2cbrt (problem 3.3.4)

Percentage Accurate: 7.1% → 96.4%
Time: 3.4s
Alternatives: 11
Speedup: 1.9×

Specification

?
\[x > 1 \land x < 10^{+308}\]
\[\begin{array}{l} \\ \sqrt[3]{x + 1} - \sqrt[3]{x} \end{array} \]
(FPCore (x) :precision binary64 (- (cbrt (+ x 1.0)) (cbrt x)))
double code(double x) {
	return cbrt((x + 1.0)) - cbrt(x);
}
public static double code(double x) {
	return Math.cbrt((x + 1.0)) - Math.cbrt(x);
}
function code(x)
	return Float64(cbrt(Float64(x + 1.0)) - cbrt(x))
end
code[x_] := N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\sqrt[3]{x + 1} - \sqrt[3]{x}
\end{array}

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 11 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 7.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt[3]{x + 1} - \sqrt[3]{x} \end{array} \]
(FPCore (x) :precision binary64 (- (cbrt (+ x 1.0)) (cbrt x)))
double code(double x) {
	return cbrt((x + 1.0)) - cbrt(x);
}
public static double code(double x) {
	return Math.cbrt((x + 1.0)) - Math.cbrt(x);
}
function code(x)
	return Float64(cbrt(Float64(x + 1.0)) - cbrt(x))
end
code[x_] := N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\sqrt[3]{x + 1} - \sqrt[3]{x}
\end{array}

Alternative 1: 96.4% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \frac{\sqrt[3]{{x}^{-1}}}{\sqrt[3]{x}} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x)
 :precision binary64
 (* (/ (cbrt (pow x -1.0)) (cbrt x)) 0.3333333333333333))
double code(double x) {
	return (cbrt(pow(x, -1.0)) / cbrt(x)) * 0.3333333333333333;
}
public static double code(double x) {
	return (Math.cbrt(Math.pow(x, -1.0)) / Math.cbrt(x)) * 0.3333333333333333;
}
function code(x)
	return Float64(Float64(cbrt((x ^ -1.0)) / cbrt(x)) * 0.3333333333333333)
end
code[x_] := N[(N[(N[Power[N[Power[x, -1.0], $MachinePrecision], 1/3], $MachinePrecision] / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
\frac{\sqrt[3]{{x}^{-1}}}{\sqrt[3]{x}} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    2. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    4. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    5. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    6. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    7. pow1/3N/A

      \[\leadsto \frac{1}{{\left({x}^{2}\right)}^{\frac{1}{3}}} \cdot \frac{1}{3} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{1}}{{\left({x}^{2}\right)}^{\frac{1}{3}}} \cdot \frac{1}{3} \]
    9. pow1/3N/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. cbrt-divN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    11. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{-1 \cdot -1}{{x}^{2}}} \cdot \frac{1}{3} \]
    12. unpow2N/A

      \[\leadsto \sqrt[3]{\frac{-1 \cdot -1}{x \cdot x}} \cdot \frac{1}{3} \]
    13. frac-timesN/A

      \[\leadsto \sqrt[3]{\frac{-1}{x} \cdot \frac{-1}{x}} \cdot \frac{1}{3} \]
    14. associate-*r/N/A

      \[\leadsto \sqrt[3]{\frac{\frac{-1}{x} \cdot -1}{x}} \cdot \frac{1}{3} \]
    15. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{\frac{-1}{x} \cdot -1}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    16. associate-*l/N/A

      \[\leadsto \frac{\sqrt[3]{\frac{-1 \cdot -1}{x}}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    17. metadata-evalN/A

      \[\leadsto \frac{\sqrt[3]{\frac{1}{x}}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    18. lower-/.f64N/A

      \[\leadsto \frac{\sqrt[3]{\frac{1}{x}}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    19. lower-cbrt.f64N/A

      \[\leadsto \frac{\sqrt[3]{\frac{1}{x}}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    20. inv-powN/A

      \[\leadsto \frac{\sqrt[3]{{x}^{-1}}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    21. lower-pow.f64N/A

      \[\leadsto \frac{\sqrt[3]{{x}^{-1}}}{\sqrt[3]{x}} \cdot \frac{1}{3} \]
    22. lift-cbrt.f6496.4

      \[\leadsto \frac{\sqrt[3]{{x}^{-1}}}{\sqrt[3]{x}} \cdot 0.3333333333333333 \]
  11. Applied rewrites96.4%

    \[\leadsto \frac{\sqrt[3]{{x}^{-1}}}{\sqrt[3]{x}} \cdot 0.3333333333333333 \]
  12. Add Preprocessing

Alternative 2: 96.4% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \frac{1}{\sqrt[3]{x}} \cdot \frac{0.3333333333333333}{\sqrt[3]{x}} \end{array} \]
(FPCore (x)
 :precision binary64
 (* (/ 1.0 (cbrt x)) (/ 0.3333333333333333 (cbrt x))))
double code(double x) {
	return (1.0 / cbrt(x)) * (0.3333333333333333 / cbrt(x));
}
public static double code(double x) {
	return (1.0 / Math.cbrt(x)) * (0.3333333333333333 / Math.cbrt(x));
}
function code(x)
	return Float64(Float64(1.0 / cbrt(x)) * Float64(0.3333333333333333 / cbrt(x)))
end
code[x_] := N[(N[(1.0 / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] * N[(0.3333333333333333 / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{1}{\sqrt[3]{x}} \cdot \frac{0.3333333333333333}{\sqrt[3]{x}}
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lift-/.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    3. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    5. associate-*l/N/A

      \[\leadsto \frac{1 \cdot \frac{1}{3}}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
    6. unpow2N/A

      \[\leadsto \frac{1 \cdot \frac{1}{3}}{\sqrt[3]{x} \cdot \color{blue}{\sqrt[3]{x}}} \]
    7. times-fracN/A

      \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \color{blue}{\frac{\frac{1}{3}}{\sqrt[3]{x}}} \]
    8. pow1/3N/A

      \[\leadsto \frac{1}{{x}^{\frac{1}{3}}} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    9. pow-negN/A

      \[\leadsto {x}^{\left(\mathsf{neg}\left(\frac{1}{3}\right)\right)} \cdot \frac{\color{blue}{\frac{1}{3}}}{\sqrt[3]{x}} \]
    10. metadata-evalN/A

      \[\leadsto {x}^{\frac{-1}{3}} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    11. metadata-evalN/A

      \[\leadsto {x}^{\left(\frac{\frac{-2}{3}}{2}\right)} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    12. lower-*.f64N/A

      \[\leadsto {x}^{\left(\frac{\frac{-2}{3}}{2}\right)} \cdot \color{blue}{\frac{\frac{1}{3}}{\sqrt[3]{x}}} \]
    13. metadata-evalN/A

      \[\leadsto {x}^{\frac{-1}{3}} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    14. metadata-evalN/A

      \[\leadsto {x}^{\left(\mathsf{neg}\left(\frac{1}{3}\right)\right)} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    15. pow-negN/A

      \[\leadsto \frac{1}{{x}^{\frac{1}{3}}} \cdot \frac{\color{blue}{\frac{1}{3}}}{\sqrt[3]{x}} \]
    16. pow1/3N/A

      \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    17. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \frac{\color{blue}{\frac{1}{3}}}{\sqrt[3]{x}} \]
    18. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \frac{\frac{1}{3}}{\sqrt[3]{x}} \]
    19. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \frac{\frac{1}{3}}{\color{blue}{\sqrt[3]{x}}} \]
    20. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \frac{0.3333333333333333}{\sqrt[3]{x}} \]
  11. Applied rewrites96.4%

    \[\leadsto \frac{1}{\sqrt[3]{x}} \cdot \color{blue}{\frac{0.3333333333333333}{\sqrt[3]{x}}} \]
  12. Add Preprocessing

Alternative 3: 96.4% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{\sqrt[3]{x}} \end{array} \]
(FPCore (x) :precision binary64 (/ (/ 0.3333333333333333 (cbrt x)) (cbrt x)))
double code(double x) {
	return (0.3333333333333333 / cbrt(x)) / cbrt(x);
}
public static double code(double x) {
	return (0.3333333333333333 / Math.cbrt(x)) / Math.cbrt(x);
}
function code(x)
	return Float64(Float64(0.3333333333333333 / cbrt(x)) / cbrt(x))
end
code[x_] := N[(N[(0.3333333333333333 / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{\sqrt[3]{x}}
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lift-/.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    3. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    5. associate-*l/N/A

      \[\leadsto \frac{1 \cdot \frac{1}{3}}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
    6. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{3}}{{\color{blue}{\left(\sqrt[3]{x}\right)}}^{2}} \]
    7. unpow2N/A

      \[\leadsto \frac{\frac{1}{3}}{\sqrt[3]{x} \cdot \color{blue}{\sqrt[3]{x}}} \]
    8. associate-/r*N/A

      \[\leadsto \frac{\frac{\frac{1}{3}}{\sqrt[3]{x}}}{\color{blue}{\sqrt[3]{x}}} \]
    9. lower-/.f64N/A

      \[\leadsto \frac{\frac{\frac{1}{3}}{\sqrt[3]{x}}}{\color{blue}{\sqrt[3]{x}}} \]
    10. lower-/.f64N/A

      \[\leadsto \frac{\frac{\frac{1}{3}}{\sqrt[3]{x}}}{\sqrt[3]{\color{blue}{x}}} \]
    11. lift-cbrt.f64N/A

      \[\leadsto \frac{\frac{\frac{1}{3}}{\sqrt[3]{x}}}{\sqrt[3]{x}} \]
    12. lift-cbrt.f6496.4

      \[\leadsto \frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{\sqrt[3]{x}} \]
  11. Applied rewrites96.4%

    \[\leadsto \frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{\color{blue}{\sqrt[3]{x}}} \]
  12. Add Preprocessing

Alternative 4: 96.4% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x)
 :precision binary64
 (* (/ 1.0 (pow (cbrt x) 2.0)) 0.3333333333333333))
double code(double x) {
	return (1.0 / pow(cbrt(x), 2.0)) * 0.3333333333333333;
}
public static double code(double x) {
	return (1.0 / Math.pow(Math.cbrt(x), 2.0)) * 0.3333333333333333;
}
function code(x)
	return Float64(Float64(1.0 / (cbrt(x) ^ 2.0)) * 0.3333333333333333)
end
code[x_] := N[(N[(1.0 / N[Power[N[Power[x, 1/3], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
\frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Add Preprocessing

Alternative 5: 96.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{0.3333333333333333}{{\left(\sqrt[3]{x}\right)}^{2}} \end{array} \]
(FPCore (x) :precision binary64 (/ 0.3333333333333333 (pow (cbrt x) 2.0)))
double code(double x) {
	return 0.3333333333333333 / pow(cbrt(x), 2.0);
}
public static double code(double x) {
	return 0.3333333333333333 / Math.pow(Math.cbrt(x), 2.0);
}
function code(x)
	return Float64(0.3333333333333333 / (cbrt(x) ^ 2.0))
end
code[x_] := N[(0.3333333333333333 / N[Power[N[Power[x, 1/3], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{0.3333333333333333}{{\left(\sqrt[3]{x}\right)}^{2}}
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lift-/.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    3. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    5. associate-*l/N/A

      \[\leadsto \frac{1 \cdot \frac{1}{3}}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
    6. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{3}}{{\color{blue}{\left(\sqrt[3]{x}\right)}}^{2}} \]
    7. lower-/.f64N/A

      \[\leadsto \frac{\frac{1}{3}}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
    8. lift-pow.f64N/A

      \[\leadsto \frac{\frac{1}{3}}{{\left(\sqrt[3]{x}\right)}^{\color{blue}{2}}} \]
    9. lift-cbrt.f6496.4

      \[\leadsto \frac{0.3333333333333333}{{\left(\sqrt[3]{x}\right)}^{2}} \]
  11. Applied rewrites96.4%

    \[\leadsto \frac{0.3333333333333333}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
  12. Add Preprocessing

Alternative 6: 96.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ {\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x) :precision binary64 (* (pow (cbrt x) -2.0) 0.3333333333333333))
double code(double x) {
	return pow(cbrt(x), -2.0) * 0.3333333333333333;
}
public static double code(double x) {
	return Math.pow(Math.cbrt(x), -2.0) * 0.3333333333333333;
}
function code(x)
	return Float64((cbrt(x) ^ -2.0) * 0.3333333333333333)
end
code[x_] := N[(N[Power[N[Power[x, 1/3], $MachinePrecision], -2.0], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
{\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Step-by-step derivation
    1. lift-/.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    2. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{\left(\mathsf{neg}\left(2\right)\right)} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{-2} \cdot \frac{1}{3} \]
    6. lower-pow.f64N/A

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{-2} \cdot \frac{1}{3} \]
    7. lift-cbrt.f6496.4

      \[\leadsto {\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333 \]
  11. Applied rewrites96.4%

    \[\leadsto \color{blue}{{\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333} \]
  12. Add Preprocessing

Alternative 7: 92.0% accurate, 1.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 1.35 \cdot 10^{+154}:\\ \;\;\;\;\frac{1}{\sqrt[3]{x \cdot x}} \cdot 0.3333333333333333\\ \mathbf{else}:\\ \;\;\;\;{x}^{-0.6666666666666666} \cdot 0.3333333333333333\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (if (<= x 1.35e+154)
   (* (/ 1.0 (cbrt (* x x))) 0.3333333333333333)
   (* (pow x -0.6666666666666666) 0.3333333333333333)))
double code(double x) {
	double tmp;
	if (x <= 1.35e+154) {
		tmp = (1.0 / cbrt((x * x))) * 0.3333333333333333;
	} else {
		tmp = pow(x, -0.6666666666666666) * 0.3333333333333333;
	}
	return tmp;
}
public static double code(double x) {
	double tmp;
	if (x <= 1.35e+154) {
		tmp = (1.0 / Math.cbrt((x * x))) * 0.3333333333333333;
	} else {
		tmp = Math.pow(x, -0.6666666666666666) * 0.3333333333333333;
	}
	return tmp;
}
function code(x)
	tmp = 0.0
	if (x <= 1.35e+154)
		tmp = Float64(Float64(1.0 / cbrt(Float64(x * x))) * 0.3333333333333333);
	else
		tmp = Float64((x ^ -0.6666666666666666) * 0.3333333333333333);
	end
	return tmp
end
code[x_] := If[LessEqual[x, 1.35e+154], N[(N[(1.0 / N[Power[N[(x * x), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision], N[(N[Power[x, -0.6666666666666666], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 1.35 \cdot 10^{+154}:\\
\;\;\;\;\frac{1}{\sqrt[3]{x \cdot x}} \cdot 0.3333333333333333\\

\mathbf{else}:\\
\;\;\;\;{x}^{-0.6666666666666666} \cdot 0.3333333333333333\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 1.35000000000000003e154

    1. Initial program 9.4%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      3. lower-cbrt.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      4. pow-flipN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      5. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      6. metadata-eval94.6

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
    5. Applied rewrites94.6%

      \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
    6. Step-by-step derivation
      1. lift-cbrt.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
      2. lift-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
      3. metadata-evalN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      4. pow-flipN/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      5. cbrt-divN/A

        \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
      6. metadata-evalN/A

        \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
      7. lower-/.f64N/A

        \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
      8. lower-cbrt.f64N/A

        \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
      9. unpow2N/A

        \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
      10. lower-*.f6494.8

        \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot 0.3333333333333333 \]
    7. Applied rewrites94.8%

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot 0.3333333333333333 \]

    if 1.35000000000000003e154 < x

    1. Initial program 4.7%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      3. lower-cbrt.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      4. pow-flipN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      5. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      6. metadata-eval7.2

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
    5. Applied rewrites7.2%

      \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
    6. Step-by-step derivation
      1. lift-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
      2. sqr-powN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
      3. metadata-evalN/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
      4. inv-powN/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
      5. metadata-evalN/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
      6. inv-powN/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      7. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      8. inv-powN/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      9. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      10. inv-powN/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
      11. lower-pow.f647.2

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
    7. Applied rewrites7.2%

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
    8. Step-by-step derivation
      1. lift-cbrt.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
      2. pow1/3N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      3. lift-*.f64N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      4. lift-pow.f64N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      5. lift-pow.f64N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      6. pow-prod-upN/A

        \[\leadsto {\left({x}^{\left(-1 + -1\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      7. metadata-evalN/A

        \[\leadsto {\left({x}^{-2}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      8. pow-powN/A

        \[\leadsto {x}^{\left(-2 \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
      9. lower-pow.f64N/A

        \[\leadsto {x}^{\left(-2 \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
      10. metadata-eval89.2

        \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
    9. Applied rewrites89.2%

      \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 8: 91.9% accurate, 1.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 1.35 \cdot 10^{+154}:\\ \;\;\;\;\sqrt[3]{\frac{1}{x \cdot x}} \cdot 0.3333333333333333\\ \mathbf{else}:\\ \;\;\;\;{x}^{-0.6666666666666666} \cdot 0.3333333333333333\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (if (<= x 1.35e+154)
   (* (cbrt (/ 1.0 (* x x))) 0.3333333333333333)
   (* (pow x -0.6666666666666666) 0.3333333333333333)))
double code(double x) {
	double tmp;
	if (x <= 1.35e+154) {
		tmp = cbrt((1.0 / (x * x))) * 0.3333333333333333;
	} else {
		tmp = pow(x, -0.6666666666666666) * 0.3333333333333333;
	}
	return tmp;
}
public static double code(double x) {
	double tmp;
	if (x <= 1.35e+154) {
		tmp = Math.cbrt((1.0 / (x * x))) * 0.3333333333333333;
	} else {
		tmp = Math.pow(x, -0.6666666666666666) * 0.3333333333333333;
	}
	return tmp;
}
function code(x)
	tmp = 0.0
	if (x <= 1.35e+154)
		tmp = Float64(cbrt(Float64(1.0 / Float64(x * x))) * 0.3333333333333333);
	else
		tmp = Float64((x ^ -0.6666666666666666) * 0.3333333333333333);
	end
	return tmp
end
code[x_] := If[LessEqual[x, 1.35e+154], N[(N[Power[N[(1.0 / N[(x * x), $MachinePrecision]), $MachinePrecision], 1/3], $MachinePrecision] * 0.3333333333333333), $MachinePrecision], N[(N[Power[x, -0.6666666666666666], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 1.35 \cdot 10^{+154}:\\
\;\;\;\;\sqrt[3]{\frac{1}{x \cdot x}} \cdot 0.3333333333333333\\

\mathbf{else}:\\
\;\;\;\;{x}^{-0.6666666666666666} \cdot 0.3333333333333333\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 1.35000000000000003e154

    1. Initial program 9.4%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      3. lower-cbrt.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      4. pow-flipN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      5. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      6. metadata-eval94.6

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
    5. Applied rewrites94.6%

      \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
    6. Step-by-step derivation
      1. lift-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
      2. metadata-evalN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      3. pow-flipN/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      4. lower-/.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      5. unpow2N/A

        \[\leadsto \sqrt[3]{\frac{1}{x \cdot x}} \cdot \frac{1}{3} \]
      6. lower-*.f6494.6

        \[\leadsto \sqrt[3]{\frac{1}{x \cdot x}} \cdot 0.3333333333333333 \]
    7. Applied rewrites94.6%

      \[\leadsto \sqrt[3]{\frac{1}{x \cdot x}} \cdot 0.3333333333333333 \]

    if 1.35000000000000003e154 < x

    1. Initial program 4.7%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      2. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
      3. lower-cbrt.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
      4. pow-flipN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      5. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
      6. metadata-eval7.2

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
    5. Applied rewrites7.2%

      \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
    6. Step-by-step derivation
      1. lift-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
      2. sqr-powN/A

        \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
      3. metadata-evalN/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
      4. inv-powN/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
      5. metadata-evalN/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
      6. inv-powN/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      7. lower-*.f64N/A

        \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      8. inv-powN/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      9. lower-pow.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
      10. inv-powN/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
      11. lower-pow.f647.2

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
    7. Applied rewrites7.2%

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
    8. Step-by-step derivation
      1. lift-cbrt.f64N/A

        \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
      2. pow1/3N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      3. lift-*.f64N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      4. lift-pow.f64N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      5. lift-pow.f64N/A

        \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      6. pow-prod-upN/A

        \[\leadsto {\left({x}^{\left(-1 + -1\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      7. metadata-evalN/A

        \[\leadsto {\left({x}^{-2}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
      8. pow-powN/A

        \[\leadsto {x}^{\left(-2 \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
      9. lower-pow.f64N/A

        \[\leadsto {x}^{\left(-2 \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
      10. metadata-eval89.2

        \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
    9. Applied rewrites89.2%

      \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 9: 88.7% accurate, 1.8× speedup?

\[\begin{array}{l} \\ \frac{1}{{x}^{0.6666666666666666}} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x)
 :precision binary64
 (* (/ 1.0 (pow x 0.6666666666666666)) 0.3333333333333333))
double code(double x) {
	return (1.0 / pow(x, 0.6666666666666666)) * 0.3333333333333333;
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = (1.0d0 / (x ** 0.6666666666666666d0)) * 0.3333333333333333d0
end function
public static double code(double x) {
	return (1.0 / Math.pow(x, 0.6666666666666666)) * 0.3333333333333333;
}
def code(x):
	return (1.0 / math.pow(x, 0.6666666666666666)) * 0.3333333333333333
function code(x)
	return Float64(Float64(1.0 / (x ^ 0.6666666666666666)) * 0.3333333333333333)
end
function tmp = code(x)
	tmp = (1.0 / (x ^ 0.6666666666666666)) * 0.3333333333333333;
end
code[x_] := N[(N[(1.0 / N[Power[x, 0.6666666666666666], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
\frac{1}{{x}^{0.6666666666666666}} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. lift-*.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    3. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    5. pow-sqrN/A

      \[\leadsto \sqrt[3]{{x}^{\left(2 \cdot -1\right)}} \cdot \frac{1}{3} \]
    6. pow-powN/A

      \[\leadsto \sqrt[3]{{\left({x}^{2}\right)}^{-1}} \cdot \frac{1}{3} \]
    7. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    8. cbrt-divN/A

      \[\leadsto \frac{\sqrt[3]{1}}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    9. metadata-evalN/A

      \[\leadsto \frac{1}{\sqrt[3]{{x}^{2}}} \cdot \frac{1}{3} \]
    10. unpow2N/A

      \[\leadsto \frac{1}{\sqrt[3]{x \cdot x}} \cdot \frac{1}{3} \]
    11. cbrt-prodN/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    12. lower-/.f64N/A

      \[\leadsto \frac{1}{\sqrt[3]{x} \cdot \sqrt[3]{x}} \cdot \frac{1}{3} \]
    13. pow2N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    14. lower-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    15. lift-cbrt.f6496.4

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  9. Applied rewrites96.4%

    \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot 0.3333333333333333 \]
  10. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    2. lift-pow.f64N/A

      \[\leadsto \frac{1}{{\left(\sqrt[3]{x}\right)}^{2}} \cdot \frac{1}{3} \]
    3. pow1/3N/A

      \[\leadsto \frac{1}{{\left({x}^{\frac{1}{3}}\right)}^{2}} \cdot \frac{1}{3} \]
    4. pow-powN/A

      \[\leadsto \frac{1}{{x}^{\left(\frac{1}{3} \cdot 2\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \frac{1}{{x}^{\frac{2}{3}}} \cdot \frac{1}{3} \]
    6. lower-pow.f6488.7

      \[\leadsto \frac{1}{{x}^{0.6666666666666666}} \cdot 0.3333333333333333 \]
  11. Applied rewrites88.7%

    \[\leadsto \frac{1}{{x}^{0.6666666666666666}} \cdot 0.3333333333333333 \]
  12. Add Preprocessing

Alternative 10: 88.7% accurate, 1.9× speedup?

\[\begin{array}{l} \\ {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \end{array} \]
(FPCore (x)
 :precision binary64
 (* (pow x -0.6666666666666666) 0.3333333333333333))
double code(double x) {
	return pow(x, -0.6666666666666666) * 0.3333333333333333;
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x)
use fmin_fmax_functions
    real(8), intent (in) :: x
    code = (x ** (-0.6666666666666666d0)) * 0.3333333333333333d0
end function
public static double code(double x) {
	return Math.pow(x, -0.6666666666666666) * 0.3333333333333333;
}
def code(x):
	return math.pow(x, -0.6666666666666666) * 0.3333333333333333
function code(x)
	return Float64((x ^ -0.6666666666666666) * 0.3333333333333333)
end
function tmp = code(x)
	tmp = (x ^ -0.6666666666666666) * 0.3333333333333333;
end
code[x_] := N[(N[Power[x, -0.6666666666666666], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]
\begin{array}{l}

\\
{x}^{-0.6666666666666666} \cdot 0.3333333333333333
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \sqrt[3]{\frac{1}{{x}^{2}}}} \]
  4. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    2. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \color{blue}{\frac{1}{3}} \]
    3. lower-cbrt.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3} \]
    4. pow-flipN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    5. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{\left(\mathsf{neg}\left(2\right)\right)}} \cdot \frac{1}{3} \]
    6. metadata-eval50.8

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333 \]
  5. Applied rewrites50.8%

    \[\leadsto \color{blue}{\sqrt[3]{{x}^{-2}} \cdot 0.3333333333333333} \]
  6. Step-by-step derivation
    1. lift-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-2}} \cdot \frac{1}{3} \]
    2. sqr-powN/A

      \[\leadsto \sqrt[3]{{x}^{\left(\frac{-2}{2}\right)} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    3. metadata-evalN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    4. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{\left(\frac{-2}{2}\right)}} \cdot \frac{1}{3} \]
    5. metadata-evalN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    6. inv-powN/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    7. lower-*.f64N/A

      \[\leadsto \sqrt[3]{\frac{1}{x} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    8. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot \frac{1}{x}} \cdot \frac{1}{3} \]
    10. inv-powN/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    11. lower-pow.f6450.8

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  7. Applied rewrites50.8%

    \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot 0.3333333333333333 \]
  8. Step-by-step derivation
    1. lift-cbrt.f64N/A

      \[\leadsto \sqrt[3]{{x}^{-1} \cdot {x}^{-1}} \cdot \frac{1}{3} \]
    2. pow1/3N/A

      \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    3. lift-*.f64N/A

      \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    4. lift-pow.f64N/A

      \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    5. lift-pow.f64N/A

      \[\leadsto {\left({x}^{-1} \cdot {x}^{-1}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    6. pow-prod-upN/A

      \[\leadsto {\left({x}^{\left(-1 + -1\right)}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    7. metadata-evalN/A

      \[\leadsto {\left({x}^{-2}\right)}^{\frac{1}{3}} \cdot \frac{1}{3} \]
    8. pow-powN/A

      \[\leadsto {x}^{\left(-2 \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
    9. lower-pow.f64N/A

      \[\leadsto {x}^{\left(-2 \cdot \frac{1}{3}\right)} \cdot \frac{1}{3} \]
    10. metadata-eval88.7

      \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
  9. Applied rewrites88.7%

    \[\leadsto {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \]
  10. Add Preprocessing

Alternative 11: 1.8% accurate, 2.0× speedup?

\[\begin{array}{l} \\ 1 - \sqrt[3]{x} \end{array} \]
(FPCore (x) :precision binary64 (- 1.0 (cbrt x)))
double code(double x) {
	return 1.0 - cbrt(x);
}
public static double code(double x) {
	return 1.0 - Math.cbrt(x);
}
function code(x)
	return Float64(1.0 - cbrt(x))
end
code[x_] := N[(1.0 - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \sqrt[3]{x}
\end{array}
Derivation
  1. Initial program 7.1%

    \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
  2. Add Preprocessing
  3. Taylor expanded in x around 0

    \[\leadsto \color{blue}{1} - \sqrt[3]{x} \]
  4. Step-by-step derivation
    1. Applied rewrites1.8%

      \[\leadsto \color{blue}{1} - \sqrt[3]{x} \]
    2. Add Preprocessing

    Developer Target 1: 98.5% accurate, 0.3× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt[3]{x + 1}\\ \frac{1}{\left(t\_0 \cdot t\_0 + \sqrt[3]{x} \cdot t\_0\right) + \sqrt[3]{x} \cdot \sqrt[3]{x}} \end{array} \end{array} \]
    (FPCore (x)
     :precision binary64
     (let* ((t_0 (cbrt (+ x 1.0))))
       (/ 1.0 (+ (+ (* t_0 t_0) (* (cbrt x) t_0)) (* (cbrt x) (cbrt x))))))
    double code(double x) {
    	double t_0 = cbrt((x + 1.0));
    	return 1.0 / (((t_0 * t_0) + (cbrt(x) * t_0)) + (cbrt(x) * cbrt(x)));
    }
    
    public static double code(double x) {
    	double t_0 = Math.cbrt((x + 1.0));
    	return 1.0 / (((t_0 * t_0) + (Math.cbrt(x) * t_0)) + (Math.cbrt(x) * Math.cbrt(x)));
    }
    
    function code(x)
    	t_0 = cbrt(Float64(x + 1.0))
    	return Float64(1.0 / Float64(Float64(Float64(t_0 * t_0) + Float64(cbrt(x) * t_0)) + Float64(cbrt(x) * cbrt(x))))
    end
    
    code[x_] := Block[{t$95$0 = N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision]}, N[(1.0 / N[(N[(N[(t$95$0 * t$95$0), $MachinePrecision] + N[(N[Power[x, 1/3], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(N[Power[x, 1/3], $MachinePrecision] * N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \sqrt[3]{x + 1}\\
    \frac{1}{\left(t\_0 \cdot t\_0 + \sqrt[3]{x} \cdot t\_0\right) + \sqrt[3]{x} \cdot \sqrt[3]{x}}
    \end{array}
    \end{array}
    

    Reproduce

    ?
    herbie shell --seed 2025088 
    (FPCore (x)
      :name "2cbrt (problem 3.3.4)"
      :precision binary64
      :pre (and (> x 1.0) (< x 1e+308))
    
      :alt
      (! :herbie-platform default (/ 1 (+ (* (cbrt (+ x 1)) (cbrt (+ x 1))) (* (cbrt x) (cbrt (+ x 1))) (* (cbrt x) (cbrt x)))))
    
      (- (cbrt (+ x 1.0)) (cbrt x)))