?

Average Error: 8.13% → 0.14%
Time: 7.1s
Precision: binary64
Cost: 6720

?

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

Error?

Target

Original8.13%
Target0.14%
Herbie0.14%
\[x + \left(x \cdot y\right) \cdot y \]

Derivation?

  1. Initial program 8.13

    \[x \cdot \left(1 + y \cdot y\right) \]
  2. Simplified8.11

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

    [Start]8.13

    \[ x \cdot \left(1 + y \cdot y\right) \]

    distribute-lft-in [=>]8.12

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

    +-commutative [=>]8.12

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

    *-rgt-identity [=>]8.12

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

    fma-def [=>]8.11

    \[ \color{blue}{\mathsf{fma}\left(x, y \cdot y, x\right)} \]
  3. Taylor expanded in x around 0 8.13

    \[\leadsto \color{blue}{\left(1 + {y}^{2}\right) \cdot x} \]
  4. Simplified0.14

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

    [Start]8.13

    \[ \left(1 + {y}^{2}\right) \cdot x \]

    +-commutative [=>]8.13

    \[ \color{blue}{\left({y}^{2} + 1\right)} \cdot x \]

    distribute-lft1-in [<=]8.12

    \[ \color{blue}{{y}^{2} \cdot x + x} \]

    unpow2 [=>]8.12

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

    associate-*l* [=>]0.14

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

    *-commutative [<=]0.14

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

    fma-def [=>]0.14

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

    *-commutative [=>]0.14

    \[ \mathsf{fma}\left(y, \color{blue}{y \cdot x}, x\right) \]
  5. Final simplification0.14

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

Alternatives

Alternative 1
Error0.15%
Cost708
\[\begin{array}{l} \mathbf{if}\;y \cdot y \leq 2 \cdot 10^{+23}:\\ \;\;\;\;x \cdot \left(y \cdot y + 1\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(y \cdot x\right)\\ \end{array} \]
Alternative 2
Error0.14%
Cost708
\[\begin{array}{l} \mathbf{if}\;y \cdot y \leq 2 \cdot 10^{+23}:\\ \;\;\;\;x + x \cdot \left(y \cdot y\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(y \cdot x\right)\\ \end{array} \]
Alternative 3
Error9.64%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -1 \lor \neg \left(y \leq 1\right):\\ \;\;\;\;x \cdot \left(y \cdot y\right)\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]
Alternative 4
Error1.67%
Cost580
\[\begin{array}{l} \mathbf{if}\;y \cdot y \leq 1:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(y \cdot x\right)\\ \end{array} \]
Alternative 5
Error0.14%
Cost448
\[x + y \cdot \left(y \cdot x\right) \]
Alternative 6
Error32.33%
Cost64
\[x \]

Error

Reproduce?

herbie shell --seed 2023121 
(FPCore (x y)
  :name "Numeric.Integration.TanhSinh:everywhere from integration-0.2.1"
  :precision binary64

  :herbie-target
  (+ x (* (* x y) y))

  (* x (+ 1.0 (* y y))))