2cos (problem 3.3.5)

Percentage Accurate: 51.7% → 99.6%

Time: 17.8s

Alternatives: 10

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: 51.7% 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: 99.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\\ \left(\left(\sin x \cdot \cos \left(\varepsilon \cdot 0.5\right)\right) \cdot t\_0 + t\_0 \cdot \left(\cos x \cdot \sin \left(\varepsilon \cdot 0.5\right)\right)\right) \cdot -2 \end{array} \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (let* ((t_0 (* eps (+ 0.5 (* -0.020833333333333332 (* eps eps))))))
   (*
    (+
     (* (* (sin x) (cos (* eps 0.5))) t_0)
     (* t_0 (* (cos x) (sin (* eps 0.5)))))
    -2.0)))

C

double code(double x, double eps) {
	double t_0 = eps * (0.5 + (-0.020833333333333332 * (eps * eps)));
	return (((sin(x) * cos((eps * 0.5))) * t_0) + (t_0 * (cos(x) * sin((eps * 0.5))))) * -2.0;
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    real(8) :: t_0
    t_0 = eps * (0.5d0 + ((-0.020833333333333332d0) * (eps * eps)))
    code = (((sin(x) * cos((eps * 0.5d0))) * t_0) + (t_0 * (cos(x) * sin((eps * 0.5d0))))) * (-2.0d0)
end function

Java

public static double code(double x, double eps) {
	double t_0 = eps * (0.5 + (-0.020833333333333332 * (eps * eps)));
	return (((Math.sin(x) * Math.cos((eps * 0.5))) * t_0) + (t_0 * (Math.cos(x) * Math.sin((eps * 0.5))))) * -2.0;
}

Python

def code(x, eps):
	t_0 = eps * (0.5 + (-0.020833333333333332 * (eps * eps)))
	return (((math.sin(x) * math.cos((eps * 0.5))) * t_0) + (t_0 * (math.cos(x) * math.sin((eps * 0.5))))) * -2.0

Julia

function code(x, eps)
	t_0 = Float64(eps * Float64(0.5 + Float64(-0.020833333333333332 * Float64(eps * eps))))
	return Float64(Float64(Float64(Float64(sin(x) * cos(Float64(eps * 0.5))) * t_0) + Float64(t_0 * Float64(cos(x) * sin(Float64(eps * 0.5))))) * -2.0)
end

MATLAB

function tmp = code(x, eps)
	t_0 = eps * (0.5 + (-0.020833333333333332 * (eps * eps)));
	tmp = (((sin(x) * cos((eps * 0.5))) * t_0) + (t_0 * (cos(x) * sin((eps * 0.5))))) * -2.0;
end

Wolfram

code[x_, eps_] := Block[{t$95$0 = N[(eps * N[(0.5 + N[(-0.020833333333333332 * N[(eps * eps), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[(N[(N[Sin[x], $MachinePrecision] * N[Cos[N[(eps * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + N[(t$95$0 * N[(N[Cos[x], $MachinePrecision] * N[Sin[N[(eps * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * -2.0), $MachinePrecision]]

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing
3. Step-by-step derivation

   1. diff-cos N/A

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

   2. *-commutative N/A

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

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

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

4. Applied egg-rr 99.7%

   \[\leadsto \color{blue}{\left(\sin \left(\frac{\varepsilon + 0}{2}\right) \cdot \sin \left(\frac{\varepsilon + x \cdot 2}{2}\right)\right) \cdot -2} \]

5. Taylor expanded in eps around 0

   \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\color{blue}{\left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot {\varepsilon}^{2}\right)\right)}, \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]
6. Step-by-step derivation

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{1}{2} + \frac{-1}{48} \cdot {\varepsilon}^{2}\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \left(\frac{-1}{48} \cdot {\varepsilon}^{2}\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \left({\varepsilon}^{2}\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

   4. unpow2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

   5. *-lowering-*.f64 99.7%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

7. Simplified 99.7%

   \[\leadsto \left(\color{blue}{\left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)} \cdot \sin \left(\frac{\varepsilon + x \cdot 2}{2}\right)\right) \cdot -2 \]

8. Taylor expanded in eps around inf

   \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \color{blue}{\sin \left(\frac{1}{2} \cdot \left(\varepsilon + 2 \cdot x\right)\right)}\right), -2\right) \]
9. Step-by-step derivation

   1. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \sin \left(\frac{1}{2} \cdot \left(\varepsilon + \left(\mathsf{neg}\left(-2\right)\right) \cdot x\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \sin \left(\frac{1}{2} \cdot \left(\varepsilon - -2 \cdot x\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(\varepsilon - -2 \cdot x\right)\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(\varepsilon + \left(\mathsf{neg}\left(-2\right)\right) \cdot x\right)\right)\right)\right), -2\right) \]

   5. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(\varepsilon + 2 \cdot x\right)\right)\right)\right), -2\right) \]

   6. +-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(2 \cdot x + \varepsilon\right)\right)\right)\right), -2\right) \]

   7. distribute-lft-in N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(2 \cdot x\right) + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

   8. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\left(\frac{1}{2} \cdot 2\right) \cdot x + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

   9. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(1 \cdot x + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

   10. *-lft-identity N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(x + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{+.f64}\left(x, \left(\frac{1}{2} \cdot \varepsilon\right)\right)\right)\right), -2\right) \]

   12. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{+.f64}\left(x, \left(\varepsilon \cdot \frac{1}{2}\right)\right)\right)\right), -2\right) \]

   13. *-lowering-*.f64 99.7%

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{+.f64}\left(x, \mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right)\right), -2\right) \]

10. Simplified 99.7%

    \[\leadsto \left(\left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) \cdot \color{blue}{\sin \left(x + \varepsilon \cdot 0.5\right)}\right) \cdot -2 \]
11. Step-by-step derivation

    1. sin-sum N/A

       \[\leadsto \mathsf{*.f64}\left(\left(\left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) \cdot \left(\sin x \cdot \cos \left(\varepsilon \cdot \frac{1}{2}\right) + \cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right)\right), -2\right) \]

    2. distribute-rgt-in N/A

       \[\leadsto \mathsf{*.f64}\left(\left(\left(\sin x \cdot \cos \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) + \left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\left(\left(\sin x \cdot \cos \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\left(\sin x \cdot \cos \left(\varepsilon \cdot \frac{1}{2}\right)\right), \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\sin x, \cos \left(\varepsilon \cdot \frac{1}{2}\right)\right), \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \cos \left(\varepsilon \cdot \frac{1}{2}\right)\right), \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\left(\varepsilon \cdot \frac{1}{2}\right)\right)\right), \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right), \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right), \mathsf{*.f64}\left(\varepsilon, \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

        \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right), \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \left(\frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

        \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right), \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

        \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right), \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right)\right), \left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right) \cdot \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

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

        \[\leadsto \mathsf{*.f64}\left(\mathsf{+.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{sin.f64}\left(x\right), \mathsf{cos.f64}\left(\mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right), \mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right)\right), \mathsf{*.f64}\left(\left(\cos x \cdot \sin \left(\varepsilon \cdot \frac{1}{2}\right)\right), \left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)\right), -2\right) \]

12. Applied egg-rr 99.8%

    \[\leadsto \color{blue}{\left(\left(\sin x \cdot \cos \left(\varepsilon \cdot 0.5\right)\right) \cdot \left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) + \left(\cos x \cdot \sin \left(\varepsilon \cdot 0.5\right)\right) \cdot \left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right)} \cdot -2 \]

13. Final simplification 99.8%

    \[\leadsto \left(\left(\sin x \cdot \cos \left(\varepsilon \cdot 0.5\right)\right) \cdot \left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) + \left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) \cdot \left(\cos x \cdot \sin \left(\varepsilon \cdot 0.5\right)\right)\right) \cdot -2 \]
14. Add Preprocessing

Alternative 2: 99.5% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ -2 \cdot \left(\left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) \cdot \sin \left(x + \varepsilon \cdot 0.5\right)\right) \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (*
  -2.0
  (*
   (* eps (+ 0.5 (* -0.020833333333333332 (* eps eps))))
   (sin (+ x (* eps 0.5))))))

C

double code(double x, double eps) {
	return -2.0 * ((eps * (0.5 + (-0.020833333333333332 * (eps * eps)))) * sin((x + (eps * 0.5))));
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = (-2.0d0) * ((eps * (0.5d0 + ((-0.020833333333333332d0) * (eps * eps)))) * sin((x + (eps * 0.5d0))))
end function

Java

public static double code(double x, double eps) {
	return -2.0 * ((eps * (0.5 + (-0.020833333333333332 * (eps * eps)))) * Math.sin((x + (eps * 0.5))));
}

Python

def code(x, eps):
	return -2.0 * ((eps * (0.5 + (-0.020833333333333332 * (eps * eps)))) * math.sin((x + (eps * 0.5))))

Julia

function code(x, eps)
	return Float64(-2.0 * Float64(Float64(eps * Float64(0.5 + Float64(-0.020833333333333332 * Float64(eps * eps)))) * sin(Float64(x + Float64(eps * 0.5)))))
end

MATLAB

function tmp = code(x, eps)
	tmp = -2.0 * ((eps * (0.5 + (-0.020833333333333332 * (eps * eps)))) * sin((x + (eps * 0.5))));
end

Wolfram

code[x_, eps_] := N[(-2.0 * N[(N[(eps * N[(0.5 + N[(-0.020833333333333332 * N[(eps * eps), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sin[N[(x + N[(eps * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing
3. Step-by-step derivation

   1. diff-cos N/A

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

   2. *-commutative N/A

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

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

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

4. Applied egg-rr 99.7%

   \[\leadsto \color{blue}{\left(\sin \left(\frac{\varepsilon + 0}{2}\right) \cdot \sin \left(\frac{\varepsilon + x \cdot 2}{2}\right)\right) \cdot -2} \]

5. Taylor expanded in eps around 0

   \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\color{blue}{\left(\varepsilon \cdot \left(\frac{1}{2} + \frac{-1}{48} \cdot {\varepsilon}^{2}\right)\right)}, \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]
6. Step-by-step derivation

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \left(\frac{1}{2} + \frac{-1}{48} \cdot {\varepsilon}^{2}\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \left(\frac{-1}{48} \cdot {\varepsilon}^{2}\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \left({\varepsilon}^{2}\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

   4. unpow2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \left(\varepsilon \cdot \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

   5. *-lowering-*.f64 99.7%

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(\varepsilon, \mathsf{*.f64}\left(x, 2\right)\right), 2\right)\right)\right), -2\right) \]

7. Simplified 99.7%

   \[\leadsto \left(\color{blue}{\left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right)} \cdot \sin \left(\frac{\varepsilon + x \cdot 2}{2}\right)\right) \cdot -2 \]

8. Taylor expanded in eps around inf

   \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \color{blue}{\sin \left(\frac{1}{2} \cdot \left(\varepsilon + 2 \cdot x\right)\right)}\right), -2\right) \]
9. Step-by-step derivation

   1. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \sin \left(\frac{1}{2} \cdot \left(\varepsilon + \left(\mathsf{neg}\left(-2\right)\right) \cdot x\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \sin \left(\frac{1}{2} \cdot \left(\varepsilon - -2 \cdot x\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(\varepsilon - -2 \cdot x\right)\right)\right)\right), -2\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(\varepsilon + \left(\mathsf{neg}\left(-2\right)\right) \cdot x\right)\right)\right)\right), -2\right) \]

   5. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(\varepsilon + 2 \cdot x\right)\right)\right)\right), -2\right) \]

   6. +-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(2 \cdot x + \varepsilon\right)\right)\right)\right), -2\right) \]

   7. distribute-lft-in N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\frac{1}{2} \cdot \left(2 \cdot x\right) + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

   8. associate-*r* N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(\left(\frac{1}{2} \cdot 2\right) \cdot x + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

   9. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(1 \cdot x + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

   10. *-lft-identity N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\left(x + \frac{1}{2} \cdot \varepsilon\right)\right)\right), -2\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{+.f64}\left(x, \left(\frac{1}{2} \cdot \varepsilon\right)\right)\right)\right), -2\right) \]

   12. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{+.f64}\left(x, \left(\varepsilon \cdot \frac{1}{2}\right)\right)\right)\right), -2\right) \]

   13. *-lowering-*.f64 99.7%

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(\mathsf{*.f64}\left(\varepsilon, \mathsf{+.f64}\left(\frac{1}{2}, \mathsf{*.f64}\left(\frac{-1}{48}, \mathsf{*.f64}\left(\varepsilon, \varepsilon\right)\right)\right)\right), \mathsf{sin.f64}\left(\mathsf{+.f64}\left(x, \mathsf{*.f64}\left(\varepsilon, \frac{1}{2}\right)\right)\right)\right), -2\right) \]

10. Simplified 99.7%

    \[\leadsto \left(\left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) \cdot \color{blue}{\sin \left(x + \varepsilon \cdot 0.5\right)}\right) \cdot -2 \]

11. Final simplification 99.7%

    \[\leadsto -2 \cdot \left(\left(\varepsilon \cdot \left(0.5 + -0.020833333333333332 \cdot \left(\varepsilon \cdot \varepsilon\right)\right)\right) \cdot \sin \left(x + \varepsilon \cdot 0.5\right)\right) \]
12. Add Preprocessing

Alternative 3: 99.3% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \sin \left(x + \varepsilon \cdot 0.5\right) \cdot \left(0 - \varepsilon\right) \end{array} \]

FPCore

(FPCore (x eps) :precision binary64 (* (sin (+ x (* eps 0.5))) (- 0.0 eps)))

C

double code(double x, double eps) {
	return sin((x + (eps * 0.5))) * (0.0 - eps);
}

Fortran

real(8) function code(x, eps)
    real(8), intent (in) :: x
    real(8), intent (in) :: eps
    code = sin((x + (eps * 0.5d0))) * (0.0d0 - eps)
end function

Java

public static double code(double x, double eps) {
	return Math.sin((x + (eps * 0.5))) * (0.0 - eps);
}

Python

def code(x, eps):
	return math.sin((x + (eps * 0.5))) * (0.0 - eps)

Julia

function code(x, eps)
	return Float64(sin(Float64(x + Float64(eps * 0.5))) * Float64(0.0 - eps))
end

MATLAB

function tmp = code(x, eps)
	tmp = sin((x + (eps * 0.5))) * (0.0 - eps);
end

Wolfram

code[x_, eps_] := N[(N[Sin[N[(x + N[(eps * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(0.0 - eps), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
2. Add Preprocessing
3. Step-by-step derivation

   1. diff-cos N/A

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

   2. *-commutative N/A

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

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

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

4. Applied egg-rr 99.7%

   \[\leadsto \color{blue}{\left(\sin \left(\frac{\varepsilon + 0}{2}\right) \cdot \sin \left(\frac{\varepsilon + x \cdot 2}{2}\right)\right) \cdot -2} \]

5. Taylor expanded in eps around 0

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

   1. *-commutative N/A

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

   2. *-lowering-*.f64 99.7%

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

7. Simplified 99.7%

   \[\leadsto \left(\color{blue}{\left(\varepsilon \cdot 0.5\right)} \cdot \sin \left(\frac{\varepsilon + x \cdot 2}{2}\right)\right) \cdot -2 \]

8. Taylor expanded in eps around inf

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

   1. mul-1-neg N/A

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

   2. *-commutative N/A

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

   3. metadata-eval N/A

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

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

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

   5. distribute-rgt-neg-in N/A

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

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

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

   7. metadata-eval N/A

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

   8. +-commutative N/A

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

   9. distribute-rgt-in N/A

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

   10. *-commutative N/A

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

   11. associate-*l* N/A

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

   12. metadata-eval N/A

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

   13. *-rgt-identity N/A

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

   14. *-commutative N/A

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

   15. mul-1-neg N/A

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

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

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

10. Simplified 99.7%

    \[\leadsto \color{blue}{\sin \left(x + \varepsilon \cdot 0.5\right) \cdot \left(0 - \varepsilon\right)} \]
11. Add Preprocessing

Alternative 4: 79.2% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ 0 - \sin x \cdot \varepsilon \end{array} \]

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
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. associate-*r* N/A

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

   2. *-commutative N/A

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

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

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

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

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

   5. mul-1-neg N/A

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

   6. neg-sub0 N/A

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

   7. --lowering--.f64 77.8%

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

5. Simplified 77.8%

   \[\leadsto \color{blue}{\sin x \cdot \left(0 - \varepsilon\right)} \]
6. Step-by-step derivation

   1. sub0-neg N/A

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

   2. neg-lowering-neg.f64 77.8%

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

7. Applied egg-rr 77.8%

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

8. Final simplification 77.8%

   \[\leadsto 0 - \sin x \cdot \varepsilon \]
9. Add Preprocessing

Alternative 5: 78.6% accurate, 8.9× speedup

Math

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

FPCore

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

C

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
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. associate-*r* N/A

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

   2. *-commutative N/A

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

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

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

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

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

   5. mul-1-neg N/A

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

   6. neg-sub0 N/A

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

   7. --lowering--.f64 77.8%

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

5. Simplified 77.8%

   \[\leadsto \color{blue}{\sin x \cdot \left(0 - \varepsilon\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\color{blue}{\left(x \cdot \left(1 + {x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)}, \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]
7. Step-by-step derivation

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \left(1 + {x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right), \mathsf{\_.f64}\left(\color{blue}{0}, \varepsilon\right)\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \left({x}^{2} \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   3. unpow2 N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \left(\left(x \cdot x\right) \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   4. associate-*l* N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \left(x \cdot \left(x \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \left(x \cdot \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) - \frac{1}{6}\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   7. sub-neg N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) + \left(\mathsf{neg}\left(\frac{1}{6}\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   8. metadata-eval N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right) + \frac{-1}{6}\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   9. +-commutative N/A

      \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \left(\frac{-1}{6} + {x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \left({x}^{2} \cdot \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\left({x}^{2}\right), \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   12. unpow2 N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\left(x \cdot x\right), \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(\frac{1}{120} + \frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{1}{120}, \left(\frac{-1}{5040} \cdot {x}^{2}\right)\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   15. *-commutative N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{1}{120}, \left({x}^{2} \cdot \frac{-1}{5040}\right)\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

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

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{1}{120}, \mathsf{*.f64}\left(\left({x}^{2}\right), \frac{-1}{5040}\right)\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   17. unpow2 N/A

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{1}{120}, \mathsf{*.f64}\left(\left(x \cdot x\right), \frac{-1}{5040}\right)\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

   18. *-lowering-*.f64 77.4%

       \[\leadsto \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, \mathsf{+.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(\frac{-1}{6}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{+.f64}\left(\frac{1}{120}, \mathsf{*.f64}\left(\mathsf{*.f64}\left(x, x\right), \frac{-1}{5040}\right)\right)\right)\right)\right)\right)\right)\right), \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]

8. Simplified 77.4%

   \[\leadsto \color{blue}{\left(x \cdot \left(1 + x \cdot \left(x \cdot \left(-0.16666666666666666 + \left(x \cdot x\right) \cdot \left(0.008333333333333333 + \left(x \cdot x\right) \cdot -0.0001984126984126984\right)\right)\right)\right)\right)} \cdot \left(0 - \varepsilon\right) \]

9. Final simplification 77.4%

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

Alternative 6: 78.5% accurate, 18.6× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
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. associate-*r* N/A

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

   2. *-commutative N/A

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

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

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

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

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

   5. mul-1-neg N/A

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

   6. neg-sub0 N/A

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

   7. --lowering--.f64 77.8%

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

5. Simplified 77.8%

   \[\leadsto \color{blue}{\sin x \cdot \left(0 - \varepsilon\right)} \]

6. Taylor expanded in x around 0

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

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

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

   2. *-commutative N/A

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

   3. *-commutative N/A

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

   4. associate-*l* N/A

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

   5. distribute-lft-out N/A

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

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

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

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

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

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

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

   9. unpow2 N/A

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

   10. *-lowering-*.f64 77.4%

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

8. Simplified 77.4%

   \[\leadsto \color{blue}{x \cdot \left(\varepsilon \cdot \left(-1 + \left(x \cdot x\right) \cdot 0.16666666666666666\right)\right)} \]
9. Add Preprocessing

Alternative 7: 53.8% accurate, 20.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -7 \cdot 10^{-142}:\\ \;\;\;\;x \cdot \left(x \cdot 0.5\right)\\ \mathbf{else}:\\ \;\;\;\;\varepsilon \cdot \left(\varepsilon \cdot -0.5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x eps)
 :precision binary64
 (if (<= x -7e-142) (* x (* x 0.5)) (* eps (* eps -0.5))))

C

double code(double x, double eps) {
	double tmp;
	if (x <= -7e-142) {
		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 <= (-7d-142)) 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 <= -7e-142) {
		tmp = x * (x * 0.5);
	} else {
		tmp = eps * (eps * -0.5);
	}
	return tmp;
}

Python

def code(x, eps):
	tmp = 0
	if x <= -7e-142:
		tmp = x * (x * 0.5)
	else:
		tmp = eps * (eps * -0.5)
	return tmp

Julia

function code(x, eps)
	tmp = 0.0
	if (x <= -7e-142)
		tmp = Float64(x * Float64(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 <= -7e-142)
		tmp = x * (x * 0.5);
	else
		tmp = eps * (eps * -0.5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, eps_] := If[LessEqual[x, -7e-142], N[(x * N[(x * 0.5), $MachinePrecision]), $MachinePrecision], N[(eps * N[(eps * -0.5), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if x < -7.00000000000000029e-142

   1. Initial program 6.7%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
   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 5.7%

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

   5. Simplified 5.7%

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

   6. Taylor expanded in x around inf

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

      1. *-commutative N/A

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

      2. unpow2 N/A

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

      3. associate-*l* N/A

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

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

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

      5. *-lowering-*.f64 12.4%

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

   8. Simplified 12.4%

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

   if -7.00000000000000029e-142 < x

   1. Initial program 63.5%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
   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 63.2%

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

   5. Simplified 63.2%

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

   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 65.5%

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

   8. Simplified 65.5%

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

Alternative 8: 78.3% accurate, 41.0× speedup

Math

\[\begin{array}{l} \\ 0 - x \cdot \varepsilon \end{array} \]

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
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. associate-*r* N/A

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

   2. *-commutative N/A

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

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

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

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

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

   5. mul-1-neg N/A

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

   6. neg-sub0 N/A

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

   7. --lowering--.f64 77.8%

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

5. Simplified 77.8%

   \[\leadsto \color{blue}{\sin x \cdot \left(0 - \varepsilon\right)} \]

6. Taylor expanded in x around 0

   \[\leadsto \mathsf{*.f64}\left(\color{blue}{x}, \mathsf{\_.f64}\left(0, \varepsilon\right)\right) \]
7. Step-by-step derivation

8. Simplified 77.1%

   \[\leadsto \color{blue}{x} \cdot \left(0 - \varepsilon\right) \]

9. Final simplification 77.1%

   \[\leadsto 0 - x \cdot \varepsilon \]
10. Add Preprocessing

Alternative 9: 51.6% accurate, 41.0× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

1. Initial program 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
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 47.2%

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

5. Simplified 47.2%

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

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 48.5%

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

8. Simplified 48.5%

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

Alternative 10: 50.3% 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 48.0%

   \[\cos \left(x + \varepsilon\right) - \cos x \]
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 47.2%

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

5. Simplified 47.2%

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

6. Taylor expanded in eps around 0

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

8. Simplified 47.2%

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

   1. metadata-eval 47.2%

      \[\leadsto 0 \]

10. Applied egg-rr 47.2%

    \[\leadsto \color{blue}{0} \]
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 2024149 
(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)))