Average Error: 0.1 → 0.0
Time: 8.3s
Precision: 64
$b \lt m$
$x \cdot \left(1 - \frac{b}{m}\right)$
$1 \cdot x + \left(-\frac{x \cdot b}{m}\right)$
x \cdot \left(1 - \frac{b}{m}\right)
1 \cdot x + \left(-\frac{x \cdot b}{m}\right)
double f(double x, double b, double m) {
double r2498871 = x;
double r2498872 = 1.0;
double r2498873 = b;
double r2498874 = m;
double r2498875 = r2498873 / r2498874;
double r2498876 = r2498872 - r2498875;
double r2498877 = r2498871 * r2498876;
return r2498877;
}


double f(double x, double b, double m) {
double r2498878 = 1.0;
double r2498879 = x;
double r2498880 = r2498878 * r2498879;
double r2498881 = b;
double r2498882 = r2498879 * r2498881;
double r2498883 = m;
double r2498884 = r2498882 / r2498883;
double r2498885 = -r2498884;
double r2498886 = r2498880 + r2498885;
return r2498886;
}



# Try it out

Results

 In Out
Enter valid numbers for all inputs

# Derivation

1. Initial program 0.1

$x \cdot \left(1 - \frac{b}{m}\right)$
2. Using strategy rm
3. Applied sub-neg0.1

$\leadsto x \cdot \color{blue}{\left(1 + \left(-\frac{b}{m}\right)\right)}$
4. Applied distribute-lft-in0.1

$\leadsto \color{blue}{x \cdot 1 + x \cdot \left(-\frac{b}{m}\right)}$
5. Simplified0.1

$\leadsto \color{blue}{1 \cdot x} + x \cdot \left(-\frac{b}{m}\right)$
6. Simplified0.0

$\leadsto 1 \cdot x + \color{blue}{\left(-\frac{x \cdot b}{m}\right)}$
7. Final simplification0.0

$\leadsto 1 \cdot x + \left(-\frac{x \cdot b}{m}\right)$

# Reproduce

herbie shell --seed 1
(FPCore (x b m)
:name "(x * (1.0 - b/m))"
:precision binary32
:pre (< b m)
(* x (- 1 (/ b m))))