# ?

Average Error: 0.0 → 0.0
Time: 4.4s
Precision: binary64
Cost: 6592

# ?

$0 \leq x \land x \leq 1.79 \cdot 10^{+308}$
$\sqrt{1 - x}$
$\sqrt{1 - x}$
(FPCore (x) :precision binary64 (sqrt (- 1.0 x)))
(FPCore (x) :precision binary64 (sqrt (- 1.0 x)))
double code(double x) {
return sqrt((1.0 - x));
}

double code(double x) {
return sqrt((1.0 - x));
}

real(8) function code(x)
real(8), intent (in) :: x
code = sqrt((1.0d0 - x))
end function

real(8) function code(x)
real(8), intent (in) :: x
code = sqrt((1.0d0 - x))
end function

public static double code(double x) {
return Math.sqrt((1.0 - x));
}

public static double code(double x) {
return Math.sqrt((1.0 - x));
}

def code(x):
return math.sqrt((1.0 - x))

def code(x):
return math.sqrt((1.0 - x))

function code(x)
return sqrt(Float64(1.0 - x))
end

function code(x)
return sqrt(Float64(1.0 - x))
end

function tmp = code(x)
tmp = sqrt((1.0 - x));
end

function tmp = code(x)
tmp = sqrt((1.0 - x));
end

code[x_] := N[Sqrt[N[(1.0 - x), $MachinePrecision]],$MachinePrecision]

code[x_] := N[Sqrt[N[(1.0 - x), $MachinePrecision]],$MachinePrecision]

\sqrt{1 - x}

\sqrt{1 - x}


# Try it out?

Results

 In Out
Enter valid numbers for all inputs

# Derivation?

1. Initial program 0.0

$\sqrt{1 - x}$
2. Final simplification0.0

$\leadsto \sqrt{1 - x}$

# Alternatives

Alternative 1
Error0.4
Cost704
$\left(2 + x \cdot \left(x \cdot -0.125 + -0.5\right)\right) + -1$
Alternative 2
Error0.6
Cost320
$1 + x \cdot -0.5$
Alternative 3
Error1.4
Cost64
$1$

# Reproduce?

herbie shell --seed 1
(FPCore (x)
:name "sqrt(1-x)"
:precision binary64
:pre (and (<= 0.0 x) (<= x 1.79e+308))
(sqrt (- 1.0 x)))