Average Error: 5.8 → 2.3
Time: 6.3s
Precision: binary64
\[x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y} \]
\[x + \frac{1}{y} \]
(FPCore (x y z)
 :precision binary64
 (+ x (/ (exp (* y (log (/ y (+ z y))))) y)))
(FPCore (x y z) :precision binary64 (+ x (/ 1.0 y)))
double code(double x, double y, double z) {
	return x + (exp((y * log((y / (z + y))))) / y);
}
double code(double x, double y, double z) {
	return x + (1.0 / y);
}
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x + (exp((y * log((y / (z + y))))) / y)
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 + (1.0d0 / y)
end function
public static double code(double x, double y, double z) {
	return x + (Math.exp((y * Math.log((y / (z + y))))) / y);
}
public static double code(double x, double y, double z) {
	return x + (1.0 / y);
}
def code(x, y, z):
	return x + (math.exp((y * math.log((y / (z + y))))) / y)
def code(x, y, z):
	return x + (1.0 / y)
function code(x, y, z)
	return Float64(x + Float64(exp(Float64(y * log(Float64(y / Float64(z + y))))) / y))
end
function code(x, y, z)
	return Float64(x + Float64(1.0 / y))
end
function tmp = code(x, y, z)
	tmp = x + (exp((y * log((y / (z + y))))) / y);
end
function tmp = code(x, y, z)
	tmp = x + (1.0 / y);
end
code[x_, y_, z_] := N[(x + N[(N[Exp[N[(y * N[Log[N[(y / N[(z + y), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / y), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_] := N[(x + N[(1.0 / y), $MachinePrecision]), $MachinePrecision]
x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y}
x + \frac{1}{y}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original5.8
Target1.0
Herbie2.3
\[\begin{array}{l} \mathbf{if}\;\frac{y}{z + y} < 7.11541576 \cdot 10^{-315}:\\ \;\;\;\;x + \frac{e^{\frac{-1}{z}}}{y}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{e^{\log \left({\left(\frac{y}{y + z}\right)}^{y}\right)}}{y}\\ \end{array} \]

Derivation

  1. Initial program 5.8

    \[x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y} \]
  2. Simplified5.8

    \[\leadsto \color{blue}{x + \frac{{\left(\frac{y}{y + z}\right)}^{y}}{y}} \]
  3. Taylor expanded in y around 0 2.3

    \[\leadsto x + \frac{\color{blue}{1}}{y} \]
  4. Final simplification2.3

    \[\leadsto x + \frac{1}{y} \]

Reproduce

herbie shell --seed 2022162 
(FPCore (x y z)
  :name "Numeric.SpecFunctions:invIncompleteBetaWorker from math-functions-0.1.5.2, G"
  :precision binary64

  :herbie-target
  (if (< (/ y (+ z y)) 7.11541576e-315) (+ x (/ (exp (/ -1.0 z)) y)) (+ x (/ (exp (log (pow (/ y (+ y z)) y))) y)))

  (+ x (/ (exp (* y (log (/ y (+ z y))))) y)))