Average Error: 0.0 → 0.0
Time: 8.7s
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 r103153 = x;
        double r103154 = y;
        double r103155 = r103153 * r103154;
        double r103156 = z;
        double r103157 = t;
        double r103158 = r103156 * r103157;
        double r103159 = r103155 + r103158;
        return r103159;
}
↓
double f(double x, double y, double z, double t) {
        double r103160 = x;
        double r103161 = y;
        double r103162 = r103160 * r103161;
        double r103163 = z;
        double r103164 = t;
        double r103165 = r103163 * r103164;
        double r103166 = r103162 + r103165;
        return r103166;
}

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 2019326 
(FPCore (x y z t)
  :name "Linear.V2:$cdot from linear-1.19.1.3, A"
  :precision binary64
  (+ (* x y) (* z t)))