?

Average Accuracy: 100.0% → 100.0%
Time: 3.1s
Precision: binary64
Cost: 6720

?

\[\left(x + y\right) - x \cdot y \]
\[\mathsf{fma}\left(x, 1 - y, y\right) \]
(FPCore (x y) :precision binary64 (- (+ x y) (* x y)))
(FPCore (x y) :precision binary64 (fma x (- 1.0 y) y))
double code(double x, double y) {
	return (x + y) - (x * y);
}
double code(double x, double y) {
	return fma(x, (1.0 - y), y);
}
function code(x, y)
	return Float64(Float64(x + y) - Float64(x * y))
end
function code(x, y)
	return fma(x, Float64(1.0 - y), y)
end
code[x_, y_] := N[(N[(x + y), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]
code[x_, y_] := N[(x * N[(1.0 - y), $MachinePrecision] + y), $MachinePrecision]
\left(x + y\right) - x \cdot y
\mathsf{fma}\left(x, 1 - y, y\right)

Error?

Derivation?

  1. Initial program 100.0%

    \[\left(x + y\right) - x \cdot y \]
  2. Simplified100.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, 1 - y, y\right)} \]
    Proof

    [Start]100.0

    \[ \left(x + y\right) - x \cdot y \]

    +-commutative [=>]100.0

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

    associate--l+ [=>]100.0

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

    +-commutative [=>]100.0

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

    *-rgt-identity [<=]100.0

    \[ \left(\color{blue}{x \cdot 1} - x \cdot y\right) + y \]

    distribute-lft-out-- [=>]100.0

    \[ \color{blue}{x \cdot \left(1 - y\right)} + y \]

    unsub-neg [<=]100.0

    \[ x \cdot \color{blue}{\left(1 + \left(-y\right)\right)} + y \]

    +-commutative [<=]100.0

    \[ x \cdot \color{blue}{\left(\left(-y\right) + 1\right)} + y \]

    fma-def [=>]100.0

    \[ \color{blue}{\mathsf{fma}\left(x, \left(-y\right) + 1, y\right)} \]

    +-commutative [=>]100.0

    \[ \mathsf{fma}\left(x, \color{blue}{1 + \left(-y\right)}, y\right) \]

    unsub-neg [=>]100.0

    \[ \mathsf{fma}\left(x, \color{blue}{1 - y}, y\right) \]
  3. Final simplification100.0%

    \[\leadsto \mathsf{fma}\left(x, 1 - y, y\right) \]

Alternatives

Alternative 1
Accuracy63.2%
Cost784
\[\begin{array}{l} t_0 := y \cdot \left(-x\right)\\ \mathbf{if}\;y \leq -1:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{-34}:\\ \;\;\;\;x\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+59}:\\ \;\;\;\;y\\ \mathbf{elif}\;y \leq 2.9 \cdot 10^{+66}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;y\\ \end{array} \]
Alternative 2
Accuracy67.9%
Cost717
\[\begin{array}{l} \mathbf{if}\;x \leq -17 \lor \neg \left(x \leq -3 \cdot 10^{-19}\right) \land x \leq -1.26 \cdot 10^{-159}:\\ \;\;\;\;x \cdot \left(1 - y\right)\\ \mathbf{else}:\\ \;\;\;\;y - x \cdot y\\ \end{array} \]
Alternative 3
Accuracy81.3%
Cost585
\[\begin{array}{l} \mathbf{if}\;x \leq -1.26 \cdot 10^{-159} \lor \neg \left(x \leq 0.08\right):\\ \;\;\;\;x \cdot \left(1 - y\right)\\ \mathbf{else}:\\ \;\;\;\;y\\ \end{array} \]
Alternative 4
Accuracy53.5%
Cost460
\[\begin{array}{l} \mathbf{if}\;x \leq -9.2 \cdot 10^{-8}:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq -9.5 \cdot 10^{-21}:\\ \;\;\;\;y\\ \mathbf{elif}\;x \leq -1.26 \cdot 10^{-159}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y\\ \end{array} \]
Alternative 5
Accuracy100.0%
Cost448
\[\left(x + y\right) - x \cdot y \]
Alternative 6
Accuracy42.6%
Cost64
\[x \]

Error

Reproduce?

herbie shell --seed 2023151 
(FPCore (x y)
  :name "Data.Colour.RGBSpace.HSL:hsl from colour-2.3.3, A"
  :precision binary64
  (- (+ x y) (* x y)))