2cos (problem 3.3.5)

Percentage Accurate: 52.0% → 99.5%

Time: 16.6s

Alternatives: 16

Speedup: 41.0×

Specification

\[\left(\left(-10000 \leq x \land x \leq 10000\right) \land 10^{-16} \cdot \left|x\right| < \varepsilon\right) \land \varepsilon < \left|x\right|\]

Math

\[\begin{array}{l} \\ \cos \left(x + \varepsilon\right) - \cos x \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (- (cos (+ x eps)) (cos x)))

C

double code(double x, double eps) {
	return cos((x + eps)) - cos(x);
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = cos((x + eps)) - cos(x)
end function

Java

public static double code(double x, double eps) {
	return Math.cos((x + eps)) - Math.cos(x);
}

Python

def code(x, eps):
	return math.cos((x + eps)) - math.cos(x)

Julia

function code(x, eps)
	return Float64(cos(Float64(x + eps)) - cos(x))
end

MATLAB

function tmp = code(x, eps)
	tmp = cos((x + eps)) - cos(x);
end

Wolfram

code[x_, eps_] := N[(N[Cos[N[(x + eps), $MachinePrecision]], $MachinePrecision] - N[Cos[x], $MachinePrecision]), $MachinePrecision]

Initial Program: 52.0% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \cos \left(x + \varepsilon\right) - \cos x \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (- (cos (+ x eps)) (cos x)))

C

double code(double x, double eps) {
	return cos((x + eps)) - cos(x);
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = cos((x + eps)) - cos(x)
end function

Java

public static double code(double x, double eps) {
	return Math.cos((x + eps)) - Math.cos(x);
}

Python

def code(x, eps):
	return math.cos((x + eps)) - math.cos(x)

Julia

function code(x, eps)
	return Float64(cos(Float64(x + eps)) - cos(x))
end

MATLAB

function tmp = code(x, eps)
	tmp = cos((x + eps)) - cos(x);
end

Wolfram

code[x_, eps_] := N[(N[Cos[N[(x + eps), $MachinePrecision]], $MachinePrecision] - N[Cos[x], $MachinePrecision]), $MachinePrecision]

Alternative 1: 99.5% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \mathsf{fma}\left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right), \varepsilon, \varepsilon \cdot \left(-0.5 \cdot \left(\varepsilon \cdot \cos x\right)\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (fma
  (* (sin x) (+ (* eps (* eps 0.16666666666666666)) -1.0))
  eps
  (* eps (* -0.5 (* eps (cos x))))))

C

double code(double x, double eps) {
	return fma((sin(x) * ((eps * (eps * 0.16666666666666666)) + -1.0)), eps, (eps * (-0.5 * (eps * cos(x)))));
}

Julia

function code(x, eps)
	return fma(Float64(sin(x) * Float64(Float64(eps * Float64(eps * 0.16666666666666666)) + -1.0)), eps, Float64(eps * Float64(-0.5 * Float64(eps * cos(x)))))
end

Wolfram

code[x_, eps_] := N[(N[(N[Sin[x], $MachinePrecision] * N[(N[(eps * N[(eps * 0.16666666666666666), $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision] * eps + N[(eps * N[(-0.5 * N[(eps * N[Cos[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) - \sin x\right)}\right) \]

   2. sub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) + \color{blue}{\left(\mathsf{neg}\left(\sin x\right)\right)}\right)\right) \]

   3. distribute-lft-in N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) + \varepsilon \cdot \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right)\right) + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right) \]

   4. associate-+l+ N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) + \color{blue}{\left(\varepsilon \cdot \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) + \left(\mathsf{neg}\left(\sin x\right)\right)\right)}\right)\right) \]

   5. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) + \left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right)\right) \]

   6. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon + \left(\mathsf{neg}\left(\sin x\right)\right)\right)}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \left(\color{blue}{\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon} + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   8. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \color{blue}{\varepsilon} + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   9. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   10. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\varepsilon \cdot \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right)\right) \]

   11. associate-*r* N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\varepsilon \cdot \left(\left(\frac{1}{6} \cdot \varepsilon\right) \cdot \sin x\right) + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   12. associate-*r* N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\left(\varepsilon \cdot \left(\frac{1}{6} \cdot \varepsilon\right)\right) \cdot \sin x + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right)\right) \]

   13. neg-mul-1 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\left(\varepsilon \cdot \left(\frac{1}{6} \cdot \varepsilon\right)\right) \cdot \sin x + -1 \cdot \color{blue}{\sin x}\right)\right)\right) \]

5. Simplified 99.8%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) + \sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right)\right)} \]
6. Step-by-step derivation

   1. +-commutative N/A

      \[\leadsto \varepsilon \cdot \left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right) + -1\right) + \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)}\right) \]

   2. distribute-rgt-in N/A

      \[\leadsto \left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right) + -1\right)\right) \cdot \varepsilon + \color{blue}{\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon} \]

   3. fma-define N/A

      \[\leadsto \mathsf{fma}\left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right) + -1\right), \color{blue}{\varepsilon}, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right) \]

   4. fma-lowering-fma.f64 N/A

      \[\leadsto \mathsf{fma.f64}\left(\left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right) + -1\right)\right), \color{blue}{\varepsilon}, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right)\right) \]

   5. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\sin x, \left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right) + -1\right)\right), \varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right)\right) \]

   6. sin-lowering-sin.f64 N/A

      \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right) + -1\right)\right), \varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right)\right) \]

   7. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\left(\varepsilon \cdot \left(\varepsilon \cdot \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right)\right) \]

   8. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right)\right) \]

   9. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right) \cdot \varepsilon\right)\right) \]

   10. *-commutative N/A

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \left(\varepsilon \cdot \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right)\right)\right) \]

   11. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right)\right)\right) \]

   12. *-commutative N/A

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \mathsf{*.f64}\left(\varepsilon, \left(\left(\frac{-1}{2} \cdot \cos x\right) \cdot \varepsilon\right)\right)\right) \]

   13. associate-*l* N/A

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \left(\cos x \cdot \varepsilon\right)\right)\right)\right) \]

   14. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \left(\cos x \cdot \varepsilon\right)\right)\right)\right) \]

   15. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{*.f64}\left(\cos x, \varepsilon\right)\right)\right)\right) \]

   16. cos-lowering-cos.f64 100.0%

       \[\leadsto \mathsf{fma.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right)\right), -1\right)\right), \varepsilon, \mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{*.f64}\left(\mathsf{cos.f64}\left(x\right), \varepsilon\right)\right)\right)\right) \]

7. Applied egg-rr 100.0%

   \[\leadsto \color{blue}{\mathsf{fma}\left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right), \varepsilon, \varepsilon \cdot \left(-0.5 \cdot \left(\cos x \cdot \varepsilon\right)\right)\right)} \]

8. Final simplification 100.0%

   \[\leadsto \mathsf{fma}\left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right), \varepsilon, \varepsilon \cdot \left(-0.5 \cdot \left(\varepsilon \cdot \cos x\right)\right)\right) \]
9. Add Preprocessing

Alternative 2: 99.3% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x + \sin x \cdot \left(\varepsilon \cdot 0.16666666666666666\right)\right) - \sin x\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (*
  eps
  (-
   (* eps (+ (* -0.5 (cos x)) (* (sin x) (* eps 0.16666666666666666))))
   (sin x))))

C

double code(double x, double eps) {
	return eps * ((eps * ((-0.5 * cos(x)) + (sin(x) * (eps * 0.16666666666666666)))) - sin(x));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * (((-0.5d0) * cos(x)) + (sin(x) * (eps * 0.16666666666666666d0)))) - sin(x))
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * ((-0.5 * Math.cos(x)) + (Math.sin(x) * (eps * 0.16666666666666666)))) - Math.sin(x));
}

Python

def code(x, eps):
	return eps * ((eps * ((-0.5 * math.cos(x)) + (math.sin(x) * (eps * 0.16666666666666666)))) - math.sin(x))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * Float64(Float64(-0.5 * cos(x)) + Float64(sin(x) * Float64(eps * 0.16666666666666666)))) - sin(x)))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * ((-0.5 * cos(x)) + (sin(x) * (eps * 0.16666666666666666)))) - sin(x));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * N[(N[(-0.5 * N[Cos[x], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[x], $MachinePrecision] * N[(eps * 0.16666666666666666), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Sin[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \varepsilon \cdot \left(\frac{1}{24} \cdot \left(\varepsilon \cdot \cos x\right) - \frac{-1}{6} \cdot \sin x\right)\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \varepsilon \cdot \left(\frac{1}{24} \cdot \left(\varepsilon \cdot \cos x\right) - \frac{-1}{6} \cdot \sin x\right)\right) - \sin x\right)}\right) \]

   2. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \varepsilon \cdot \left(\frac{1}{24} \cdot \left(\varepsilon \cdot \cos x\right) - \frac{-1}{6} \cdot \sin x\right)\right)\right), \color{blue}{\sin x}\right)\right) \]

5. Simplified 99.8%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x + \varepsilon \cdot \left(\left(\varepsilon \cdot \cos x\right) \cdot 0.041666666666666664 + 0.16666666666666666 \cdot \sin x\right)\right) - \sin x\right)} \]

6. Taylor expanded in eps around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right)}\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]
7. Step-by-step derivation

   1. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x + \left(\frac{1}{6} \cdot \varepsilon\right) \cdot \sin x\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x + \left(\varepsilon \cdot \frac{1}{6}\right) \cdot \sin x\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x + \varepsilon \cdot \left(\frac{1}{6} \cdot \sin x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   4. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\left(\frac{-1}{2} \cdot \cos x\right), \left(\varepsilon \cdot \left(\frac{1}{6} \cdot \sin x\right)\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   5. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right), \left(\varepsilon \cdot \left(\frac{1}{6} \cdot \sin x\right)\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   6. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \left(\varepsilon \cdot \left(\frac{1}{6} \cdot \sin x\right)\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   7. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \left(\left(\varepsilon \cdot \frac{1}{6}\right) \cdot \sin x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   8. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \left(\left(\frac{1}{6} \cdot \varepsilon\right) \cdot \sin x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   9. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \mathsf{*.f64}\left(\left(\frac{1}{6} \cdot \varepsilon\right), \sin x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   10. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \mathsf{*.f64}\left(\left(\varepsilon \cdot \frac{1}{6}\right), \sin x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   11. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right), \sin x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

   12. sin-lowering-sin.f64 99.8%

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right), \mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{6}\right), \mathsf{sin.f64}\left(x\right)\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

8. Simplified 99.8%

   \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot \color{blue}{\left(-0.5 \cdot \cos x + \left(\varepsilon \cdot 0.16666666666666666\right) \cdot \sin x\right)} - \sin x\right) \]

9. Final simplification 99.8%

   \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x + \sin x \cdot \left(\varepsilon \cdot 0.16666666666666666\right)\right) - \sin x\right) \]
10. Add Preprocessing

Alternative 3: 99.3% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right) + \varepsilon \cdot \left(-0.5 \cdot \cos x\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (*
  eps
  (+
   (* (sin x) (+ (* eps (* eps 0.16666666666666666)) -1.0))
   (* eps (* -0.5 (cos x))))))

C

double code(double x, double eps) {
	return eps * ((sin(x) * ((eps * (eps * 0.16666666666666666)) + -1.0)) + (eps * (-0.5 * cos(x))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((sin(x) * ((eps * (eps * 0.16666666666666666d0)) + (-1.0d0))) + (eps * ((-0.5d0) * cos(x))))
end function

Java

public static double code(double x, double eps) {
	return eps * ((Math.sin(x) * ((eps * (eps * 0.16666666666666666)) + -1.0)) + (eps * (-0.5 * Math.cos(x))));
}

Python

def code(x, eps):
	return eps * ((math.sin(x) * ((eps * (eps * 0.16666666666666666)) + -1.0)) + (eps * (-0.5 * math.cos(x))))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(sin(x) * Float64(Float64(eps * Float64(eps * 0.16666666666666666)) + -1.0)) + Float64(eps * Float64(-0.5 * cos(x)))))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((sin(x) * ((eps * (eps * 0.16666666666666666)) + -1.0)) + (eps * (-0.5 * cos(x))));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(N[Sin[x], $MachinePrecision] * N[(N[(eps * N[(eps * 0.16666666666666666), $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision] + N[(eps * N[(-0.5 * N[Cos[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) - \sin x\right)}\right) \]

   2. sub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x + \frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) + \color{blue}{\left(\mathsf{neg}\left(\sin x\right)\right)}\right)\right) \]

   3. distribute-lft-in N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) + \varepsilon \cdot \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right)\right) + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right) \]

   4. associate-+l+ N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) + \color{blue}{\left(\varepsilon \cdot \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) + \left(\mathsf{neg}\left(\sin x\right)\right)\right)}\right)\right) \]

   5. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) + \left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right)\right) \]

   6. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon + \left(\mathsf{neg}\left(\sin x\right)\right)\right)}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \left(\color{blue}{\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon} + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   8. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \color{blue}{\varepsilon} + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   9. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) \cdot \varepsilon + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   10. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\varepsilon \cdot \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \sin x\right)\right) + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right)\right) \]

   11. associate-*r* N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\varepsilon \cdot \left(\left(\frac{1}{6} \cdot \varepsilon\right) \cdot \sin x\right) + \left(\mathsf{neg}\left(\sin x\right)\right)\right)\right)\right) \]

   12. associate-*r* N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\left(\varepsilon \cdot \left(\frac{1}{6} \cdot \varepsilon\right)\right) \cdot \sin x + \left(\mathsf{neg}\left(\color{blue}{\sin x}\right)\right)\right)\right)\right) \]

   13. neg-mul-1 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \left(\left(\varepsilon \cdot \left(\frac{1}{6} \cdot \varepsilon\right)\right) \cdot \sin x + -1 \cdot \color{blue}{\sin x}\right)\right)\right) \]

5. Simplified 99.8%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) + \sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right)\right)} \]

6. Final simplification 99.8%

   \[\leadsto \varepsilon \cdot \left(\sin x \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot 0.16666666666666666\right) + -1\right) + \varepsilon \cdot \left(-0.5 \cdot \cos x\right)\right) \]
7. Add Preprocessing

Alternative 4: 99.2% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (* eps (- (* eps (* -0.5 (cos x))) (sin x))))

C

double code(double x, double eps) {
	return eps * ((eps * (-0.5 * cos(x))) - sin(x));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * ((-0.5d0) * cos(x))) - sin(x))
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * (-0.5 * Math.cos(x))) - Math.sin(x));
}

Python

def code(x, eps):
	return eps * ((eps * (-0.5 * math.cos(x))) - math.sin(x))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * Float64(-0.5 * cos(x))) - sin(x)))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * (-0.5 * cos(x))) - sin(x));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * N[(-0.5 * N[Cos[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Sin[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]
6. Add Preprocessing

Alternative 5: 98.8% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5 - \sin x\right) \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (* eps (- (* eps -0.5) (sin x))))

C

double code(double x, double eps) {
	return eps * ((eps * -0.5) - sin(x));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * (-0.5d0)) - sin(x))
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * -0.5) - Math.sin(x));
}

Python

def code(x, eps):
	return eps * ((eps * -0.5) - math.sin(x))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * -0.5) - sin(x)))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * -0.5) - sin(x));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * -0.5), $MachinePrecision] - N[Sin[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\color{blue}{\left(\frac{-1}{2} \cdot \varepsilon\right)}, \mathsf{sin.f64}\left(x\right)\right)\right) \]
7. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

   2. *-lowering-*.f64 99.3%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

8. Simplified 99.3%

   \[\leadsto \varepsilon \cdot \left(\color{blue}{\varepsilon \cdot -0.5} - \sin x\right) \]
9. Add Preprocessing

Alternative 6: 98.4% accurate, 7.6× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5 + x \cdot \left(-1 - \left(x \cdot x\right) \cdot \left(-0.16666666666666666 + x \cdot \left(x \cdot \left(0.008333333333333333 + \left(x \cdot x\right) \cdot -0.0001984126984126984\right)\right)\right)\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (*
  eps
  (+
   (* eps -0.5)
   (*
    x
    (-
     -1.0
     (*
      (* x x)
      (+
       -0.16666666666666666
       (*
        x
        (*
         x
         (+ 0.008333333333333333 (* (* x x) -0.0001984126984126984)))))))))))

C

double code(double x, double eps) {
	return eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + (x * (x * (0.008333333333333333 + ((x * x) * -0.0001984126984126984)))))))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * (-0.5d0)) + (x * ((-1.0d0) - ((x * x) * ((-0.16666666666666666d0) + (x * (x * (0.008333333333333333d0 + ((x * x) * (-0.0001984126984126984d0))))))))))
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + (x * (x * (0.008333333333333333 + ((x * x) * -0.0001984126984126984)))))))));
}

Python

def code(x, eps):
	return eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + (x * (x * (0.008333333333333333 + ((x * x) * -0.0001984126984126984)))))))))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * -0.5) + Float64(x * Float64(-1.0 - Float64(Float64(x * x) * Float64(-0.16666666666666666 + Float64(x * Float64(x * Float64(0.008333333333333333 + Float64(Float64(x * x) * -0.0001984126984126984))))))))))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + (x * (x * (0.008333333333333333 + ((x * x) * -0.0001984126984126984)))))))));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * -0.5), $MachinePrecision] + N[(x * N[(-1.0 - N[(N[(x * x), $MachinePrecision] * N[(-0.16666666666666666 + N[(x * N[(x * N[(0.008333333333333333 + N[(N[(x * x), $MachinePrecision] * -0.0001984126984126984), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\color{blue}{\left(\frac{-1}{2} \cdot \varepsilon\right)}, \mathsf{sin.f64}\left(x\right)\right)\right) \]
7. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

   2. *-lowering-*.f64 99.3%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

8. Simplified 99.3%

   \[\leadsto \varepsilon \cdot \left(\color{blue}{\varepsilon \cdot -0.5} - \sin x\right) \]

9. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \color{blue}{\left(x \cdot \left(1 + {x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)}\right)\right) \]
10. Step-by-step derivation

    1. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \color{blue}{\left(1 + {x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)}\right)\right)\right) \]

    2. +-lowering-+.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \color{blue}{\left({x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)}\right)\right)\right)\right) \]

    3. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left({x}^{2}\right), \color{blue}{\left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)}\right)\right)\right)\right)\right) \]

    4. unpow2 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left(x \cdot x\right), \left(\color{blue}{{x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)} - \frac{1}{6}\right)\right)\right)\right)\right)\right) \]

    5. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\color{blue}{{x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)} - \frac{1}{6}\right)\right)\right)\right)\right)\right) \]

    6. sub-neg N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{6}\right)\right)}\right)\right)\right)\right)\right)\right) \]

    7. metadata-eval N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) + \frac{-1}{6}\right)\right)\right)\right)\right)\right) \]

    8. +-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\frac{-1}{6} + \color{blue}{{x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)}\right)\right)\right)\right)\right)\right) \]

    9. +-lowering-+.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \color{blue}{\left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)}\right)\right)\right)\right)\right)\right) \]

    10. unpow2 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \left(\left(x \cdot x\right) \cdot \left(\color{blue}{\frac{1}{120}} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right)\right)\right) \]

    11. associate-*l* N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \left(x \cdot \color{blue}{\left(x \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)}\right)\right)\right)\right)\right)\right)\right) \]

    12. *-lowering-*.f64 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \color{blue}{\left(x \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)}\right)\right)\right)\right)\right)\right)\right) \]

    13. *-lowering-*.f64 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)}\right)\right)\right)\right)\right)\right)\right)\right) \]

    14. +-lowering-+.f64 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{1}{120}, \color{blue}{\left(\frac{-1}{5040} \cdot {x}^{2}\right)}\right)\right)\right)\right)\right)\right)\right)\right)\right) \]

    15. *-commutative N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{1}{120}, \left({x}^{2} \cdot \color{blue}{\frac{-1}{5040}}\right)\right)\right)\right)\right)\right)\right)\right)\right)\right) \]

    16. *-lowering-*.f64 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{1}{120}, \mathsf{*.f64}\left(\left({x}^{2}\right), \color{blue}{\frac{-1}{5040}}\right)\right)\right)\right)\right)\right)\right)\right)\right)\right) \]

    17. unpow2 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{1}{120}, \mathsf{*.f64}\left(\left(x \cdot x\right), \frac{-1}{5040}\right)\right)\right)\right)\right)\right)\right)\right)\right)\right) \]

    18. *-lowering-*.f64 98.6%

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{1}{120}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \frac{-1}{5040}\right)\right)\right)\right)\right)\right)\right)\right)\right)\right) \]

11. Simplified 98.6%

    \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot -0.5 - \color{blue}{x \cdot \left(1 + \left(x \cdot x\right) \cdot \left(-0.16666666666666666 + x \cdot \left(x \cdot \left(0.008333333333333333 + \left(x \cdot x\right) \cdot -0.0001984126984126984\right)\right)\right)\right)}\right) \]

12. Final simplification 98.6%

    \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot -0.5 + x \cdot \left(-1 - \left(x \cdot x\right) \cdot \left(-0.16666666666666666 + x \cdot \left(x \cdot \left(0.008333333333333333 + \left(x \cdot x\right) \cdot -0.0001984126984126984\right)\right)\right)\right)\right) \]
13. Add Preprocessing

Alternative 7: 98.3% accurate, 8.9× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5 - x\right) + \left(x \cdot \left(x \cdot x\right)\right) \cdot \left(\varepsilon \cdot \left(0.16666666666666666 + \left(x \cdot x\right) \cdot -0.008333333333333333\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (+
  (* eps (- (* eps -0.5) x))
  (*
   (* x (* x x))
   (* eps (+ 0.16666666666666666 (* (* x x) -0.008333333333333333))))))

C

double code(double x, double eps) {
	return (eps * ((eps * -0.5) - x)) + ((x * (x * x)) * (eps * (0.16666666666666666 + ((x * x) * -0.008333333333333333))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = (eps * ((eps * (-0.5d0)) - x)) + ((x * (x * x)) * (eps * (0.16666666666666666d0 + ((x * x) * (-0.008333333333333333d0)))))
end function

Java

public static double code(double x, double eps) {
	return (eps * ((eps * -0.5) - x)) + ((x * (x * x)) * (eps * (0.16666666666666666 + ((x * x) * -0.008333333333333333))));
}

Python

def code(x, eps):
	return (eps * ((eps * -0.5) - x)) + ((x * (x * x)) * (eps * (0.16666666666666666 + ((x * x) * -0.008333333333333333))))

Julia

function code(x, eps)
	return Float64(Float64(eps * Float64(Float64(eps * -0.5) - x)) + Float64(Float64(x * Float64(x * x)) * Float64(eps * Float64(0.16666666666666666 + Float64(Float64(x * x) * -0.008333333333333333)))))
end

MATLAB

function tmp = code(x, eps)
	tmp = (eps * ((eps * -0.5) - x)) + ((x * (x * x)) * (eps * (0.16666666666666666 + ((x * x) * -0.008333333333333333))));
end

Wolfram

code[x_, eps_] := N[(N[(eps * N[(N[(eps * -0.5), $MachinePrecision] - x), $MachinePrecision]), $MachinePrecision] + N[(N[(x * N[(x * x), $MachinePrecision]), $MachinePrecision] * N[(eps * N[(0.16666666666666666 + N[(N[(x * x), $MachinePrecision] * -0.008333333333333333), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\color{blue}{\left(\frac{-1}{2} \cdot \varepsilon\right)}, \mathsf{sin.f64}\left(x\right)\right)\right) \]
7. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

   2. *-lowering-*.f64 99.3%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

8. Simplified 99.3%

   \[\leadsto \varepsilon \cdot \left(\color{blue}{\varepsilon \cdot -0.5} - \sin x\right) \]

9. Taylor expanded in x around 0

   \[\leadsto \color{blue}{\frac{-1}{2} \cdot {\varepsilon}^{2} + x \cdot \left(-1 \cdot \varepsilon + {x}^{2} \cdot \left(\frac{-1}{120} \cdot \left(\varepsilon \cdot {x}^{2}\right) + \frac{1}{6} \cdot \varepsilon\right)\right)} \]
10. Step-by-step derivation

    1. distribute-rgt-in N/A

       \[\leadsto \frac{-1}{2} \cdot {\varepsilon}^{2} + \left(\left(-1 \cdot \varepsilon\right) \cdot x + \color{blue}{\left({x}^{2} \cdot \left(\frac{-1}{120} \cdot \left(\varepsilon \cdot {x}^{2}\right) + \frac{1}{6} \cdot \varepsilon\right)\right) \cdot x}\right) \]

    2. associate-+r+ N/A

       \[\leadsto \left(\frac{-1}{2} \cdot {\varepsilon}^{2} + \left(-1 \cdot \varepsilon\right) \cdot x\right) + \color{blue}{\left({x}^{2} \cdot \left(\frac{-1}{120} \cdot \left(\varepsilon \cdot {x}^{2}\right) + \frac{1}{6} \cdot \varepsilon\right)\right) \cdot x} \]

    3. +-commutative N/A

       \[\leadsto \left(\left(-1 \cdot \varepsilon\right) \cdot x + \frac{-1}{2} \cdot {\varepsilon}^{2}\right) + \color{blue}{\left({x}^{2} \cdot \left(\frac{-1}{120} \cdot \left(\varepsilon \cdot {x}^{2}\right) + \frac{1}{6} \cdot \varepsilon\right)\right)} \cdot x \]

    4. associate-*r* N/A

       \[\leadsto \left(-1 \cdot \left(\varepsilon \cdot x\right) + \frac{-1}{2} \cdot {\varepsilon}^{2}\right) + \left(\color{blue}{{x}^{2}} \cdot \left(\frac{-1}{120} \cdot \left(\varepsilon \cdot {x}^{2}\right) + \frac{1}{6} \cdot \varepsilon\right)\right) \cdot x \]

    5. +-lowering-+.f64 N/A

       \[\leadsto \mathsf{+.f64}\left(\left(-1 \cdot \left(\varepsilon \cdot x\right) + \frac{-1}{2} \cdot {\varepsilon}^{2}\right), \color{blue}{\left(\left({x}^{2} \cdot \left(\frac{-1}{120} \cdot \left(\varepsilon \cdot {x}^{2}\right) + \frac{1}{6} \cdot \varepsilon\right)\right) \cdot x\right)}\right) \]

11. Simplified 98.6%

    \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot -0.5 - x\right) + \left(x \cdot \left(x \cdot x\right)\right) \cdot \left(\varepsilon \cdot \left(0.16666666666666666 + \left(x \cdot x\right) \cdot -0.008333333333333333\right)\right)} \]
12. Add Preprocessing

Alternative 8: 98.3% accurate, 9.8× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5 + x \cdot \left(-1 - \left(x \cdot x\right) \cdot \left(-0.16666666666666666 + \left(x \cdot x\right) \cdot 0.008333333333333333\right)\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (*
  eps
  (+
   (* eps -0.5)
   (*
    x
    (-
     -1.0
     (* (* x x) (+ -0.16666666666666666 (* (* x x) 0.008333333333333333))))))))

C

double code(double x, double eps) {
	return eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + ((x * x) * 0.008333333333333333))))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * (-0.5d0)) + (x * ((-1.0d0) - ((x * x) * ((-0.16666666666666666d0) + ((x * x) * 0.008333333333333333d0))))))
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + ((x * x) * 0.008333333333333333))))));
}

Python

def code(x, eps):
	return eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + ((x * x) * 0.008333333333333333))))))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * -0.5) + Float64(x * Float64(-1.0 - Float64(Float64(x * x) * Float64(-0.16666666666666666 + Float64(Float64(x * x) * 0.008333333333333333)))))))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * -0.5) + (x * (-1.0 - ((x * x) * (-0.16666666666666666 + ((x * x) * 0.008333333333333333))))));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * -0.5), $MachinePrecision] + N[(x * N[(-1.0 - N[(N[(x * x), $MachinePrecision] * N[(-0.16666666666666666 + N[(N[(x * x), $MachinePrecision] * 0.008333333333333333), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\color{blue}{\left(\frac{-1}{2} \cdot \varepsilon\right)}, \mathsf{sin.f64}\left(x\right)\right)\right) \]
7. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

   2. *-lowering-*.f64 99.3%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

8. Simplified 99.3%

   \[\leadsto \varepsilon \cdot \left(\color{blue}{\varepsilon \cdot -0.5} - \sin x\right) \]

9. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \color{blue}{\left(x \cdot \left(1 + {x}^{2} \cdot \left(\frac{1}{120} \cdot {x}^{2} - \frac{1}{6}\right)\right)\right)}\right)\right) \]
10. Step-by-step derivation

    1. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \color{blue}{\left(1 + {x}^{2} \cdot \left(\frac{1}{120} \cdot {x}^{2} - \frac{1}{6}\right)\right)}\right)\right)\right) \]

    2. +-lowering-+.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \color{blue}{\left({x}^{2} \cdot \left(\frac{1}{120} \cdot {x}^{2} - \frac{1}{6}\right)\right)}\right)\right)\right)\right) \]

    3. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left({x}^{2}\right), \color{blue}{\left(\frac{1}{120} \cdot {x}^{2} - \frac{1}{6}\right)}\right)\right)\right)\right)\right) \]

    4. unpow2 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\left(x \cdot x\right), \left(\color{blue}{\frac{1}{120} \cdot {x}^{2}} - \frac{1}{6}\right)\right)\right)\right)\right)\right) \]

    5. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\color{blue}{\frac{1}{120} \cdot {x}^{2}} - \frac{1}{6}\right)\right)\right)\right)\right)\right) \]

    6. sub-neg N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\frac{1}{120} \cdot {x}^{2} + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{6}\right)\right)}\right)\right)\right)\right)\right)\right) \]

    7. metadata-eval N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\frac{1}{120} \cdot {x}^{2} + \frac{-1}{6}\right)\right)\right)\right)\right)\right) \]

    8. +-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\frac{-1}{6} + \color{blue}{\frac{1}{120} \cdot {x}^{2}}\right)\right)\right)\right)\right)\right) \]

    9. +-lowering-+.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \color{blue}{\left(\frac{1}{120} \cdot {x}^{2}\right)}\right)\right)\right)\right)\right)\right) \]

    10. *-commutative N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \left({x}^{2} \cdot \color{blue}{\frac{1}{120}}\right)\right)\right)\right)\right)\right)\right) \]

    11. *-lowering-*.f64 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\left({x}^{2}\right), \color{blue}{\frac{1}{120}}\right)\right)\right)\right)\right)\right)\right) \]

    12. unpow2 N/A

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\left(x \cdot x\right), \frac{1}{120}\right)\right)\right)\right)\right)\right)\right) \]

    13. *-lowering-*.f64 98.6%

        \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \frac{1}{120}\right)\right)\right)\right)\right)\right)\right) \]

11. Simplified 98.6%

    \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot -0.5 - \color{blue}{x \cdot \left(1 + \left(x \cdot x\right) \cdot \left(-0.16666666666666666 + \left(x \cdot x\right) \cdot 0.008333333333333333\right)\right)}\right) \]

12. Final simplification 98.6%

    \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot -0.5 + x \cdot \left(-1 - \left(x \cdot x\right) \cdot \left(-0.16666666666666666 + \left(x \cdot x\right) \cdot 0.008333333333333333\right)\right)\right) \]
13. Add Preprocessing

Alternative 9: 98.3% accurate, 10.8× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5 + x \cdot \left(-1 + x \cdot \left(x \cdot 0.16666666666666666 + \varepsilon \cdot 0.25\right)\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (*
  eps
  (+
   (* eps -0.5)
   (* x (+ -1.0 (* x (+ (* x 0.16666666666666666) (* eps 0.25))))))))

C

double code(double x, double eps) {
	return eps * ((eps * -0.5) + (x * (-1.0 + (x * ((x * 0.16666666666666666) + (eps * 0.25))))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * (-0.5d0)) + (x * ((-1.0d0) + (x * ((x * 0.16666666666666666d0) + (eps * 0.25d0))))))
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * -0.5) + (x * (-1.0 + (x * ((x * 0.16666666666666666) + (eps * 0.25))))));
}

Python

def code(x, eps):
	return eps * ((eps * -0.5) + (x * (-1.0 + (x * ((x * 0.16666666666666666) + (eps * 0.25))))))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * -0.5) + Float64(x * Float64(-1.0 + Float64(x * Float64(Float64(x * 0.16666666666666666) + Float64(eps * 0.25)))))))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * -0.5) + (x * (-1.0 + (x * ((x * 0.16666666666666666) + (eps * 0.25))))));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * -0.5), $MachinePrecision] + N[(x * N[(-1.0 + N[(x * N[(N[(x * 0.16666666666666666), $MachinePrecision] + N[(eps * 0.25), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \varepsilon + x \cdot \left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) - 1\right)\right)}\right) \]
7. Step-by-step derivation

   1. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\left(\frac{-1}{2} \cdot \varepsilon\right), \color{blue}{\left(x \cdot \left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) - 1\right)\right)}\right)\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), \left(\color{blue}{x} \cdot \left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) - 1\right)\right)\right)\right) \]

   3. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \left(\color{blue}{x} \cdot \left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) - 1\right)\right)\right)\right) \]

   4. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \color{blue}{\left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) - 1\right)}\right)\right)\right) \]

   5. sub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}\right)\right)\right)\right) \]

   6. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right) + -1\right)\right)\right)\right) \]

   7. +-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \left(-1 + \color{blue}{x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right)}\right)\right)\right)\right) \]

   8. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(-1, \color{blue}{\left(x \cdot \left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right)\right)}\right)\right)\right)\right) \]

   9. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(-1, \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{1}{6} \cdot x + \frac{1}{4} \cdot \varepsilon\right)}\right)\right)\right)\right)\right) \]

   10. +-lowering-+.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(-1, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\left(\frac{1}{6} \cdot x\right), \color{blue}{\left(\frac{1}{4} \cdot \varepsilon\right)}\right)\right)\right)\right)\right)\right) \]

   11. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(-1, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{1}{6}, x\right), \left(\color{blue}{\frac{1}{4}} \cdot \varepsilon\right)\right)\right)\right)\right)\right)\right) \]

   12. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(-1, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{1}{6}, x\right), \left(\varepsilon \cdot \color{blue}{\frac{1}{4}}\right)\right)\right)\right)\right)\right)\right) \]

   13. *-lowering-*.f64 98.5%

       \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(-1, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\mathsf{*.f64}\left(\frac{1}{6}, x\right), \mathsf{*.f64}\left(\varepsilon, \color{blue}{\frac{1}{4}}\right)\right)\right)\right)\right)\right)\right) \]

8. Simplified 98.5%

   \[\leadsto \varepsilon \cdot \color{blue}{\left(\varepsilon \cdot -0.5 + x \cdot \left(-1 + x \cdot \left(0.16666666666666666 \cdot x + \varepsilon \cdot 0.25\right)\right)\right)} \]

9. Final simplification 98.5%

   \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot -0.5 + x \cdot \left(-1 + x \cdot \left(x \cdot 0.16666666666666666 + \varepsilon \cdot 0.25\right)\right)\right) \]
10. Add Preprocessing

Alternative 10: 98.2% accurate, 13.7× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\left(\varepsilon \cdot -0.5 - x\right) + x \cdot \left(x \cdot \left(x \cdot 0.16666666666666666\right)\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (* eps (+ (- (* eps -0.5) x) (* x (* x (* x 0.16666666666666666))))))

C

double code(double x, double eps) {
	return eps * (((eps * -0.5) - x) + (x * (x * (x * 0.16666666666666666))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * (((eps * (-0.5d0)) - x) + (x * (x * (x * 0.16666666666666666d0))))
end function

Java

public static double code(double x, double eps) {
	return eps * (((eps * -0.5) - x) + (x * (x * (x * 0.16666666666666666))));
}

Python

def code(x, eps):
	return eps * (((eps * -0.5) - x) + (x * (x * (x * 0.16666666666666666))))

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(Float64(eps * -0.5) - x) + Float64(x * Float64(x * Float64(x * 0.16666666666666666)))))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * (((eps * -0.5) - x) + (x * (x * (x * 0.16666666666666666))));
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(N[(eps * -0.5), $MachinePrecision] - x), $MachinePrecision] + N[(x * N[(x * N[(x * 0.16666666666666666), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\color{blue}{\left(\frac{-1}{2} \cdot \varepsilon\right)}, \mathsf{sin.f64}\left(x\right)\right)\right) \]
7. Step-by-step derivation

   1. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

   2. *-lowering-*.f64 99.3%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), \mathsf{sin.f64}\left(\color{blue}{x}\right)\right)\right) \]

8. Simplified 99.3%

   \[\leadsto \varepsilon \cdot \left(\color{blue}{\varepsilon \cdot -0.5} - \sin x\right) \]

9. Taylor expanded in x around 0

   \[\leadsto \color{blue}{\frac{-1}{2} \cdot {\varepsilon}^{2} + x \cdot \left(-1 \cdot \varepsilon + \frac{1}{6} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right)} \]
10. Step-by-step derivation

    1. distribute-rgt-in N/A

       \[\leadsto \frac{-1}{2} \cdot {\varepsilon}^{2} + \left(\left(-1 \cdot \varepsilon\right) \cdot x + \color{blue}{\left(\frac{1}{6} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right) \cdot x}\right) \]

    2. associate-+r+ N/A

       \[\leadsto \left(\frac{-1}{2} \cdot {\varepsilon}^{2} + \left(-1 \cdot \varepsilon\right) \cdot x\right) + \color{blue}{\left(\frac{1}{6} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right) \cdot x} \]

    3. +-commutative N/A

       \[\leadsto \left(\left(-1 \cdot \varepsilon\right) \cdot x + \frac{-1}{2} \cdot {\varepsilon}^{2}\right) + \color{blue}{\left(\frac{1}{6} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right)} \cdot x \]

    4. associate-*r* N/A

       \[\leadsto \left(-1 \cdot \left(\varepsilon \cdot x\right) + \frac{-1}{2} \cdot {\varepsilon}^{2}\right) + \left(\color{blue}{\frac{1}{6}} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right) \cdot x \]

    5. *-commutative N/A

       \[\leadsto \left(-1 \cdot \left(x \cdot \varepsilon\right) + \frac{-1}{2} \cdot {\varepsilon}^{2}\right) + \left(\frac{1}{6} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right) \cdot x \]

    6. associate-*r* N/A

       \[\leadsto \left(\left(-1 \cdot x\right) \cdot \varepsilon + \frac{-1}{2} \cdot {\varepsilon}^{2}\right) + \left(\color{blue}{\frac{1}{6}} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right) \cdot x \]

    7. unpow2 N/A

       \[\leadsto \left(\left(-1 \cdot x\right) \cdot \varepsilon + \frac{-1}{2} \cdot \left(\varepsilon \cdot \varepsilon\right)\right) + \left(\frac{1}{6} \cdot \left(\varepsilon \cdot \color{blue}{{x}^{2}}\right)\right) \cdot x \]

    8. associate-*r* N/A

       \[\leadsto \left(\left(-1 \cdot x\right) \cdot \varepsilon + \left(\frac{-1}{2} \cdot \varepsilon\right) \cdot \varepsilon\right) + \left(\frac{1}{6} \cdot \color{blue}{\left(\varepsilon \cdot {x}^{2}\right)}\right) \cdot x \]

    9. distribute-rgt-in N/A

       \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \color{blue}{\left(\frac{1}{6} \cdot \left(\varepsilon \cdot {x}^{2}\right)\right)} \cdot x \]

    10. associate-*r* N/A

        \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \left(\left(\frac{1}{6} \cdot \varepsilon\right) \cdot {x}^{2}\right) \cdot x \]

    11. associate-*r* N/A

        \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \left(\frac{1}{6} \cdot \varepsilon\right) \cdot \color{blue}{\left({x}^{2} \cdot x\right)} \]

    12. *-commutative N/A

        \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \left(\varepsilon \cdot \frac{1}{6}\right) \cdot \left(\color{blue}{{x}^{2}} \cdot x\right) \]

    13. unpow2 N/A

        \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \left(\varepsilon \cdot \frac{1}{6}\right) \cdot \left(\left(x \cdot x\right) \cdot x\right) \]

    14. unpow3 N/A

        \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \left(\varepsilon \cdot \frac{1}{6}\right) \cdot {x}^{\color{blue}{3}} \]

    15. associate-*l* N/A

        \[\leadsto \varepsilon \cdot \left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \varepsilon \cdot \color{blue}{\left(\frac{1}{6} \cdot {x}^{3}\right)} \]

    16. distribute-lft-out N/A

        \[\leadsto \varepsilon \cdot \color{blue}{\left(\left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right) + \frac{1}{6} \cdot {x}^{3}\right)} \]

11. Simplified 98.5%

    \[\leadsto \color{blue}{\varepsilon \cdot \left(\left(\varepsilon \cdot -0.5 - x\right) + x \cdot \left(x \cdot \left(x \cdot 0.16666666666666666\right)\right)\right)} \]
12. Add Preprocessing

Alternative 11: 54.0% accurate, 20.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -3.2 \cdot 10^{-143}:\\ \;\;\;\;\left(x \cdot x\right) \cdot 0.5\\ \mathbf{else}:\\ \;\;\;\;\varepsilon \cdot \left(\varepsilon \cdot -0.5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (if (<= x -3.2e-143) (* (* x x) 0.5) (* eps (* eps -0.5))))

C

double code(double x, double eps) {
	double tmp;
	if (x <= -3.2e-143) {
		tmp = (x * x) * 0.5;
	} else {
		tmp = eps * (eps * -0.5);
	}
	return tmp;
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    real(8) :: tmp
    if (x <= (-3.2d-143)) then
        tmp = (x * x) * 0.5d0
    else
        tmp = eps * (eps * (-0.5d0))
    end if
    code = tmp
end function

Java

public static double code(double x, double eps) {
	double tmp;
	if (x <= -3.2e-143) {
		tmp = (x * x) * 0.5;
	} else {
		tmp = eps * (eps * -0.5);
	}
	return tmp;
}

Python

def code(x, eps):
	tmp = 0
	if x <= -3.2e-143:
		tmp = (x * x) * 0.5
	else:
		tmp = eps * (eps * -0.5)
	return tmp

Julia

function code(x, eps)
	tmp = 0.0
	if (x <= -3.2e-143)
		tmp = Float64(Float64(x * x) * 0.5);
	else
		tmp = Float64(eps * Float64(eps * -0.5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, eps)
	tmp = 0.0;
	if (x <= -3.2e-143)
		tmp = (x * x) * 0.5;
	else
		tmp = eps * (eps * -0.5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, eps_] := If[LessEqual[x, -3.2e-143], N[(N[(x * x), $MachinePrecision] * 0.5), $MachinePrecision], N[(eps * N[(eps * -0.5), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < -3.1999999999999998e-143

   1. Initial program 6.1%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \color{blue}{\left(1 + \frac{-1}{2} \cdot {x}^{2}\right)}\right) \]
   4. Step-by-step derivation

      1. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \color{blue}{\left(\frac{-1}{2} \cdot {x}^{2}\right)}\right)\right) \]

      2. unpow2 N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \left(\frac{-1}{2} \cdot \left(x \cdot \color{blue}{x}\right)\right)\right)\right) \]

      3. associate-*r* N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \left(\left(\frac{-1}{2} \cdot x\right) \cdot \color{blue}{x}\right)\right)\right) \]

      4. *-commutative N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \left(x \cdot \color{blue}{\left(\frac{-1}{2} \cdot x\right)}\right)\right)\right) \]

      5. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{-1}{2} \cdot x\right)}\right)\right)\right) \]

      6. *-commutative N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \left(x \cdot \color{blue}{\frac{-1}{2}}\right)\right)\right)\right) \]

      7. *-lowering-*.f64 5.4%

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \color{blue}{\frac{-1}{2}}\right)\right)\right)\right) \]

   5. Simplified 5.4%

      \[\leadsto \cos \left(x + \varepsilon\right) - \color{blue}{\left(1 + x \cdot \left(x \cdot -0.5\right)\right)} \]

   6. Taylor expanded in x around inf

      \[\leadsto \color{blue}{\frac{1}{2} \cdot {x}^{2}} \]
   7. Step-by-step derivation

      1. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\frac{1}{2}, \color{blue}{\left({x}^{2}\right)}\right) \]

      2. unpow2 N/A

         \[\leadsto \mathsf{*.f64}\left(\frac{1}{2}, \left(x \cdot \color{blue}{x}\right)\right) \]

      3. *-lowering-*.f64 11.9%

         \[\leadsto \mathsf{*.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(x, \color{blue}{x}\right)\right) \]

   8. Simplified 11.9%

      \[\leadsto \color{blue}{0.5 \cdot \left(x \cdot x\right)} \]

   if -3.1999999999999998e-143 < x

   1. Initial program 66.7%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\cos \varepsilon - 1} \]
   4. Step-by-step derivation

      1. sub-neg N/A

         \[\leadsto \cos \varepsilon + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)} \]

      2. metadata-eval N/A

         \[\leadsto \cos \varepsilon + -1 \]

      3. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{+.f64}\left(\cos \varepsilon, \color{blue}{-1}\right) \]

      4. cos-lowering-cos.f64 66.3%

         \[\leadsto \mathsf{+.f64}\left(\mathsf{cos.f64}\left(\varepsilon\right), -1\right) \]

   5. Simplified 66.3%

      \[\leadsto \color{blue}{\cos \varepsilon + -1} \]

   6. Taylor expanded in eps around 0

      \[\leadsto \color{blue}{\frac{-1}{2} \cdot {\varepsilon}^{2}} \]
   7. Step-by-step derivation

      1. *-commutative N/A

         \[\leadsto {\varepsilon}^{2} \cdot \color{blue}{\frac{-1}{2}} \]

      2. unpow2 N/A

         \[\leadsto \left(\varepsilon \cdot \varepsilon\right) \cdot \frac{-1}{2} \]

      3. associate-*l* N/A

         \[\leadsto \varepsilon \cdot \color{blue}{\left(\varepsilon \cdot \frac{-1}{2}\right)} \]

      4. *-commutative N/A

         \[\leadsto \varepsilon \cdot \left(\frac{-1}{2} \cdot \color{blue}{\varepsilon}\right) \]

      5. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \varepsilon\right)}\right) \]

      6. *-commutative N/A

         \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \color{blue}{\frac{-1}{2}}\right)\right) \]

      7. *-lowering-*.f64 68.2%

         \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \color{blue}{\frac{-1}{2}}\right)\right) \]

   8. Simplified 68.2%

      \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot -0.5\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 52.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -3.2 \cdot 10^{-143}:\\ \;\;\;\;\left(x \cdot x\right) \cdot 0.5\\ \mathbf{else}:\\ \;\;\;\;\varepsilon \cdot \left(\varepsilon \cdot -0.5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 52.4% accurate, 20.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -3.2 \cdot 10^{-143}:\\ \;\;\;\;\left(x \cdot x\right) \cdot 0.5\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (if (<= x -3.2e-143) (* (* x x) 0.5) 0.0))

C

double code(double x, double eps) {
	double tmp;
	if (x <= -3.2e-143) {
		tmp = (x * x) * 0.5;
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    real(8) :: tmp
    if (x <= (-3.2d-143)) then
        tmp = (x * x) * 0.5d0
    else
        tmp = 0.0d0
    end if
    code = tmp
end function

Java

public static double code(double x, double eps) {
	double tmp;
	if (x <= -3.2e-143) {
		tmp = (x * x) * 0.5;
	} else {
		tmp = 0.0;
	}
	return tmp;
}

Python

def code(x, eps):
	tmp = 0
	if x <= -3.2e-143:
		tmp = (x * x) * 0.5
	else:
		tmp = 0.0
	return tmp

Julia

function code(x, eps)
	tmp = 0.0
	if (x <= -3.2e-143)
		tmp = Float64(Float64(x * x) * 0.5);
	else
		tmp = 0.0;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, eps)
	tmp = 0.0;
	if (x <= -3.2e-143)
		tmp = (x * x) * 0.5;
	else
		tmp = 0.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, eps_] := If[LessEqual[x, -3.2e-143], N[(N[(x * x), $MachinePrecision] * 0.5), $MachinePrecision], 0.0]

Derivation

1. Split input into 2 regimes

2. if x < -3.1999999999999998e-143

   1. Initial program 6.1%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \color{blue}{\left(1 + \frac{-1}{2} \cdot {x}^{2}\right)}\right) \]
   4. Step-by-step derivation

      1. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \color{blue}{\left(\frac{-1}{2} \cdot {x}^{2}\right)}\right)\right) \]

      2. unpow2 N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \left(\frac{-1}{2} \cdot \left(x \cdot \color{blue}{x}\right)\right)\right)\right) \]

      3. associate-*r* N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \left(\left(\frac{-1}{2} \cdot x\right) \cdot \color{blue}{x}\right)\right)\right) \]

      4. *-commutative N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \left(x \cdot \color{blue}{\left(\frac{-1}{2} \cdot x\right)}\right)\right)\right) \]

      5. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \color{blue}{\left(\frac{-1}{2} \cdot x\right)}\right)\right)\right) \]

      6. *-commutative N/A

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \left(x \cdot \color{blue}{\frac{-1}{2}}\right)\right)\right)\right) \]

      7. *-lowering-*.f64 5.4%

         \[\leadsto \mathsf{\_.f64}\left(\mathsf{cos.f64}\left(\mathsf{+.f64}\left(x, \varepsilon\right)\right), \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \color{blue}{\frac{-1}{2}}\right)\right)\right)\right) \]

   5. Simplified 5.4%

      \[\leadsto \cos \left(x + \varepsilon\right) - \color{blue}{\left(1 + x \cdot \left(x \cdot -0.5\right)\right)} \]

   6. Taylor expanded in x around inf

      \[\leadsto \color{blue}{\frac{1}{2} \cdot {x}^{2}} \]
   7. Step-by-step derivation

      1. *-lowering-*.f64 N/A

         \[\leadsto \mathsf{*.f64}\left(\frac{1}{2}, \color{blue}{\left({x}^{2}\right)}\right) \]

      2. unpow2 N/A

         \[\leadsto \mathsf{*.f64}\left(\frac{1}{2}, \left(x \cdot \color{blue}{x}\right)\right) \]

      3. *-lowering-*.f64 11.9%

         \[\leadsto \mathsf{*.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(x, \color{blue}{x}\right)\right) \]

   8. Simplified 11.9%

      \[\leadsto \color{blue}{0.5 \cdot \left(x \cdot x\right)} \]

   if -3.1999999999999998e-143 < x

   1. Initial program 66.7%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
   2. Add Preprocessing

   3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\cos \varepsilon - 1} \]
   4. Step-by-step derivation

      1. sub-neg N/A

         \[\leadsto \cos \varepsilon + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)} \]

      2. metadata-eval N/A

         \[\leadsto \cos \varepsilon + -1 \]

      3. +-lowering-+.f64 N/A

         \[\leadsto \mathsf{+.f64}\left(\cos \varepsilon, \color{blue}{-1}\right) \]

      4. cos-lowering-cos.f64 66.3%

         \[\leadsto \mathsf{+.f64}\left(\mathsf{cos.f64}\left(\varepsilon\right), -1\right) \]

   5. Simplified 66.3%

      \[\leadsto \color{blue}{\cos \varepsilon + -1} \]

   6. Taylor expanded in eps around 0

      \[\leadsto \mathsf{+.f64}\left(\color{blue}{1}, -1\right) \]
   7. Step-by-step derivation

   8. Simplified 66.3%

      \[\leadsto \color{blue}{1} + -1 \]
   9. Step-by-step derivation

      1. metadata-eval 66.3%

         \[\leadsto 0 \]

   10. Applied egg-rr 66.3%

       \[\leadsto \color{blue}{0} \]
3. Recombined 2 regimes into one program.

4. Final simplification 50.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -3.2 \cdot 10^{-143}:\\ \;\;\;\;\left(x \cdot x\right) \cdot 0.5\\ \mathbf{else}:\\ \;\;\;\;0\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 97.8% accurate, 22.8× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5\right) - x \cdot \varepsilon \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (- (* eps (* eps -0.5)) (* x eps)))

C

double code(double x, double eps) {
	return (eps * (eps * -0.5)) - (x * eps);
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = (eps * (eps * (-0.5d0))) - (x * eps)
end function

Java

public static double code(double x, double eps) {
	return (eps * (eps * -0.5)) - (x * eps);
}

Python

def code(x, eps):
	return (eps * (eps * -0.5)) - (x * eps)

Julia

function code(x, eps)
	return Float64(Float64(eps * Float64(eps * -0.5)) - Float64(x * eps))
end

MATLAB

function tmp = code(x, eps)
	tmp = (eps * (eps * -0.5)) - (x * eps);
end

Wolfram

code[x_, eps_] := N[(N[(eps * N[(eps * -0.5), $MachinePrecision]), $MachinePrecision] - N[(x * eps), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \color{blue}{-1 \cdot \left(\varepsilon \cdot x\right) + \frac{-1}{2} \cdot {\varepsilon}^{2}} \]
7. Step-by-step derivation

   1. associate-*r* N/A

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

   2. mul-1-neg N/A

      \[\leadsto \left(\mathsf{neg}\left(\varepsilon\right)\right) \cdot x + \frac{-1}{2} \cdot {\varepsilon}^{2} \]

   3. +-commutative N/A

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

   4. cancel-sign-sub-inv N/A

      \[\leadsto \frac{-1}{2} \cdot {\varepsilon}^{2} - \color{blue}{\varepsilon \cdot x} \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{\_.f64}\left(\left(\frac{-1}{2} \cdot {\varepsilon}^{2}\right), \color{blue}{\left(\varepsilon \cdot x\right)}\right) \]

   6. *-commutative N/A

      \[\leadsto \mathsf{\_.f64}\left(\left({\varepsilon}^{2} \cdot \frac{-1}{2}\right), \left(\color{blue}{\varepsilon} \cdot x\right)\right) \]

   7. unpow2 N/A

      \[\leadsto \mathsf{\_.f64}\left(\left(\left(\varepsilon \cdot \varepsilon\right) \cdot \frac{-1}{2}\right), \left(\varepsilon \cdot x\right)\right) \]

   8. associate-*l* N/A

      \[\leadsto \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\varepsilon \cdot \frac{-1}{2}\right)\right), \left(\color{blue}{\varepsilon} \cdot x\right)\right) \]

   9. *-commutative N/A

      \[\leadsto \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \varepsilon\right)\right), \left(\varepsilon \cdot x\right)\right) \]

   10. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \varepsilon\right)\right), \left(\color{blue}{\varepsilon} \cdot x\right)\right) \]

   11. *-commutative N/A

       \[\leadsto \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \frac{-1}{2}\right)\right), \left(\varepsilon \cdot x\right)\right) \]

   12. *-lowering-*.f64 N/A

       \[\leadsto \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right)\right), \left(\varepsilon \cdot x\right)\right) \]

   13. *-lowering-*.f64 98.4%

       \[\leadsto \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right)\right), \mathsf{*.f64}\left(\varepsilon, \color{blue}{x}\right)\right) \]

8. Simplified 98.4%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot -0.5\right) - \varepsilon \cdot x} \]

9. Final simplification 98.4%

   \[\leadsto \varepsilon \cdot \left(\varepsilon \cdot -0.5\right) - x \cdot \varepsilon \]
10. Add Preprocessing

Alternative 14: 97.8% accurate, 29.3× speedup

Math

\[\begin{array}{l} \\ \varepsilon \cdot \left(\varepsilon \cdot -0.5 - x\right) \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (* eps (- (* eps -0.5) x)))

C

double code(double x, double eps) {
	return eps * ((eps * -0.5) - x);
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = eps * ((eps * (-0.5d0)) - x)
end function

Java

public static double code(double x, double eps) {
	return eps * ((eps * -0.5) - x);
}

Python

def code(x, eps):
	return eps * ((eps * -0.5) - x)

Julia

function code(x, eps)
	return Float64(eps * Float64(Float64(eps * -0.5) - x))
end

MATLAB

function tmp = code(x, eps)
	tmp = eps * ((eps * -0.5) - x);
end

Wolfram

code[x_, eps_] := N[(eps * N[(N[(eps * -0.5), $MachinePrecision] - x), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)} \]
4. Step-by-step derivation

   1. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(\frac{-1}{2} \cdot \left(\varepsilon \cdot \cos x\right) - \sin x\right)}\right) \]

   2. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\left(\varepsilon \cdot \cos x\right) \cdot \frac{-1}{2} - \sin \color{blue}{x}\right)\right) \]

   3. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\cos x \cdot \frac{-1}{2}\right) - \sin \color{blue}{x}\right)\right) \]

   4. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right) - \sin x\right)\right) \]

   5. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \left(\frac{-1}{2} \cdot \cos x\right)\right), \color{blue}{\sin x}\right)\right) \]

   6. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \cos x\right)\right), \sin \color{blue}{x}\right)\right) \]

   7. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \cos x\right)\right), \sin x\right)\right) \]

   8. cos-lowering-cos.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \sin x\right)\right) \]

   9. sin-lowering-sin.f64 99.6%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{*.f64}\left(\frac{-1}{2}, \mathsf{cos.f64}\left(x\right)\right)\right), \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 99.6%

   \[\leadsto \color{blue}{\varepsilon \cdot \left(\varepsilon \cdot \left(-0.5 \cdot \cos x\right) - \sin x\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\varepsilon, \color{blue}{\left(-1 \cdot x + \frac{-1}{2} \cdot \varepsilon\right)}\right) \]
7. Step-by-step derivation

   1. +-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \varepsilon + \color{blue}{-1 \cdot x}\right)\right) \]

   2. mul-1-neg N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \varepsilon + \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]

   3. unsub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \left(\frac{-1}{2} \cdot \varepsilon - \color{blue}{x}\right)\right) \]

   4. --lowering--.f64 N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\frac{-1}{2} \cdot \varepsilon\right), \color{blue}{x}\right)\right) \]

   5. *-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\left(\varepsilon \cdot \frac{-1}{2}\right), x\right)\right) \]

   6. *-lowering-*.f64 98.4%

      \[\leadsto \mathsf{*.f64}\left(\varepsilon, \mathsf{\_.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{-1}{2}\right), x\right)\right) \]

8. Simplified 98.4%

   \[\leadsto \varepsilon \cdot \color{blue}{\left(\varepsilon \cdot -0.5 - x\right)} \]
9. Add Preprocessing

Alternative 15: 78.8% accurate, 41.0× speedup

Math

\[\begin{array}{l} \\ x \cdot \left(0 - \varepsilon\right) \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (* x (- 0.0 eps)))

C

double code(double x, double eps) {
	return x * (0.0 - eps);
}

Fortran

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

Java

public static double code(double x, double eps) {
	return x * (0.0 - eps);
}

Python

def code(x, eps):
	return x * (0.0 - eps)

Julia

function code(x, eps)
	return Float64(x * Float64(0.0 - eps))
end

MATLAB

function tmp = code(x, eps)
	tmp = x * (0.0 - eps);
end

Wolfram

code[x_, eps_] := N[(x * N[(0.0 - eps), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in eps around 0

   \[\leadsto \color{blue}{-1 \cdot \left(\varepsilon \cdot \sin x\right)} \]
4. Step-by-step derivation

   1. mul-1-neg N/A

      \[\leadsto \mathsf{neg}\left(\varepsilon \cdot \sin x\right) \]

   2. neg-sub0 N/A

      \[\leadsto 0 - \color{blue}{\varepsilon \cdot \sin x} \]

   3. --lowering--.f64 N/A

      \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{\left(\varepsilon \cdot \sin x\right)}\right) \]

   4. *-lowering-*.f64 N/A

      \[\leadsto \mathsf{\_.f64}\left(0, \mathsf{*.f64}\left(\varepsilon, \color{blue}{\sin x}\right)\right) \]

   5. sin-lowering-sin.f64 79.2%

      \[\leadsto \mathsf{\_.f64}\left(0, \mathsf{*.f64}\left(\varepsilon, \mathsf{sin.f64}\left(x\right)\right)\right) \]

5. Simplified 79.2%

   \[\leadsto \color{blue}{0 - \varepsilon \cdot \sin x} \]

6. Taylor expanded in x around 0

   \[\leadsto \color{blue}{-1 \cdot \left(\varepsilon \cdot x\right)} \]
7. Step-by-step derivation

   1. mul-1-neg N/A

      \[\leadsto \mathsf{neg}\left(\varepsilon \cdot x\right) \]

   2. neg-sub0 N/A

      \[\leadsto 0 - \color{blue}{\varepsilon \cdot x} \]

   3. --lowering--.f64 N/A

      \[\leadsto \mathsf{\_.f64}\left(0, \color{blue}{\left(\varepsilon \cdot x\right)}\right) \]

   4. *-lowering-*.f64 78.3%

      \[\leadsto \mathsf{\_.f64}\left(0, \mathsf{*.f64}\left(\varepsilon, \color{blue}{x}\right)\right) \]

8. Simplified 78.3%

   \[\leadsto \color{blue}{0 - \varepsilon \cdot x} \]

9. Final simplification 78.3%

   \[\leadsto x \cdot \left(0 - \varepsilon\right) \]
10. Add Preprocessing

Alternative 16: 50.7% accurate, 205.0× speedup

Math

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

FPCore

(FPCore (x eps) :precision binary64 0.0)

C

double code(double x, double eps) {
	return 0.0;
}

Fortran

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

Java

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

Python

def code(x, eps):
	return 0.0

Julia

function code(x, eps)
	return 0.0
end

MATLAB

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

Wolfram

code[x_, eps_] := 0.0

Derivation

1. Initial program 49.4%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing

3. Taylor expanded in x around 0

   \[\leadsto \color{blue}{\cos \varepsilon - 1} \]
4. Step-by-step derivation

   1. sub-neg N/A

      \[\leadsto \cos \varepsilon + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)} \]

   2. metadata-eval N/A

      \[\leadsto \cos \varepsilon + -1 \]

   3. +-lowering-+.f64 N/A

      \[\leadsto \mathsf{+.f64}\left(\cos \varepsilon, \color{blue}{-1}\right) \]

   4. cos-lowering-cos.f64 48.8%

      \[\leadsto \mathsf{+.f64}\left(\mathsf{cos.f64}\left(\varepsilon\right), -1\right) \]

5. Simplified 48.8%

   \[\leadsto \color{blue}{\cos \varepsilon + -1} \]

6. Taylor expanded in eps around 0

   \[\leadsto \mathsf{+.f64}\left(\color{blue}{1}, -1\right) \]
7. Step-by-step derivation

8. Simplified 48.8%

   \[\leadsto \color{blue}{1} + -1 \]
9. Step-by-step derivation

   1. metadata-eval 48.8%

      \[\leadsto 0 \]

10. Applied egg-rr 48.8%

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

Developer Target 1: 99.7% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(-2 \cdot \sin \left(x + \frac{\varepsilon}{2}\right)\right) \cdot \sin \left(\frac{\varepsilon}{2}\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (* (* -2.0 (sin (+ x (/ eps 2.0)))) (sin (/ eps 2.0))))

C

double code(double x, double eps) {
	return (-2.0 * sin((x + (eps / 2.0)))) * sin((eps / 2.0));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = ((-2.0d0) * sin((x + (eps / 2.0d0)))) * sin((eps / 2.0d0))
end function

Java

public static double code(double x, double eps) {
	return (-2.0 * Math.sin((x + (eps / 2.0)))) * Math.sin((eps / 2.0));
}

Python

def code(x, eps):
	return (-2.0 * math.sin((x + (eps / 2.0)))) * math.sin((eps / 2.0))

Julia

function code(x, eps)
	return Float64(Float64(-2.0 * sin(Float64(x + Float64(eps / 2.0)))) * sin(Float64(eps / 2.0)))
end

MATLAB

function tmp = code(x, eps)
	tmp = (-2.0 * sin((x + (eps / 2.0)))) * sin((eps / 2.0));
end

Wolfram

code[x_, eps_] := N[(N[(-2.0 * N[Sin[N[(x + N[(eps / 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(eps / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

Reproduce

herbie shell --seed 2024161 
(FPCore (x eps)
  :name "2cos (problem 3.3.5)"
  :precision binary64
  :pre (and (and (and (<= -10000.0 x) (<= x 10000.0)) (< (* 1e-16 (fabs x)) eps)) (< eps (fabs x)))

  :alt
  (! :herbie-platform default (* -2 (sin (+ x (/ eps 2))) (sin (/ eps 2))))

  (- (cos (+ x eps)) (cos x)))