?

Average Accuracy: 100.0% → 100.0%
Time: 3.2s
Precision: binary64
Cost: 448

?

\[\left(\frac{x}{2} + y \cdot x\right) + z \]
\[z + \left(0.5 + y\right) \cdot x \]
(FPCore (x y z) :precision binary64 (+ (+ (/ x 2.0) (* y x)) z))
(FPCore (x y z) :precision binary64 (+ z (* (+ 0.5 y) x)))
double code(double x, double y, double z) {
	return ((x / 2.0) + (y * x)) + z;
}
double code(double x, double y, double z) {
	return z + ((0.5 + y) * x);
}
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = ((x / 2.0d0) + (y * x)) + z
end function
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = z + ((0.5d0 + y) * x)
end function
public static double code(double x, double y, double z) {
	return ((x / 2.0) + (y * x)) + z;
}
public static double code(double x, double y, double z) {
	return z + ((0.5 + y) * x);
}
def code(x, y, z):
	return ((x / 2.0) + (y * x)) + z
def code(x, y, z):
	return z + ((0.5 + y) * x)
function code(x, y, z)
	return Float64(Float64(Float64(x / 2.0) + Float64(y * x)) + z)
end
function code(x, y, z)
	return Float64(z + Float64(Float64(0.5 + y) * x))
end
function tmp = code(x, y, z)
	tmp = ((x / 2.0) + (y * x)) + z;
end
function tmp = code(x, y, z)
	tmp = z + ((0.5 + y) * x);
end
code[x_, y_, z_] := N[(N[(N[(x / 2.0), $MachinePrecision] + N[(y * x), $MachinePrecision]), $MachinePrecision] + z), $MachinePrecision]
code[x_, y_, z_] := N[(z + N[(N[(0.5 + y), $MachinePrecision] * x), $MachinePrecision]), $MachinePrecision]
\left(\frac{x}{2} + y \cdot x\right) + z
z + \left(0.5 + y\right) \cdot x

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 100.0%

    \[\left(\frac{x}{2} + y \cdot x\right) + z \]
  2. Simplified100.0%

    \[\leadsto \color{blue}{\frac{x}{2} + \left(x \cdot y + z\right)} \]
    Proof

    [Start]100.0

    \[ \left(\frac{x}{2} + y \cdot x\right) + z \]

    associate-+l+ [=>]100.0

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

    *-commutative [=>]100.0

    \[ \frac{x}{2} + \left(\color{blue}{x \cdot y} + z\right) \]
  3. Taylor expanded in x around 0 100.0%

    \[\leadsto \color{blue}{z + \left(0.5 + y\right) \cdot x} \]
  4. Final simplification100.0%

    \[\leadsto z + \left(0.5 + y\right) \cdot x \]

Alternatives

Alternative 1
Accuracy52.5%
Cost1116
\[\begin{array}{l} \mathbf{if}\;y \leq -0.5:\\ \;\;\;\;y \cdot x\\ \mathbf{elif}\;y \leq -1.45 \cdot 10^{-223}:\\ \;\;\;\;0.5 \cdot x\\ \mathbf{elif}\;y \leq -1.7 \cdot 10^{-246}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq 5.9 \cdot 10^{-207}:\\ \;\;\;\;0.5 \cdot x\\ \mathbf{elif}\;y \leq 1.15 \cdot 10^{-113}:\\ \;\;\;\;z\\ \mathbf{elif}\;y \leq 5.2 \cdot 10^{-17}:\\ \;\;\;\;0.5 \cdot x\\ \mathbf{elif}\;y \leq 2.4 \cdot 10^{+181}:\\ \;\;\;\;z\\ \mathbf{else}:\\ \;\;\;\;y \cdot x\\ \end{array} \]
Alternative 2
Accuracy83.7%
Cost585
\[\begin{array}{l} \mathbf{if}\;x \leq -4.5 \cdot 10^{+56} \lor \neg \left(x \leq 1.2 \cdot 10^{+48}\right):\\ \;\;\;\;\left(0.5 + y\right) \cdot x\\ \mathbf{else}:\\ \;\;\;\;z + y \cdot x\\ \end{array} \]
Alternative 3
Accuracy98.7%
Cost585
\[\begin{array}{l} \mathbf{if}\;y \leq -0.5 \lor \neg \left(y \leq 0.0115\right):\\ \;\;\;\;z + y \cdot x\\ \mathbf{else}:\\ \;\;\;\;z + \frac{x}{2}\\ \end{array} \]
Alternative 4
Accuracy76.0%
Cost584
\[\begin{array}{l} \mathbf{if}\;z \leq -5.5 \cdot 10^{+33}:\\ \;\;\;\;z\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+99}:\\ \;\;\;\;\left(0.5 + y\right) \cdot x\\ \mathbf{else}:\\ \;\;\;\;z\\ \end{array} \]
Alternative 5
Accuracy58.2%
Cost456
\[\begin{array}{l} \mathbf{if}\;x \leq -7.6 \cdot 10^{+55}:\\ \;\;\;\;0.5 \cdot x\\ \mathbf{elif}\;x \leq 2.7 \cdot 10^{+46}:\\ \;\;\;\;z\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot x\\ \end{array} \]
Alternative 6
Accuracy46.2%
Cost64
\[z \]

Error

Reproduce?

herbie shell --seed 2023137 
(FPCore (x y z)
  :name "Data.Histogram.Bin.BinF:$cfromIndex from histogram-fill-0.8.4.1"
  :precision binary64
  (+ (+ (/ x 2.0) (* y x)) z))