Average Error: 0.1 → 0.1
Time: 6.2s
Precision: binary64
\[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z\]
\[\left(y + \left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \left(\left(y + 0.5\right) \cdot 0.3333333333333333\right) \cdot \log y\right)\right)\right) - z\]
\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z
\left(y + \left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \left(\left(y + 0.5\right) \cdot 0.3333333333333333\right) \cdot \log y\right)\right)\right) - z
(FPCore (x y z) :precision binary64 (- (+ (- x (* (+ y 0.5) (log y))) y) z))
(FPCore (x y z)
 :precision binary64
 (-
  (+
   y
   (-
    x
    (+
     (* (+ y 0.5) (* 2.0 (log (cbrt y))))
     (* (* (+ y 0.5) 0.3333333333333333) (log y)))))
  z))
double code(double x, double y, double z) {
	return ((x - ((y + 0.5) * log(y))) + y) - z;
}
double code(double x, double y, double z) {
	return (y + (x - (((y + 0.5) * (2.0 * log(cbrt(y)))) + (((y + 0.5) * 0.3333333333333333) * log(y))))) - z;
}

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

Original0.1
Target0.1
Herbie0.1
\[\left(\left(y + x\right) - z\right) - \left(y + 0.5\right) \cdot \log y\]

Derivation

  1. Initial program 0.1

    \[\left(\left(x - \left(y + 0.5\right) \cdot \log y\right) + y\right) - z\]
  2. Using strategy rm
  3. Applied add-cube-cbrt_binary64_112300.1

    \[\leadsto \left(\left(x - \left(y + 0.5\right) \cdot \log \color{blue}{\left(\left(\sqrt[3]{y} \cdot \sqrt[3]{y}\right) \cdot \sqrt[3]{y}\right)}\right) + y\right) - z\]
  4. Applied log-prod_binary64_112810.2

    \[\leadsto \left(\left(x - \left(y + 0.5\right) \cdot \color{blue}{\left(\log \left(\sqrt[3]{y} \cdot \sqrt[3]{y}\right) + \log \left(\sqrt[3]{y}\right)\right)}\right) + y\right) - z\]
  5. Applied distribute-rgt-in_binary64_111500.2

    \[\leadsto \left(\left(x - \color{blue}{\left(\log \left(\sqrt[3]{y} \cdot \sqrt[3]{y}\right) \cdot \left(y + 0.5\right) + \log \left(\sqrt[3]{y}\right) \cdot \left(y + 0.5\right)\right)}\right) + y\right) - z\]
  6. Simplified0.2

    \[\leadsto \left(\left(x - \left(\color{blue}{\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right)} + \log \left(\sqrt[3]{y}\right) \cdot \left(y + 0.5\right)\right)\right) + y\right) - z\]
  7. Simplified0.2

    \[\leadsto \left(\left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \color{blue}{\left(y + 0.5\right) \cdot \log \left(\sqrt[3]{y}\right)}\right)\right) + y\right) - z\]
  8. Using strategy rm
  9. Applied pow1/3_binary64_112770.2

    \[\leadsto \left(\left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \left(y + 0.5\right) \cdot \log \color{blue}{\left({y}^{0.3333333333333333}\right)}\right)\right) + y\right) - z\]
  10. Applied log-pow_binary64_112840.2

    \[\leadsto \left(\left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \left(y + 0.5\right) \cdot \color{blue}{\left(0.3333333333333333 \cdot \log y\right)}\right)\right) + y\right) - z\]
  11. Applied associate-*r*_binary64_111400.1

    \[\leadsto \left(\left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \color{blue}{\left(\left(y + 0.5\right) \cdot 0.3333333333333333\right) \cdot \log y}\right)\right) + y\right) - z\]
  12. Final simplification0.1

    \[\leadsto \left(y + \left(x - \left(\left(y + 0.5\right) \cdot \left(2 \cdot \log \left(\sqrt[3]{y}\right)\right) + \left(\left(y + 0.5\right) \cdot 0.3333333333333333\right) \cdot \log y\right)\right)\right) - z\]

Reproduce

herbie shell --seed 2020280 
(FPCore (x y z)
  :name "Numeric.SpecFunctions:stirlingError from math-functions-0.1.5.2"
  :precision binary64

  :herbie-target
  (- (- (+ y x) z) (* (+ y 0.5) (log y)))

  (- (+ (- x (* (+ y 0.5) (log y))) y) z))