?

Average Accuracy: 100.0% → 100.0%
Time: 4.0s
Precision: binary64
Cost: 448

?

\[\left(x + y\right) \cdot \left(z + 1\right) \]
\[\left(x + y\right) \cdot \left(z + 1\right) \]
(FPCore (x y z) :precision binary64 (* (+ x y) (+ z 1.0)))
(FPCore (x y z) :precision binary64 (* (+ x y) (+ z 1.0)))
double code(double x, double y, double z) {
	return (x + y) * (z + 1.0);
}
double code(double x, double y, double z) {
	return (x + y) * (z + 1.0);
}
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = (x + y) * (z + 1.0d0)
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 = (x + y) * (z + 1.0d0)
end function
public static double code(double x, double y, double z) {
	return (x + y) * (z + 1.0);
}
public static double code(double x, double y, double z) {
	return (x + y) * (z + 1.0);
}
def code(x, y, z):
	return (x + y) * (z + 1.0)
def code(x, y, z):
	return (x + y) * (z + 1.0)
function code(x, y, z)
	return Float64(Float64(x + y) * Float64(z + 1.0))
end
function code(x, y, z)
	return Float64(Float64(x + y) * Float64(z + 1.0))
end
function tmp = code(x, y, z)
	tmp = (x + y) * (z + 1.0);
end
function tmp = code(x, y, z)
	tmp = (x + y) * (z + 1.0);
end
code[x_, y_, z_] := N[(N[(x + y), $MachinePrecision] * N[(z + 1.0), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_] := N[(N[(x + y), $MachinePrecision] * N[(z + 1.0), $MachinePrecision]), $MachinePrecision]
\left(x + y\right) \cdot \left(z + 1\right)
\left(x + y\right) \cdot \left(z + 1\right)

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 100.0%

    \[\left(x + y\right) \cdot \left(z + 1\right) \]
  2. Final simplification100.0%

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

Alternatives

Alternative 1
Accuracy48.6%
Cost1248
\[\begin{array}{l} \mathbf{if}\;z \leq -1.6 \cdot 10^{+80}:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq -5 \cdot 10^{+43}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;z \leq -1:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq -2.9 \cdot 10^{-147}:\\ \;\;\;\;y\\ \mathbf{elif}\;z \leq -4 \cdot 10^{-212}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 1:\\ \;\;\;\;y\\ \mathbf{elif}\;z \leq 4 \cdot 10^{+101}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;z \leq 1.42 \cdot 10^{+169}:\\ \;\;\;\;x \cdot z\\ \mathbf{else}:\\ \;\;\;\;y \cdot z\\ \end{array} \]
Alternative 2
Accuracy79.5%
Cost984
\[\begin{array}{l} \mathbf{if}\;z \leq -2.2 \cdot 10^{+80}:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq -9.5 \cdot 10^{+40}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;z \leq -1:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq 3100:\\ \;\;\;\;x + y\\ \mathbf{elif}\;z \leq 5.8 \cdot 10^{+101}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;z \leq 1.32 \cdot 10^{+169}:\\ \;\;\;\;x \cdot z\\ \mathbf{else}:\\ \;\;\;\;y \cdot z\\ \end{array} \]
Alternative 3
Accuracy79.7%
Cost984
\[\begin{array}{l} \mathbf{if}\;z \leq -2.2 \cdot 10^{+79}:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq -1.75 \cdot 10^{+41}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;z \leq -1:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq 2600:\\ \;\;\;\;x + y\\ \mathbf{elif}\;z \leq 6 \cdot 10^{+100}:\\ \;\;\;\;y \cdot \left(z + 1\right)\\ \mathbf{elif}\;z \leq 2.1 \cdot 10^{+168}:\\ \;\;\;\;x \cdot z\\ \mathbf{else}:\\ \;\;\;\;y \cdot z\\ \end{array} \]
Alternative 4
Accuracy80.1%
Cost984
\[\begin{array}{l} \mathbf{if}\;z \leq -1 \cdot 10^{+80}:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;z \leq -2.3 \cdot 10^{+42}:\\ \;\;\;\;y \cdot z\\ \mathbf{elif}\;z \leq -6.6 \cdot 10^{-6}:\\ \;\;\;\;x \cdot \left(z + 1\right)\\ \mathbf{elif}\;z \leq 2600:\\ \;\;\;\;x + y\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{+100}:\\ \;\;\;\;y \cdot \left(z + 1\right)\\ \mathbf{elif}\;z \leq 8.5 \cdot 10^{+167}:\\ \;\;\;\;x \cdot z\\ \mathbf{else}:\\ \;\;\;\;y \cdot z\\ \end{array} \]
Alternative 5
Accuracy97.3%
Cost585
\[\begin{array}{l} \mathbf{if}\;z \leq -1 \lor \neg \left(z \leq 1\right):\\ \;\;\;\;z \cdot \left(x + y\right)\\ \mathbf{else}:\\ \;\;\;\;x + y\\ \end{array} \]
Alternative 6
Accuracy38.4%
Cost460
\[\begin{array}{l} \mathbf{if}\;x \leq -1.9 \cdot 10^{+86}:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq -8.6 \cdot 10^{+37}:\\ \;\;\;\;x \cdot z\\ \mathbf{elif}\;x \leq -2.9 \cdot 10^{-136}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y\\ \end{array} \]
Alternative 7
Accuracy38.7%
Cost196
\[\begin{array}{l} \mathbf{if}\;x \leq -2.3 \cdot 10^{-136}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y\\ \end{array} \]
Alternative 8
Accuracy32.8%
Cost64
\[x \]

Error

Reproduce?

herbie shell --seed 2023133 
(FPCore (x y z)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, G"
  :precision binary64
  (* (+ x y) (+ z 1.0)))