2cbrt (problem 3.3.4)

Percentage Accurate: 7.1% → 98.6%

Time: 8.4s

Alternatives: 12

Speedup: 1.9×

Specification

\[x > 1 \land x < 10^{+308}\]

Math

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

FPCore

(FPCore (x) :precision binary64 (- (cbrt (+ x 1.0)) (cbrt x)))

C

double code(double x) {
	return cbrt((x + 1.0)) - cbrt(x);
}

Java

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

Julia

function code(x)
	return Float64(cbrt(Float64(x + 1.0)) - cbrt(x))
end

Wolfram

code[x_] := N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]

Initial Program: 7.1% accurate, 1.0× speedup

Math

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

FPCore

(FPCore (x) :precision binary64 (- (cbrt (+ x 1.0)) (cbrt x)))

C

double code(double x) {
	return cbrt((x + 1.0)) - cbrt(x);
}

Java

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

Julia

function code(x)
	return Float64(cbrt(Float64(x + 1.0)) - cbrt(x))
end

Wolfram

code[x_] := N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision]

Alternative 1: 98.6% accurate, 0.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\sqrt[3]{x + 1} - \sqrt[3]{x} \leq 5 \cdot 10^{-11}:\\ \;\;\;\;\frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{{\left(\sqrt[3]{x}\right)}^{0.25}}\\ \mathbf{else}:\\ \;\;\;\;\frac{\left(1 + x\right) - x}{\mathsf{fma}\left(\sqrt[3]{1 + x} + \sqrt[3]{x}, \sqrt[3]{x}, e^{\mathsf{log1p}\left(x\right) \cdot 0.6666666666666666}\right)}\\ \end{array} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (if (<= (- (cbrt (+ x 1.0)) (cbrt x)) 5e-11)
   (/ (/ (/ 0.3333333333333333 (cbrt x)) (pow x 0.25)) (pow (cbrt x) 0.25))
   (/
    (- (+ 1.0 x) x)
    (fma
     (+ (cbrt (+ 1.0 x)) (cbrt x))
     (cbrt x)
     (exp (* (log1p x) 0.6666666666666666))))))

C

double code(double x) {
	double tmp;
	if ((cbrt((x + 1.0)) - cbrt(x)) <= 5e-11) {
		tmp = ((0.3333333333333333 / cbrt(x)) / pow(x, 0.25)) / pow(cbrt(x), 0.25);
	} else {
		tmp = ((1.0 + x) - x) / fma((cbrt((1.0 + x)) + cbrt(x)), cbrt(x), exp((log1p(x) * 0.6666666666666666)));
	}
	return tmp;
}

Julia

function code(x)
	tmp = 0.0
	if (Float64(cbrt(Float64(x + 1.0)) - cbrt(x)) <= 5e-11)
		tmp = Float64(Float64(Float64(0.3333333333333333 / cbrt(x)) / (x ^ 0.25)) / (cbrt(x) ^ 0.25));
	else
		tmp = Float64(Float64(Float64(1.0 + x) - x) / fma(Float64(cbrt(Float64(1.0 + x)) + cbrt(x)), cbrt(x), exp(Float64(log1p(x) * 0.6666666666666666))));
	end
	return tmp
end

Wolfram

code[x_] := If[LessEqual[N[(N[Power[N[(x + 1.0), $MachinePrecision], 1/3], $MachinePrecision] - N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision], 5e-11], N[(N[(N[(0.3333333333333333 / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] / N[Power[x, 0.25], $MachinePrecision]), $MachinePrecision] / N[Power[N[Power[x, 1/3], $MachinePrecision], 0.25], $MachinePrecision]), $MachinePrecision], N[(N[(N[(1.0 + x), $MachinePrecision] - x), $MachinePrecision] / N[(N[(N[Power[N[(1.0 + x), $MachinePrecision], 1/3], $MachinePrecision] + N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] * N[Power[x, 1/3], $MachinePrecision] + N[Exp[N[(N[Log[1 + x], $MachinePrecision] * 0.6666666666666666), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (-.f64 (cbrt.f64 (+.f64 x #s(literal 1 binary64))) (cbrt.f64 x)) < 5.00000000000000018e-11

   1. Initial program 4.3%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
   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. *-commutative N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

      2. lower-*.f64 N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

      3. unpow2 N/A

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

      4. sqr-neg-rev N/A

         \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

      5. associate-/r* N/A

         \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

      6. distribute-neg-frac2 N/A

         \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      7. distribute-neg-frac N/A

         \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      8. metadata-eval N/A

         \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      9. lower-cbrt.f64 N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

      10. metadata-eval N/A

          \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      11. distribute-neg-frac N/A

          \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      12. distribute-neg-frac2 N/A

          \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      13. associate-/r* N/A

          \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

      14. sqr-neg-rev N/A

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

      15. associate-/r* N/A

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

      16. lower-/.f64 N/A

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

      17. lower-/.f64 52.6

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

   5. Applied rewrites 52.6%

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
   6. Step-by-step derivation

   7. Applied rewrites 94.9%

      \[\leadsto \frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{\color{blue}{{x}^{0.08333333333333333}}} \]
   8. Step-by-step derivation

   9. Applied rewrites 98.6%

      \[\leadsto \frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{{\left(\sqrt[3]{x}\right)}^{\color{blue}{0.25}}} \]

   if 5.00000000000000018e-11 < (-.f64 (cbrt.f64 (+.f64 x #s(literal 1 binary64))) (cbrt.f64 x))

   1. Initial program 57.5%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
   2. Add Preprocessing
   3. Step-by-step derivation

      1. lift-cbrt.f64 N/A

         \[\leadsto \sqrt[3]{x + 1} - \color{blue}{\sqrt[3]{x}} \]

      2. pow1/3 N/A

         \[\leadsto \sqrt[3]{x + 1} - \color{blue}{{x}^{\frac{1}{3}}} \]

      3. sqr-pow N/A

         \[\leadsto \sqrt[3]{x + 1} - \color{blue}{{x}^{\left(\frac{\frac{1}{3}}{2}\right)} \cdot {x}^{\left(\frac{\frac{1}{3}}{2}\right)}} \]

      4. pow2 N/A

         \[\leadsto \sqrt[3]{x + 1} - \color{blue}{{\left({x}^{\left(\frac{\frac{1}{3}}{2}\right)}\right)}^{2}} \]

      5. lower-pow.f64 N/A

         \[\leadsto \sqrt[3]{x + 1} - \color{blue}{{\left({x}^{\left(\frac{\frac{1}{3}}{2}\right)}\right)}^{2}} \]

      6. lower-pow.f64 N/A

         \[\leadsto \sqrt[3]{x + 1} - {\color{blue}{\left({x}^{\left(\frac{\frac{1}{3}}{2}\right)}\right)}}^{2} \]

      7. metadata-eval 54.7

         \[\leadsto \sqrt[3]{x + 1} - {\left({x}^{\color{blue}{0.16666666666666666}}\right)}^{2} \]

   4. Applied rewrites 54.7%

      \[\leadsto \sqrt[3]{x + 1} - \color{blue}{{\left({x}^{0.16666666666666666}\right)}^{2}} \]

   6. Applied rewrites 97.6%

      \[\leadsto \color{blue}{\frac{\left(1 + x\right) - x}{\mathsf{fma}\left(\sqrt[3]{1 + x} + \sqrt[3]{x}, \sqrt[3]{x}, e^{\mathsf{log1p}\left(x\right) \cdot 0.6666666666666666}\right)}} \]
3. Recombined 2 regimes into one program.
4. Add Preprocessing

Alternative 2: 96.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{{\left(\sqrt[3]{x}\right)}^{0.25}} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (/ (/ (/ 0.3333333333333333 (cbrt x)) (pow x 0.25)) (pow (cbrt x) 0.25)))

C

double code(double x) {
	return ((0.3333333333333333 / cbrt(x)) / pow(x, 0.25)) / pow(cbrt(x), 0.25);
}

Java

public static double code(double x) {
	return ((0.3333333333333333 / Math.cbrt(x)) / Math.pow(x, 0.25)) / Math.pow(Math.cbrt(x), 0.25);
}

Julia

function code(x)
	return Float64(Float64(Float64(0.3333333333333333 / cbrt(x)) / (x ^ 0.25)) / (cbrt(x) ^ 0.25))
end

Wolfram

code[x_] := N[(N[(N[(0.3333333333333333 / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] / N[Power[x, 0.25], $MachinePrecision]), $MachinePrecision] / N[Power[N[Power[x, 1/3], $MachinePrecision], 0.25], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 93.2%

   \[\leadsto \frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{\color{blue}{{x}^{0.08333333333333333}}} \]
8. Step-by-step derivation

9. Applied rewrites 96.8%

   \[\leadsto \frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{{\left(\sqrt[3]{x}\right)}^{\color{blue}{0.25}}} \]
10. Add Preprocessing

Alternative 3: 96.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \frac{\frac{0.3333333333333333}{\sqrt[3]{x} \cdot {x}^{0.25}}}{{\left(\sqrt[3]{x}\right)}^{0.25}} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (/ (/ 0.3333333333333333 (* (cbrt x) (pow x 0.25))) (pow (cbrt x) 0.25)))

C

double code(double x) {
	return (0.3333333333333333 / (cbrt(x) * pow(x, 0.25))) / pow(cbrt(x), 0.25);
}

Java

public static double code(double x) {
	return (0.3333333333333333 / (Math.cbrt(x) * Math.pow(x, 0.25))) / Math.pow(Math.cbrt(x), 0.25);
}

Julia

function code(x)
	return Float64(Float64(0.3333333333333333 / Float64(cbrt(x) * (x ^ 0.25))) / (cbrt(x) ^ 0.25))
end

Wolfram

code[x_] := N[(N[(0.3333333333333333 / N[(N[Power[x, 1/3], $MachinePrecision] * N[Power[x, 0.25], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Power[N[Power[x, 1/3], $MachinePrecision], 0.25], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 93.2%

   \[\leadsto \frac{\frac{\frac{0.3333333333333333}{\sqrt[3]{x}}}{{x}^{0.25}}}{\color{blue}{{x}^{0.08333333333333333}}} \]
8. Step-by-step derivation

9. Applied rewrites 93.2%

   \[\leadsto \frac{\frac{0.3333333333333333}{\left(-\sqrt[3]{x}\right) \cdot \left(-{x}^{0.25}\right)}}{{\color{blue}{x}}^{0.08333333333333333}} \]
10. Step-by-step derivation

11. Applied rewrites 96.7%

    \[\leadsto \frac{\frac{0.3333333333333333}{\left(-\sqrt[3]{x}\right) \cdot \left(-{x}^{0.25}\right)}}{{\left(\sqrt[3]{x}\right)}^{\color{blue}{0.25}}} \]

12. Final simplification 96.7%

    \[\leadsto \frac{\frac{0.3333333333333333}{\sqrt[3]{x} \cdot {x}^{0.25}}}{{\left(\sqrt[3]{x}\right)}^{0.25}} \]
13. Add Preprocessing

Alternative 4: 96.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \left(\frac{-1}{\sqrt[3]{x}} \cdot \left(-\sqrt[3]{{x}^{-1}}\right)\right) \cdot 0.3333333333333333 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (* (* (/ -1.0 (cbrt x)) (- (cbrt (pow x -1.0)))) 0.3333333333333333))

C

double code(double x) {
	return ((-1.0 / cbrt(x)) * -cbrt(pow(x, -1.0))) * 0.3333333333333333;
}

Java

public static double code(double x) {
	return ((-1.0 / Math.cbrt(x)) * -Math.cbrt(Math.pow(x, -1.0))) * 0.3333333333333333;
}

Julia

function code(x)
	return Float64(Float64(Float64(-1.0 / cbrt(x)) * Float64(-cbrt((x ^ -1.0)))) * 0.3333333333333333)
end

Wolfram

code[x_] := N[(N[(N[(-1.0 / N[Power[x, 1/3], $MachinePrecision]), $MachinePrecision] * (-N[Power[N[Power[x, -1.0], $MachinePrecision], 1/3], $MachinePrecision])), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 96.4%

   \[\leadsto \left(\frac{-1}{\sqrt[3]{x}} \cdot \frac{-1}{\sqrt[3]{x}}\right) \cdot 0.3333333333333333 \]

8. Taylor expanded in x around 0

   \[\leadsto \left(\frac{-1}{\sqrt[3]{x}} \cdot \left(-1 \cdot \sqrt[3]{\frac{1}{x}}\right)\right) \cdot \frac{1}{3} \]
9. Step-by-step derivation

10. Applied rewrites 96.5%

    \[\leadsto \left(\frac{-1}{\sqrt[3]{x}} \cdot \left(-\sqrt[3]{\frac{1}{x}}\right)\right) \cdot 0.3333333333333333 \]

11. Final simplification 96.5%

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

Alternative 5: 96.4% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \frac{\sqrt[3]{\frac{-1}{x}} \cdot 0.3333333333333333}{\sqrt[3]{-x}} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (/ (* (cbrt (/ -1.0 x)) 0.3333333333333333) (cbrt (- x))))

C

double code(double x) {
	return (cbrt((-1.0 / x)) * 0.3333333333333333) / cbrt(-x);
}

Java

public static double code(double x) {
	return (Math.cbrt((-1.0 / x)) * 0.3333333333333333) / Math.cbrt(-x);
}

Julia

function code(x)
	return Float64(Float64(cbrt(Float64(-1.0 / x)) * 0.3333333333333333) / cbrt(Float64(-x)))
end

Wolfram

code[x_] := N[(N[(N[Power[N[(-1.0 / x), $MachinePrecision], 1/3], $MachinePrecision] * 0.3333333333333333), $MachinePrecision] / N[Power[(-x), 1/3], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 96.5%

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

Alternative 6: 96.4% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \frac{\sqrt[3]{\frac{-1}{x}}}{\sqrt[3]{-x}} \cdot 0.3333333333333333 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (* (/ (cbrt (/ -1.0 x)) (cbrt (- x))) 0.3333333333333333))

C

double code(double x) {
	return (cbrt((-1.0 / x)) / cbrt(-x)) * 0.3333333333333333;
}

Java

public static double code(double x) {
	return (Math.cbrt((-1.0 / x)) / Math.cbrt(-x)) * 0.3333333333333333;
}

Julia

function code(x)
	return Float64(Float64(cbrt(Float64(-1.0 / x)) / cbrt(Float64(-x))) * 0.3333333333333333)
end

Wolfram

code[x_] := N[(N[(N[Power[N[(-1.0 / x), $MachinePrecision], 1/3], $MachinePrecision] / N[Power[(-x), 1/3], $MachinePrecision]), $MachinePrecision] * 0.3333333333333333), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 96.5%

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

Alternative 7: 96.3% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{0.3333333333333333}{{\left(\sqrt[3]{x}\right)}^{2}} \end{array} \]

FPCore

(FPCore (x) :precision binary64 (/ 0.3333333333333333 (pow (cbrt x) 2.0)))

C

double code(double x) {
	return 0.3333333333333333 / pow(cbrt(x), 2.0);
}

Java

public static double code(double x) {
	return 0.3333333333333333 / Math.pow(Math.cbrt(x), 2.0);
}

Julia

function code(x)
	return Float64(0.3333333333333333 / (cbrt(x) ^ 2.0))
end

Wolfram

code[x_] := N[(0.3333333333333333 / N[Power[N[Power[x, 1/3], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 96.5%

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

Alternative 8: 96.4% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ {\left(\sqrt[3]{x}\right)}^{-2} \cdot 0.3333333333333333 \end{array} \]

FPCore

(FPCore (x) :precision binary64 (* (pow (cbrt x) -2.0) 0.3333333333333333))

C

double code(double x) {
	return pow(cbrt(x), -2.0) * 0.3333333333333333;
}

Java

public static double code(double x) {
	return Math.pow(Math.cbrt(x), -2.0) * 0.3333333333333333;
}

Julia

function code(x)
	return Float64((cbrt(x) ^ -2.0) * 0.3333333333333333)
end

Wolfram

code[x_] := N[(N[Power[N[Power[x, 1/3], $MachinePrecision], -2.0], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 96.5%

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

Alternative 9: 92.0% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 1.35 \cdot 10^{+154}:\\ \;\;\;\;\frac{0.3333333333333333}{\sqrt[3]{x \cdot x}}\\ \mathbf{else}:\\ \;\;\;\;\frac{0.3333333333333333}{{x}^{0.6666666666666666}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (if (<= x 1.35e+154)
   (/ 0.3333333333333333 (cbrt (* x x)))
   (/ 0.3333333333333333 (pow x 0.6666666666666666))))

C

double code(double x) {
	double tmp;
	if (x <= 1.35e+154) {
		tmp = 0.3333333333333333 / cbrt((x * x));
	} else {
		tmp = 0.3333333333333333 / pow(x, 0.6666666666666666);
	}
	return tmp;
}

Java

public static double code(double x) {
	double tmp;
	if (x <= 1.35e+154) {
		tmp = 0.3333333333333333 / Math.cbrt((x * x));
	} else {
		tmp = 0.3333333333333333 / Math.pow(x, 0.6666666666666666);
	}
	return tmp;
}

Julia

function code(x)
	tmp = 0.0
	if (x <= 1.35e+154)
		tmp = Float64(0.3333333333333333 / cbrt(Float64(x * x)));
	else
		tmp = Float64(0.3333333333333333 / (x ^ 0.6666666666666666));
	end
	return tmp
end

Wolfram

code[x_] := If[LessEqual[x, 1.35e+154], N[(0.3333333333333333 / N[Power[N[(x * x), $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision], N[(0.3333333333333333 / N[Power[x, 0.6666666666666666], $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < 1.35000000000000003e154

   1. Initial program 9.1%

      \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
   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. *-commutative N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

      2. lower-*.f64 N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

      3. unpow2 N/A

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

      4. sqr-neg-rev N/A

         \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

      5. associate-/r* N/A

         \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

      6. distribute-neg-frac2 N/A

         \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      7. distribute-neg-frac N/A

         \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      8. metadata-eval N/A

         \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      9. lower-cbrt.f64 N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

      10. metadata-eval N/A

          \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      11. distribute-neg-frac N/A

          \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      12. distribute-neg-frac2 N/A

          \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      13. associate-/r* N/A

          \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

      14. sqr-neg-rev N/A

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

      15. associate-/r* N/A

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

      16. lower-/.f64 N/A

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

      17. lower-/.f64 95.1

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

   5. Applied rewrites 95.1%

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
   6. Step-by-step derivation

   7. Applied rewrites 94.7%

      \[\leadsto \frac{0.3333333333333333}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
   8. Step-by-step derivation

   9. Applied rewrites 95.3%

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

   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. *-commutative N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

      2. lower-*.f64 N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

      3. unpow2 N/A

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

      4. sqr-neg-rev N/A

         \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

      5. associate-/r* N/A

         \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

      6. distribute-neg-frac2 N/A

         \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      7. distribute-neg-frac N/A

         \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      8. metadata-eval N/A

         \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      9. lower-cbrt.f64 N/A

         \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

      10. metadata-eval N/A

          \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      11. distribute-neg-frac N/A

          \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      12. distribute-neg-frac2 N/A

          \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

      13. associate-/r* N/A

          \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

      14. sqr-neg-rev N/A

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

      15. associate-/r* N/A

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

      16. lower-/.f64 N/A

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

      17. lower-/.f64 9.7

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

   5. Applied rewrites 9.7%

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
   6. Step-by-step derivation

   7. Applied rewrites 98.3%

      \[\leadsto \frac{0.3333333333333333}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
   8. Step-by-step derivation

   9. Applied rewrites 89.2%

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

Alternative 10: 88.7% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \frac{0.3333333333333333}{{x}^{0.6666666666666666}} \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (/ 0.3333333333333333 (pow x 0.6666666666666666)))

C

double code(double x) {
	return 0.3333333333333333 / pow(x, 0.6666666666666666);
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = 0.3333333333333333d0 / (x ** 0.6666666666666666d0)
end function

Java

public static double code(double x) {
	return 0.3333333333333333 / Math.pow(x, 0.6666666666666666);
}

Python

def code(x):
	return 0.3333333333333333 / math.pow(x, 0.6666666666666666)

Julia

function code(x)
	return Float64(0.3333333333333333 / (x ^ 0.6666666666666666))
end

MATLAB

function tmp = code(x)
	tmp = 0.3333333333333333 / (x ^ 0.6666666666666666);
end

Wolfram

code[x_] := N[(0.3333333333333333 / N[Power[x, 0.6666666666666666], $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 96.5%

   \[\leadsto \frac{0.3333333333333333}{\color{blue}{{\left(\sqrt[3]{x}\right)}^{2}}} \]
8. Step-by-step derivation

9. Applied rewrites 88.9%

   \[\leadsto \frac{0.3333333333333333}{{x}^{\color{blue}{0.6666666666666666}}} \]
10. Add Preprocessing

Alternative 11: 88.7% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ {x}^{-0.6666666666666666} \cdot 0.3333333333333333 \end{array} \]

FPCore

(FPCore (x)
 :precision binary64
 (* (pow x -0.6666666666666666) 0.3333333333333333))

C

double code(double x) {
	return pow(x, -0.6666666666666666) * 0.3333333333333333;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = (x ** (-0.6666666666666666d0)) * 0.3333333333333333d0
end function

Java

public static double code(double x) {
	return Math.pow(x, -0.6666666666666666) * 0.3333333333333333;
}

Python

def code(x):
	return math.pow(x, -0.6666666666666666) * 0.3333333333333333

Julia

function code(x)
	return Float64((x ^ -0.6666666666666666) * 0.3333333333333333)
end

MATLAB

function tmp = code(x)
	tmp = (x ^ -0.6666666666666666) * 0.3333333333333333;
end

Wolfram

code[x_] := N[(N[Power[x, -0.6666666666666666], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
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. *-commutative N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   2. lower-*.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{1}{{x}^{2}}} \cdot \frac{1}{3}} \]

   3. unpow2 N/A

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

   4. sqr-neg-rev N/A

      \[\leadsto \sqrt[3]{\frac{1}{\color{blue}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   5. associate-/r* N/A

      \[\leadsto \sqrt[3]{\color{blue}{\frac{\frac{1}{\mathsf{neg}\left(x\right)}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   6. distribute-neg-frac2 N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   7. distribute-neg-frac N/A

      \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{\mathsf{neg}\left(1\right)}{x}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   8. metadata-eval N/A

      \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{-1}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   9. lower-cbrt.f64 N/A

      \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{-1}{x}}{\mathsf{neg}\left(x\right)}}} \cdot \frac{1}{3} \]

   10. metadata-eval N/A

       \[\leadsto \sqrt[3]{\frac{\frac{\color{blue}{\mathsf{neg}\left(1\right)}}{x}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   11. distribute-neg-frac N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\mathsf{neg}\left(\frac{1}{x}\right)}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   12. distribute-neg-frac2 N/A

       \[\leadsto \sqrt[3]{\frac{\color{blue}{\frac{1}{\mathsf{neg}\left(x\right)}}}{\mathsf{neg}\left(x\right)}} \cdot \frac{1}{3} \]

   13. associate-/r* N/A

       \[\leadsto \sqrt[3]{\color{blue}{\frac{1}{\left(\mathsf{neg}\left(x\right)\right) \cdot \left(\mathsf{neg}\left(x\right)\right)}}} \cdot \frac{1}{3} \]

   14. sqr-neg-rev N/A

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

   15. associate-/r* N/A

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

   16. lower-/.f64 N/A

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

   17. lower-/.f64 53.0

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

5. Applied rewrites 53.0%

   \[\leadsto \color{blue}{\sqrt[3]{\frac{\frac{1}{x}}{x}} \cdot 0.3333333333333333} \]
6. Step-by-step derivation

7. Applied rewrites 88.9%

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

Alternative 12: 4.1% accurate, 207.0× speedup

Math

\[\begin{array}{l} \\ 0 \end{array} \]

FPCore

(FPCore (x) :precision binary64 0.0)

C

double code(double x) {
	return 0.0;
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = 0.0d0
end function

Java

public static double code(double x) {
	return 0.0;
}

Python

def code(x):
	return 0.0

Julia

function code(x)
	return 0.0
end

MATLAB

function tmp = code(x)
	tmp = 0.0;
end

Wolfram

code[x_] := 0.0

Derivation

1. Initial program 7.0%

   \[\sqrt[3]{x + 1} - \sqrt[3]{x} \]
2. Add Preprocessing
3. Step-by-step derivation

   1. rem-exp-log N/A

      \[\leadsto \sqrt[3]{\color{blue}{e^{\log \left(x + 1\right)}}} - \sqrt[3]{x} \]

   2. unpow1 N/A

      \[\leadsto \sqrt[3]{e^{\log \color{blue}{\left({\left(x + 1\right)}^{1}\right)}}} - \sqrt[3]{x} \]

   3. log-pow N/A

      \[\leadsto \sqrt[3]{e^{\color{blue}{1 \cdot \log \left(x + 1\right)}}} - \sqrt[3]{x} \]

   4. rem-cube-cbrt N/A

      \[\leadsto \sqrt[3]{e^{1 \cdot \log \color{blue}{\left({\left(\sqrt[3]{x + 1}\right)}^{3}\right)}}} - \sqrt[3]{x} \]

   5. lift-cbrt.f64 N/A

      \[\leadsto \sqrt[3]{e^{1 \cdot \log \left({\color{blue}{\left(\sqrt[3]{x + 1}\right)}}^{3}\right)}} - \sqrt[3]{x} \]

   6. pow-to-exp N/A

      \[\leadsto \sqrt[3]{e^{1 \cdot \log \color{blue}{\left(e^{\log \left(\sqrt[3]{x + 1}\right) \cdot 3}\right)}}} - \sqrt[3]{x} \]

   7. rem-log-exp N/A

      \[\leadsto \sqrt[3]{e^{1 \cdot \color{blue}{\left(\log \left(\sqrt[3]{x + 1}\right) \cdot 3\right)}}} - \sqrt[3]{x} \]

   8. exp-prod N/A

      \[\leadsto \sqrt[3]{\color{blue}{{\left(e^{1}\right)}^{\left(\log \left(\sqrt[3]{x + 1}\right) \cdot 3\right)}}} - \sqrt[3]{x} \]

   9. lower-pow.f64 N/A

      \[\leadsto \sqrt[3]{\color{blue}{{\left(e^{1}\right)}^{\left(\log \left(\sqrt[3]{x + 1}\right) \cdot 3\right)}}} - \sqrt[3]{x} \]

   10. lower-exp.f64 N/A

       \[\leadsto \sqrt[3]{{\color{blue}{\left(e^{1}\right)}}^{\left(\log \left(\sqrt[3]{x + 1}\right) \cdot 3\right)}} - \sqrt[3]{x} \]

   11. rem-log-exp N/A

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\color{blue}{\log \left(e^{\log \left(\sqrt[3]{x + 1}\right) \cdot 3}\right)}}} - \sqrt[3]{x} \]

   12. pow-to-exp N/A

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\log \color{blue}{\left({\left(\sqrt[3]{x + 1}\right)}^{3}\right)}}} - \sqrt[3]{x} \]

   13. lift-cbrt.f64 N/A

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\log \left({\color{blue}{\left(\sqrt[3]{x + 1}\right)}}^{3}\right)}} - \sqrt[3]{x} \]

   14. rem-cube-cbrt N/A

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\log \color{blue}{\left(x + 1\right)}}} - \sqrt[3]{x} \]

   15. lift-+.f64 N/A

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\log \color{blue}{\left(x + 1\right)}}} - \sqrt[3]{x} \]

   16. +-commutative N/A

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\log \color{blue}{\left(1 + x\right)}}} - \sqrt[3]{x} \]

   17. lower-log1p.f64 5.0

       \[\leadsto \sqrt[3]{{\left(e^{1}\right)}^{\color{blue}{\left(\mathsf{log1p}\left(x\right)\right)}}} - \sqrt[3]{x} \]

4. Applied rewrites 5.0%

   \[\leadsto \sqrt[3]{\color{blue}{{\left(e^{1}\right)}^{\left(\mathsf{log1p}\left(x\right)\right)}}} - \sqrt[3]{x} \]

5. Taylor expanded in x around inf

   \[\leadsto \color{blue}{0} \]
6. Step-by-step derivation

7. Applied rewrites 4.1%

   \[\leadsto \color{blue}{0} \]
8. Add Preprocessing

Developer Target 1: 98.5% accurate, 0.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt[3]{x + 1}\\ \frac{1}{\left(t\_0 \cdot t\_0 + \sqrt[3]{x} \cdot t\_0\right) + \sqrt[3]{x} \cdot \sqrt[3]{x}} \end{array} \end{array} \]

FPCore

(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))))))

C

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)));
}

Java

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)));
}

Julia

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

Wolfram

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]]

Reproduce

herbie shell --seed 2024326 
(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)))