Average Error: 0.0 → 0.0
Time: 1.6s
Precision: binary64
\[x \cdot x - y \cdot y \]
\[\mathsf{fma}\left(x, x, -y \cdot y\right) \]
(FPCore (x y) :precision binary64 (- (* x x) (* y y)))
(FPCore (x y) :precision binary64 (fma x x (- (* y y))))
double code(double x, double y) {
	return (x * x) - (y * y);
}
double code(double x, double y) {
	return fma(x, x, -(y * y));
}
function code(x, y)
	return Float64(Float64(x * x) - Float64(y * y))
end
function code(x, y)
	return fma(x, x, Float64(-Float64(y * y)))
end
code[x_, y_] := N[(N[(x * x), $MachinePrecision] - N[(y * y), $MachinePrecision]), $MachinePrecision]
code[x_, y_] := N[(x * x + (-N[(y * y), $MachinePrecision])), $MachinePrecision]
x \cdot x - y \cdot y
\mathsf{fma}\left(x, x, -y \cdot y\right)

Error

Bits error versus x

Bits error versus y

Derivation

  1. Initial program 0.0

    \[x \cdot x - y \cdot y \]
  2. Applied fma-neg_binary640.0

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, x, -y \cdot y\right)} \]
  3. Final simplification0.0

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

Reproduce

herbie shell --seed 2022131 
(FPCore (x y)
  :name "Examples.Basics.BasicTests:f2 from sbv-4.4"
  :precision binary64
  (- (* x x) (* y y)))