Average Error: 0.0 → 0.0
Time: 2.1s
Precision: binary64
Cost: 448
\[x \cdot y + z \cdot t\]
↓
\[x \cdot y + z \cdot t\]
x \cdot y + z \cdot t
↓
x \cdot y + z \cdot t
(FPCore (x y z t) :precision binary64 (+ (* x y) (* z t)))
↓
(FPCore (x y z t) :precision binary64 (+ (* x y) (* z t)))
double code(double x, double y, double z, double t) {
	return (x * y) + (z * t);
}
↓
double code(double x, double y, double z, double t) {
	return (x * y) + (z * t);
}

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

Alternatives

Alternative 1
Error16.5
Cost1297
\[\begin{array}{l} \mathbf{if}\;x \cdot y \leq -3.8168513046105537 \cdot 10^{+43} \lor \neg \left(x \cdot y \leq -1.475637455351863 \cdot 10^{-24} \lor \neg \left(x \cdot y \leq -1.468320221817705 \cdot 10^{-66}\right) \land x \cdot y \leq 6926372935188991\right):\\ \;\;\;\;x \cdot y\\ \mathbf{else}:\\ \;\;\;\;z \cdot t\\ \end{array}\]
Alternative 2
Error30.9
Cost192
\[x \cdot y\]
Alternative 3
Error61.0
Cost64
\[0\]
Alternative 4
Error61.7
Cost64
\[1\]

Error

Derivation

  1. Initial program 0.0

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

  2. Simplified0.0

    \[\leadsto \color{blue}{x \cdot y + z \cdot t}\]

  3. Final simplification0.0

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

Reproduce

herbie shell --seed 2021044 
(FPCore (x y z t)
  :name "Linear.V2:$cdot from linear-1.19.1.3, A"
  :precision binary64
  (+ (* x y) (* z t)))