
↓
x \cdot y + z \cdot t
double f(double x, double y, double z, double t) {
        double r129396 = x;
        double r129397 = y;
        double r129398 = r129396 * r129397;
        double r129399 = z;
        double r129400 = t;
        double r129401 = r129399 * r129400;
        double r129402 = r129398 + r129401;
        return r129402;
}
↓
double f(double x, double y, double z, double t) {
        double r129403 = x;
        double r129404 = y;
        double r129405 = r129403 * r129404;
        double r129406 = z;
        double r129407 = t;
        double r129408 = r129406 * r129407;
        double r129409 = r129405 + r129408;
        return r129409;
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[x \cdot y + z \cdot t\]

  2. Final simplification0.0

    \[\leadsto x \cdot y + z \cdot t\]

Reproduce

herbie shell --seed 2019323 
(FPCore (x y z t)
  :name "Linear.V2:$cdot from linear-1.19.1.3, A"
  :precision binary64
  (+ (* x y) (* z t)))