?

Average Accuracy: 100.0% → 100.0%
Time: 2.5s
Precision: binary64
Cost: 6784

?

\[x \cdot y - z \cdot t \]
\[\mathsf{fma}\left(-z, t, x \cdot y\right) \]
(FPCore (x y z t) :precision binary64 (- (* x y) (* z t)))
(FPCore (x y z t) :precision binary64 (fma (- z) t (* x y)))
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 fma(-z, t, (x * y));
}
function code(x, y, z, t)
	return Float64(Float64(x * y) - Float64(z * t))
end
function code(x, y, z, t)
	return fma(Float64(-z), t, Float64(x * y))
end
code[x_, y_, z_, t_] := N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_, t_] := N[((-z) * t + N[(x * y), $MachinePrecision]), $MachinePrecision]
x \cdot y - z \cdot t
\mathsf{fma}\left(-z, t, x \cdot y\right)

Error?

Derivation?

  1. Initial program 100.0%

    \[x \cdot y - z \cdot t \]
  2. Applied egg-rr100.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(-z, t, x \cdot y\right)} \]
    Proof

    [Start]100.0

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

    sub-neg [=>]100.0

    \[ \color{blue}{x \cdot y + \left(-z \cdot t\right)} \]

    +-commutative [=>]100.0

    \[ \color{blue}{\left(-z \cdot t\right) + x \cdot y} \]

    distribute-lft-neg-in [=>]100.0

    \[ \color{blue}{\left(-z\right) \cdot t} + x \cdot y \]

    fma-def [=>]100.0

    \[ \color{blue}{\mathsf{fma}\left(-z, t, x \cdot y\right)} \]
  3. Final simplification100.0%

    \[\leadsto \mathsf{fma}\left(-z, t, x \cdot y\right) \]

Alternatives

Alternative 1
Accuracy65.0%
Cost1051
\[\begin{array}{l} \mathbf{if}\;t \leq -8.2 \cdot 10^{-103} \lor \neg \left(t \leq 6.2 \cdot 10^{-144}\right) \land \left(t \leq 2.4 \cdot 10^{-133} \lor \neg \left(t \leq 1.75 \cdot 10^{-46}\right) \land \left(t \leq 4 \cdot 10^{-17} \lor \neg \left(t \leq 8 \cdot 10^{+47}\right)\right)\right):\\ \;\;\;\;z \cdot \left(-t\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot y\\ \end{array} \]
Alternative 2
Accuracy100.0%
Cost448
\[x \cdot y - z \cdot t \]
Alternative 3
Accuracy52.2%
Cost192
\[x \cdot y \]

Error

Reproduce?

herbie shell --seed 2023147 
(FPCore (x y z t)
  :name "Linear.V3:cross from linear-1.19.1.3"
  :precision binary64
  (- (* x y) (* z t)))