Octave 3.8, jcobi/4

Percentage Accurate: 16.9% → 97.0%
Time: 13.0s
Alternatives: 12
Speedup: 115.0×

Specification

?
\[\left(\alpha > -1 \land \beta > -1\right) \land i > 1\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_2 := t\_1 \cdot t\_1\\ \frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1} \end{array} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (* i (+ (+ alpha beta) i)))
        (t_1 (+ (+ alpha beta) (* 2.0 i)))
        (t_2 (* t_1 t_1)))
   (/ (/ (* t_0 (+ (* beta alpha) t_0)) t_2) (- t_2 1.0))))
double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: t_2
    t_0 = i * ((alpha + beta) + i)
    t_1 = (alpha + beta) + (2.0d0 * i)
    t_2 = t_1 * t_1
    code = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0d0)
end function
public static double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
def code(alpha, beta, i):
	t_0 = i * ((alpha + beta) + i)
	t_1 = (alpha + beta) + (2.0 * i)
	t_2 = t_1 * t_1
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0)
function code(alpha, beta, i)
	t_0 = Float64(i * Float64(Float64(alpha + beta) + i))
	t_1 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
	t_2 = Float64(t_1 * t_1)
	return Float64(Float64(Float64(t_0 * Float64(Float64(beta * alpha) + t_0)) / t_2) / Float64(t_2 - 1.0))
end
function tmp = code(alpha, beta, i)
	t_0 = i * ((alpha + beta) + i);
	t_1 = (alpha + beta) + (2.0 * i);
	t_2 = t_1 * t_1;
	tmp = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, N[(N[(N[(t$95$0 * N[(N[(beta * alpha), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision] / N[(t$95$2 - 1.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_2 := t\_1 \cdot t\_1\\
\frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1}
\end{array}
\end{array}

Sampling outcomes in binary64 precision:

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 12 alternatives:

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

Initial Program: 16.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_2 := t\_1 \cdot t\_1\\ \frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1} \end{array} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (* i (+ (+ alpha beta) i)))
        (t_1 (+ (+ alpha beta) (* 2.0 i)))
        (t_2 (* t_1 t_1)))
   (/ (/ (* t_0 (+ (* beta alpha) t_0)) t_2) (- t_2 1.0))))
double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
real(8) function code(alpha, beta, i)
    real(8), intent (in) :: alpha
    real(8), intent (in) :: beta
    real(8), intent (in) :: i
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: t_2
    t_0 = i * ((alpha + beta) + i)
    t_1 = (alpha + beta) + (2.0d0 * i)
    t_2 = t_1 * t_1
    code = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0d0)
end function
public static double code(double alpha, double beta, double i) {
	double t_0 = i * ((alpha + beta) + i);
	double t_1 = (alpha + beta) + (2.0 * i);
	double t_2 = t_1 * t_1;
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
}
def code(alpha, beta, i):
	t_0 = i * ((alpha + beta) + i)
	t_1 = (alpha + beta) + (2.0 * i)
	t_2 = t_1 * t_1
	return ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0)
function code(alpha, beta, i)
	t_0 = Float64(i * Float64(Float64(alpha + beta) + i))
	t_1 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
	t_2 = Float64(t_1 * t_1)
	return Float64(Float64(Float64(t_0 * Float64(Float64(beta * alpha) + t_0)) / t_2) / Float64(t_2 - 1.0))
end
function tmp = code(alpha, beta, i)
	t_0 = i * ((alpha + beta) + i);
	t_1 = (alpha + beta) + (2.0 * i);
	t_2 = t_1 * t_1;
	tmp = ((t_0 * ((beta * alpha) + t_0)) / t_2) / (t_2 - 1.0);
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, N[(N[(N[(t$95$0 * N[(N[(beta * alpha), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision] / N[(t$95$2 - 1.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
t_1 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_2 := t\_1 \cdot t\_1\\
\frac{\frac{t\_0 \cdot \left(\beta \cdot \alpha + t\_0\right)}{t\_2}}{t\_2 - 1}
\end{array}
\end{array}

Alternative 1: 97.0% accurate, 1.1× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\ \frac{\left(i + \beta\right) \cdot \frac{i}{\mathsf{fma}\left(i, 2, \beta\right)}}{\mathsf{fma}\left(i, 2, \beta\right) - 1} \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0} \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (fma 2.0 i (+ alpha beta))))
   (*
    (/ (* (+ i beta) (/ i (fma i 2.0 beta))) (- (fma i 2.0 beta) 1.0))
    (/ (* (/ i t_0) (+ i (+ alpha beta))) (+ 1.0 t_0)))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double t_0 = fma(2.0, i, (alpha + beta));
	return (((i + beta) * (i / fma(i, 2.0, beta))) / (fma(i, 2.0, beta) - 1.0)) * (((i / t_0) * (i + (alpha + beta))) / (1.0 + t_0));
}
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	t_0 = fma(2.0, i, Float64(alpha + beta))
	return Float64(Float64(Float64(Float64(i + beta) * Float64(i / fma(i, 2.0, beta))) / Float64(fma(i, 2.0, beta) - 1.0)) * Float64(Float64(Float64(i / t_0) * Float64(i + Float64(alpha + beta))) / Float64(1.0 + t_0)))
end
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[(N[(i + beta), $MachinePrecision] * N[(i / N[(i * 2.0 + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(i * 2.0 + beta), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(N[(i / t$95$0), $MachinePrecision] * N[(i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\
\frac{\left(i + \beta\right) \cdot \frac{i}{\mathsf{fma}\left(i, 2, \beta\right)}}{\mathsf{fma}\left(i, 2, \beta\right) - 1} \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0}
\end{array}
\end{array}
Derivation
  1. Initial program 19.3%

    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-*.f64N/A

      \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. lift-*.f64N/A

      \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    3. associate-*l*N/A

      \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    5. lower-*.f64N/A

      \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    6. *-commutativeN/A

      \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    7. lower-*.f6419.2

      \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    8. lift-+.f64N/A

      \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    9. +-commutativeN/A

      \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    10. lift-*.f64N/A

      \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    11. *-commutativeN/A

      \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    12. lower-fma.f6419.2

      \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    13. lift-*.f64N/A

      \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    14. *-commutativeN/A

      \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    15. lower-*.f6419.2

      \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
  4. Applied rewrites19.2%

    \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
  5. Applied rewrites46.3%

    \[\leadsto \color{blue}{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1}} \]
  6. Taylor expanded in alpha around 0

    \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i \cdot \left(\beta + i\right)}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
  7. Step-by-step derivation
    1. lower-/.f64N/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i \cdot \left(\beta + i\right)}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
    2. lower-*.f64N/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i \cdot \left(\beta + i\right)}}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
    3. +-commutativeN/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \color{blue}{\left(i + \beta\right)}}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
    4. lower-+.f64N/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \color{blue}{\left(i + \beta\right)}}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
    5. lower-*.f64N/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
    6. +-commutativeN/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
    7. lower-fma.f64N/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\color{blue}{\mathsf{fma}\left(2, i, \beta\right)} \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
    8. lower--.f64N/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \color{blue}{\left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
    9. +-commutativeN/A

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \left(\color{blue}{\left(2 \cdot i + \beta\right)} - 1\right)} \]
    10. lower-fma.f6439.1

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \left(\color{blue}{\mathsf{fma}\left(2, i, \beta\right)} - 1\right)} \]
  8. Applied rewrites39.1%

    \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \left(\mathsf{fma}\left(2, i, \beta\right) - 1\right)}} \]
  9. Step-by-step derivation
    1. Applied rewrites85.9%

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\frac{i}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \left(i + \beta\right)}{\color{blue}{\mathsf{fma}\left(i, 2, \beta\right) - 1}} \]
    2. Final simplification85.9%

      \[\leadsto \frac{\left(i + \beta\right) \cdot \frac{i}{\mathsf{fma}\left(i, 2, \beta\right)}}{\mathsf{fma}\left(i, 2, \beta\right) - 1} \cdot \frac{\frac{i}{\mathsf{fma}\left(2, i, \alpha + \beta\right)} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + \mathsf{fma}\left(2, i, \alpha + \beta\right)} \]
    3. Add Preprocessing

    Alternative 2: 97.0% accurate, 1.1× speedup?

    \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\ \left(\frac{i}{\mathsf{fma}\left(i, 2, \beta\right) - 1} \cdot \frac{i + \beta}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0} \end{array} \end{array} \]
    NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
    (FPCore (alpha beta i)
     :precision binary64
     (let* ((t_0 (fma 2.0 i (+ alpha beta))))
       (*
        (* (/ i (- (fma i 2.0 beta) 1.0)) (/ (+ i beta) (fma i 2.0 beta)))
        (/ (* (/ i t_0) (+ i (+ alpha beta))) (+ 1.0 t_0)))))
    assert(alpha < beta && beta < i);
    double code(double alpha, double beta, double i) {
    	double t_0 = fma(2.0, i, (alpha + beta));
    	return ((i / (fma(i, 2.0, beta) - 1.0)) * ((i + beta) / fma(i, 2.0, beta))) * (((i / t_0) * (i + (alpha + beta))) / (1.0 + t_0));
    }
    
    alpha, beta, i = sort([alpha, beta, i])
    function code(alpha, beta, i)
    	t_0 = fma(2.0, i, Float64(alpha + beta))
    	return Float64(Float64(Float64(i / Float64(fma(i, 2.0, beta) - 1.0)) * Float64(Float64(i + beta) / fma(i, 2.0, beta))) * Float64(Float64(Float64(i / t_0) * Float64(i + Float64(alpha + beta))) / Float64(1.0 + t_0)))
    end
    
    NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
    code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[(i / N[(N[(i * 2.0 + beta), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(i + beta), $MachinePrecision] / N[(i * 2.0 + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(N[(i / t$95$0), $MachinePrecision] * N[(i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
    
    \begin{array}{l}
    [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
    \\
    \begin{array}{l}
    t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\
    \left(\frac{i}{\mathsf{fma}\left(i, 2, \beta\right) - 1} \cdot \frac{i + \beta}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0}
    \end{array}
    \end{array}
    
    Derivation
    1. Initial program 19.3%

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      3. associate-*l*N/A

        \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      4. *-commutativeN/A

        \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      5. lower-*.f64N/A

        \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      6. *-commutativeN/A

        \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      7. lower-*.f6419.2

        \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      9. +-commutativeN/A

        \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      10. lift-*.f64N/A

        \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      11. *-commutativeN/A

        \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      12. lower-fma.f6419.2

        \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      13. lift-*.f64N/A

        \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      14. *-commutativeN/A

        \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      15. lower-*.f6419.2

        \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    4. Applied rewrites19.2%

      \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    5. Applied rewrites46.3%

      \[\leadsto \color{blue}{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1}} \]
    6. Taylor expanded in alpha around 0

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i \cdot \left(\beta + i\right)}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
    7. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i \cdot \left(\beta + i\right)}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
      2. lower-*.f64N/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i \cdot \left(\beta + i\right)}}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \color{blue}{\left(i + \beta\right)}}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
      4. lower-+.f64N/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \color{blue}{\left(i + \beta\right)}}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
      5. lower-*.f64N/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\color{blue}{\left(\beta + 2 \cdot i\right) \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
      6. +-commutativeN/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\color{blue}{\left(2 \cdot i + \beta\right)} \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
      7. lower-fma.f64N/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\color{blue}{\mathsf{fma}\left(2, i, \beta\right)} \cdot \left(\left(\beta + 2 \cdot i\right) - 1\right)} \]
      8. lower--.f64N/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \color{blue}{\left(\left(\beta + 2 \cdot i\right) - 1\right)}} \]
      9. +-commutativeN/A

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \left(\color{blue}{\left(2 \cdot i + \beta\right)} - 1\right)} \]
      10. lower-fma.f6439.1

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \left(\color{blue}{\mathsf{fma}\left(2, i, \beta\right)} - 1\right)} \]
    8. Applied rewrites39.1%

      \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i \cdot \left(i + \beta\right)}{\mathsf{fma}\left(2, i, \beta\right) \cdot \left(\mathsf{fma}\left(2, i, \beta\right) - 1\right)}} \]
    9. Step-by-step derivation
      1. Applied rewrites85.9%

        \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \left(\frac{i + \beta}{\mathsf{fma}\left(i, 2, \beta\right)} \cdot \color{blue}{\frac{i}{\mathsf{fma}\left(i, 2, \beta\right) - 1}}\right) \]
      2. Final simplification85.9%

        \[\leadsto \left(\frac{i}{\mathsf{fma}\left(i, 2, \beta\right) - 1} \cdot \frac{i + \beta}{\mathsf{fma}\left(i, 2, \beta\right)}\right) \cdot \frac{\frac{i}{\mathsf{fma}\left(2, i, \alpha + \beta\right)} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + \mathsf{fma}\left(2, i, \alpha + \beta\right)} \]
      3. Add Preprocessing

      Alternative 3: 84.6% accurate, 1.2× speedup?

      \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\ \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{t\_0 - 1} \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0}\\ \end{array} \end{array} \]
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      (FPCore (alpha beta i)
       :precision binary64
       (let* ((t_0 (fma 2.0 i (+ alpha beta))))
         (if (<= beta 3.6e+216)
           (-
            (fma 0.0625 (/ (* 2.0 (+ alpha beta)) i) 0.0625)
            (* (/ (+ alpha beta) i) 0.125))
           (*
            (/ (+ i alpha) (- t_0 1.0))
            (/ (* (/ i t_0) (+ i (+ alpha beta))) (+ 1.0 t_0))))))
      assert(alpha < beta && beta < i);
      double code(double alpha, double beta, double i) {
      	double t_0 = fma(2.0, i, (alpha + beta));
      	double tmp;
      	if (beta <= 3.6e+216) {
      		tmp = fma(0.0625, ((2.0 * (alpha + beta)) / i), 0.0625) - (((alpha + beta) / i) * 0.125);
      	} else {
      		tmp = ((i + alpha) / (t_0 - 1.0)) * (((i / t_0) * (i + (alpha + beta))) / (1.0 + t_0));
      	}
      	return tmp;
      }
      
      alpha, beta, i = sort([alpha, beta, i])
      function code(alpha, beta, i)
      	t_0 = fma(2.0, i, Float64(alpha + beta))
      	tmp = 0.0
      	if (beta <= 3.6e+216)
      		tmp = Float64(fma(0.0625, Float64(Float64(2.0 * Float64(alpha + beta)) / i), 0.0625) - Float64(Float64(Float64(alpha + beta) / i) * 0.125));
      	else
      		tmp = Float64(Float64(Float64(i + alpha) / Float64(t_0 - 1.0)) * Float64(Float64(Float64(i / t_0) * Float64(i + Float64(alpha + beta))) / Float64(1.0 + t_0)));
      	end
      	return tmp
      end
      
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[beta, 3.6e+216], N[(N[(0.0625 * N[(N[(2.0 * N[(alpha + beta), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] + 0.0625), $MachinePrecision] - N[(N[(N[(alpha + beta), $MachinePrecision] / i), $MachinePrecision] * 0.125), $MachinePrecision]), $MachinePrecision], N[(N[(N[(i + alpha), $MachinePrecision] / N[(t$95$0 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(N[(i / t$95$0), $MachinePrecision] * N[(i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
      
      \begin{array}{l}
      [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
      \\
      \begin{array}{l}
      t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\
      \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
      \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\
      
      \mathbf{else}:\\
      \;\;\;\;\frac{i + \alpha}{t\_0 - 1} \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if beta < 3.6000000000000002e216

        1. Initial program 21.2%

          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lower-*.f6421.1

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lower-fma.f6421.1

            \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lower-*.f6421.1

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        4. Applied rewrites21.1%

          \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        5. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\alpha + \beta\right) + i\right) \cdot \color{blue}{\left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\alpha + \beta\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. lower-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. lower-*.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\alpha + \beta\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. lower-+.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          16. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          17. lower-*.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        6. Applied rewrites21.2%

          \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        7. Taylor expanded in i around inf

          \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
        8. Step-by-step derivation
          1. lower--.f64N/A

            \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          2. +-commutativeN/A

            \[\leadsto \color{blue}{\left(\frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i} + \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          3. lower-fma.f64N/A

            \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \alpha + 2 \cdot \beta}{i}, \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          4. lower-/.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \color{blue}{\frac{2 \cdot \alpha + 2 \cdot \beta}{i}}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          5. distribute-lft-inN/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          6. lower-*.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          7. lower-+.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \color{blue}{\left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          8. lower-*.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \color{blue}{\frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          9. lower-/.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \color{blue}{\frac{\alpha + \beta}{i}} \]
          10. lower-+.f6482.4

            \[\leadsto \mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\color{blue}{\alpha + \beta}}{i} \]
        9. Applied rewrites82.4%

          \[\leadsto \color{blue}{\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\alpha + \beta}{i}} \]

        if 3.6000000000000002e216 < beta

        1. Initial program 0.0%

          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lower-*.f640.0

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lower-fma.f640.0

            \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lower-*.f640.0

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        4. Applied rewrites0.0%

          \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        5. Applied rewrites10.7%

          \[\leadsto \color{blue}{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1}} \]
        6. Taylor expanded in beta around inf

          \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{\alpha + i}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \]
        7. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i + \alpha}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \]
          2. lower-+.f6483.5

            \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i + \alpha}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \]
        8. Applied rewrites83.5%

          \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i + \alpha}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \]
      3. Recombined 2 regimes into one program.
      4. Final simplification82.5%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{\mathsf{fma}\left(2, i, \alpha + \beta\right) - 1} \cdot \frac{\frac{i}{\mathsf{fma}\left(2, i, \alpha + \beta\right)} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + \mathsf{fma}\left(2, i, \alpha + \beta\right)}\\ \end{array} \]
      5. Add Preprocessing

      Alternative 4: 84.3% accurate, 1.4× speedup?

      \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\ \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{\beta} \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0}\\ \end{array} \end{array} \]
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      (FPCore (alpha beta i)
       :precision binary64
       (let* ((t_0 (fma 2.0 i (+ alpha beta))))
         (if (<= beta 3.6e+216)
           (-
            (fma 0.0625 (/ (* 2.0 (+ alpha beta)) i) 0.0625)
            (* (/ (+ alpha beta) i) 0.125))
           (*
            (/ (+ i alpha) beta)
            (/ (* (/ i t_0) (+ i (+ alpha beta))) (+ 1.0 t_0))))))
      assert(alpha < beta && beta < i);
      double code(double alpha, double beta, double i) {
      	double t_0 = fma(2.0, i, (alpha + beta));
      	double tmp;
      	if (beta <= 3.6e+216) {
      		tmp = fma(0.0625, ((2.0 * (alpha + beta)) / i), 0.0625) - (((alpha + beta) / i) * 0.125);
      	} else {
      		tmp = ((i + alpha) / beta) * (((i / t_0) * (i + (alpha + beta))) / (1.0 + t_0));
      	}
      	return tmp;
      }
      
      alpha, beta, i = sort([alpha, beta, i])
      function code(alpha, beta, i)
      	t_0 = fma(2.0, i, Float64(alpha + beta))
      	tmp = 0.0
      	if (beta <= 3.6e+216)
      		tmp = Float64(fma(0.0625, Float64(Float64(2.0 * Float64(alpha + beta)) / i), 0.0625) - Float64(Float64(Float64(alpha + beta) / i) * 0.125));
      	else
      		tmp = Float64(Float64(Float64(i + alpha) / beta) * Float64(Float64(Float64(i / t_0) * Float64(i + Float64(alpha + beta))) / Float64(1.0 + t_0)));
      	end
      	return tmp
      end
      
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[beta, 3.6e+216], N[(N[(0.0625 * N[(N[(2.0 * N[(alpha + beta), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] + 0.0625), $MachinePrecision] - N[(N[(N[(alpha + beta), $MachinePrecision] / i), $MachinePrecision] * 0.125), $MachinePrecision]), $MachinePrecision], N[(N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision] * N[(N[(N[(i / t$95$0), $MachinePrecision] * N[(i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
      
      \begin{array}{l}
      [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
      \\
      \begin{array}{l}
      t_0 := \mathsf{fma}\left(2, i, \alpha + \beta\right)\\
      \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
      \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\
      
      \mathbf{else}:\\
      \;\;\;\;\frac{i + \alpha}{\beta} \cdot \frac{\frac{i}{t\_0} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + t\_0}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if beta < 3.6000000000000002e216

        1. Initial program 21.2%

          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lower-*.f6421.1

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lower-fma.f6421.1

            \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lower-*.f6421.1

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        4. Applied rewrites21.1%

          \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        5. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\alpha + \beta\right) + i\right) \cdot \color{blue}{\left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\alpha + \beta\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. lower-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. lower-*.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\alpha + \beta\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. lower-+.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          16. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          17. lower-*.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        6. Applied rewrites21.2%

          \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        7. Taylor expanded in i around inf

          \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
        8. Step-by-step derivation
          1. lower--.f64N/A

            \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          2. +-commutativeN/A

            \[\leadsto \color{blue}{\left(\frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i} + \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          3. lower-fma.f64N/A

            \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \alpha + 2 \cdot \beta}{i}, \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          4. lower-/.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \color{blue}{\frac{2 \cdot \alpha + 2 \cdot \beta}{i}}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          5. distribute-lft-inN/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          6. lower-*.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          7. lower-+.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \color{blue}{\left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          8. lower-*.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \color{blue}{\frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          9. lower-/.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \color{blue}{\frac{\alpha + \beta}{i}} \]
          10. lower-+.f6482.4

            \[\leadsto \mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\color{blue}{\alpha + \beta}}{i} \]
        9. Applied rewrites82.4%

          \[\leadsto \color{blue}{\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\alpha + \beta}{i}} \]

        if 3.6000000000000002e216 < beta

        1. Initial program 0.0%

          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lower-*.f640.0

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lower-fma.f640.0

            \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lower-*.f640.0

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        4. Applied rewrites0.0%

          \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        5. Applied rewrites10.7%

          \[\leadsto \color{blue}{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1}} \]
        6. Taylor expanded in beta around inf

          \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{\alpha + i}{\beta}} \]
        7. Step-by-step derivation
          1. lower-/.f64N/A

            \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{\alpha + i}{\beta}} \]
          2. +-commutativeN/A

            \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i + \alpha}}{\beta} \]
          3. lower-+.f6482.5

            \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \frac{\color{blue}{i + \alpha}}{\beta} \]
        8. Applied rewrites82.5%

          \[\leadsto \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) + 1} \cdot \color{blue}{\frac{i + \alpha}{\beta}} \]
      3. Recombined 2 regimes into one program.
      4. Final simplification82.4%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{i + \alpha}{\beta} \cdot \frac{\frac{i}{\mathsf{fma}\left(2, i, \alpha + \beta\right)} \cdot \left(i + \left(\alpha + \beta\right)\right)}{1 + \mathsf{fma}\left(2, i, \alpha + \beta\right)}\\ \end{array} \]
      5. Add Preprocessing

      Alternative 5: 84.3% accurate, 2.1× speedup?

      \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\ \end{array} \end{array} \]
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      (FPCore (alpha beta i)
       :precision binary64
       (if (<= beta 3.6e+216)
         (-
          (fma 0.0625 (/ (* 2.0 (+ alpha beta)) i) 0.0625)
          (* (/ (+ alpha beta) i) 0.125))
         (/ (/ (+ i alpha) beta) (/ beta i))))
      assert(alpha < beta && beta < i);
      double code(double alpha, double beta, double i) {
      	double tmp;
      	if (beta <= 3.6e+216) {
      		tmp = fma(0.0625, ((2.0 * (alpha + beta)) / i), 0.0625) - (((alpha + beta) / i) * 0.125);
      	} else {
      		tmp = ((i + alpha) / beta) / (beta / i);
      	}
      	return tmp;
      }
      
      alpha, beta, i = sort([alpha, beta, i])
      function code(alpha, beta, i)
      	tmp = 0.0
      	if (beta <= 3.6e+216)
      		tmp = Float64(fma(0.0625, Float64(Float64(2.0 * Float64(alpha + beta)) / i), 0.0625) - Float64(Float64(Float64(alpha + beta) / i) * 0.125));
      	else
      		tmp = Float64(Float64(Float64(i + alpha) / beta) / Float64(beta / i));
      	end
      	return tmp
      end
      
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      code[alpha_, beta_, i_] := If[LessEqual[beta, 3.6e+216], N[(N[(0.0625 * N[(N[(2.0 * N[(alpha + beta), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] + 0.0625), $MachinePrecision] - N[(N[(N[(alpha + beta), $MachinePrecision] / i), $MachinePrecision] * 0.125), $MachinePrecision]), $MachinePrecision], N[(N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision] / N[(beta / i), $MachinePrecision]), $MachinePrecision]]
      
      \begin{array}{l}
      [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
      \\
      \begin{array}{l}
      \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
      \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\
      
      \mathbf{else}:\\
      \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if beta < 3.6000000000000002e216

        1. Initial program 21.2%

          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lower-*.f6421.1

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lower-fma.f6421.1

            \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lower-*.f6421.1

            \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        4. Applied rewrites21.1%

          \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        5. Step-by-step derivation
          1. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. lift-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          3. *-commutativeN/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. associate-*l*N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\alpha + \beta\right) + i\right) \cdot \color{blue}{\left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. lower-*.f64N/A

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\alpha + \beta\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          8. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          9. lower-+.f64N/A

            \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          10. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          11. lower-*.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          12. lift-+.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\alpha + \beta\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          13. +-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          14. lower-+.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          15. lift-*.f64N/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          16. *-commutativeN/A

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          17. lower-*.f6421.2

            \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        6. Applied rewrites21.2%

          \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        7. Taylor expanded in i around inf

          \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
        8. Step-by-step derivation
          1. lower--.f64N/A

            \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          2. +-commutativeN/A

            \[\leadsto \color{blue}{\left(\frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i} + \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          3. lower-fma.f64N/A

            \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \alpha + 2 \cdot \beta}{i}, \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          4. lower-/.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \color{blue}{\frac{2 \cdot \alpha + 2 \cdot \beta}{i}}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          5. distribute-lft-inN/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          6. lower-*.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          7. lower-+.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \color{blue}{\left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          8. lower-*.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \color{blue}{\frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          9. lower-/.f64N/A

            \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \color{blue}{\frac{\alpha + \beta}{i}} \]
          10. lower-+.f6482.4

            \[\leadsto \mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\color{blue}{\alpha + \beta}}{i} \]
        9. Applied rewrites82.4%

          \[\leadsto \color{blue}{\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\alpha + \beta}{i}} \]

        if 3.6000000000000002e216 < beta

        1. Initial program 0.0%

          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        2. Add Preprocessing
        3. Taylor expanded in beta around inf

          \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
          2. unpow2N/A

            \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
          3. times-fracN/A

            \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
          4. lower-*.f64N/A

            \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
          5. lower-/.f64N/A

            \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
          6. +-commutativeN/A

            \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
          7. lower-+.f64N/A

            \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
          8. lower-/.f6482.2

            \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
        5. Applied rewrites82.2%

          \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
        6. Step-by-step derivation
          1. Applied rewrites82.4%

            \[\leadsto \frac{\frac{\alpha + i}{\beta}}{\color{blue}{\frac{\beta}{i}}} \]
        7. Recombined 2 regimes into one program.
        8. Final simplification82.4%

          \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\ \end{array} \]
        9. Add Preprocessing

        Alternative 6: 84.3% accurate, 2.5× speedup?

        \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.125, \frac{\beta}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\ \end{array} \end{array} \]
        NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
        (FPCore (alpha beta i)
         :precision binary64
         (if (<= beta 3.6e+216)
           (- (fma 0.125 (/ beta i) 0.0625) (* (/ (+ alpha beta) i) 0.125))
           (/ (/ (+ i alpha) beta) (/ beta i))))
        assert(alpha < beta && beta < i);
        double code(double alpha, double beta, double i) {
        	double tmp;
        	if (beta <= 3.6e+216) {
        		tmp = fma(0.125, (beta / i), 0.0625) - (((alpha + beta) / i) * 0.125);
        	} else {
        		tmp = ((i + alpha) / beta) / (beta / i);
        	}
        	return tmp;
        }
        
        alpha, beta, i = sort([alpha, beta, i])
        function code(alpha, beta, i)
        	tmp = 0.0
        	if (beta <= 3.6e+216)
        		tmp = Float64(fma(0.125, Float64(beta / i), 0.0625) - Float64(Float64(Float64(alpha + beta) / i) * 0.125));
        	else
        		tmp = Float64(Float64(Float64(i + alpha) / beta) / Float64(beta / i));
        	end
        	return tmp
        end
        
        NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
        code[alpha_, beta_, i_] := If[LessEqual[beta, 3.6e+216], N[(N[(0.125 * N[(beta / i), $MachinePrecision] + 0.0625), $MachinePrecision] - N[(N[(N[(alpha + beta), $MachinePrecision] / i), $MachinePrecision] * 0.125), $MachinePrecision]), $MachinePrecision], N[(N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision] / N[(beta / i), $MachinePrecision]), $MachinePrecision]]
        
        \begin{array}{l}
        [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
        \\
        \begin{array}{l}
        \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
        \;\;\;\;\mathsf{fma}\left(0.125, \frac{\beta}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\
        
        \mathbf{else}:\\
        \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if beta < 3.6000000000000002e216

          1. Initial program 21.2%

            \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            2. lift-*.f64N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            3. associate-*l*N/A

              \[\leadsto \frac{\frac{\color{blue}{i \cdot \left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            4. *-commutativeN/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            5. lower-*.f64N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            6. *-commutativeN/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            7. lower-*.f6421.1

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            8. lift-+.f64N/A

              \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            9. +-commutativeN/A

              \[\leadsto \frac{\frac{\left(\color{blue}{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right) + \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            10. lift-*.f64N/A

              \[\leadsto \frac{\frac{\left(\left(\color{blue}{i \cdot \left(\left(\alpha + \beta\right) + i\right)} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            11. *-commutativeN/A

              \[\leadsto \frac{\frac{\left(\left(\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot i} + \beta \cdot \alpha\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            12. lower-fma.f6421.1

              \[\leadsto \frac{\frac{\left(\color{blue}{\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \beta \cdot \alpha\right)} \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            13. lift-*.f64N/A

              \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            14. *-commutativeN/A

              \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            15. lower-*.f6421.1

              \[\leadsto \frac{\frac{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          4. Applied rewrites21.1%

            \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. Step-by-step derivation
            1. lift-*.f64N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            2. lift-*.f64N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot \left(\left(\alpha + \beta\right) + i\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            3. *-commutativeN/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\left(\alpha + \beta\right) + i\right) \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)} \cdot i}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            4. associate-*l*N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            5. *-commutativeN/A

              \[\leadsto \frac{\frac{\left(\left(\alpha + \beta\right) + i\right) \cdot \color{blue}{\left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            6. lower-*.f64N/A

              \[\leadsto \frac{\frac{\color{blue}{\left(\left(\alpha + \beta\right) + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            7. lift-+.f64N/A

              \[\leadsto \frac{\frac{\left(\color{blue}{\left(\alpha + \beta\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            8. +-commutativeN/A

              \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            9. lower-+.f64N/A

              \[\leadsto \frac{\frac{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) \cdot \left(i \cdot \mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            10. *-commutativeN/A

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            11. lower-*.f6421.2

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \color{blue}{\left(\mathsf{fma}\left(\left(\alpha + \beta\right) + i, i, \alpha \cdot \beta\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            12. lift-+.f64N/A

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\alpha + \beta\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            13. +-commutativeN/A

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            14. lower-+.f6421.2

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\color{blue}{\left(\beta + \alpha\right)} + i, i, \alpha \cdot \beta\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            15. lift-*.f64N/A

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\alpha \cdot \beta}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            16. *-commutativeN/A

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            17. lower-*.f6421.2

              \[\leadsto \frac{\frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \color{blue}{\beta \cdot \alpha}\right) \cdot i\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          6. Applied rewrites21.2%

            \[\leadsto \frac{\frac{\color{blue}{\left(\left(\beta + \alpha\right) + i\right) \cdot \left(\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right) \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          7. Taylor expanded in i around inf

            \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
          8. Step-by-step derivation
            1. lower--.f64N/A

              \[\leadsto \color{blue}{\left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
            2. +-commutativeN/A

              \[\leadsto \color{blue}{\left(\frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i} + \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
            3. lower-fma.f64N/A

              \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \alpha + 2 \cdot \beta}{i}, \frac{1}{16}\right)} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
            4. lower-/.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \color{blue}{\frac{2 \cdot \alpha + 2 \cdot \beta}{i}}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
            5. distribute-lft-inN/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
            6. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{\color{blue}{2 \cdot \left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
            7. lower-+.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \color{blue}{\left(\alpha + \beta\right)}}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
            8. lower-*.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \color{blue}{\frac{1}{8} \cdot \frac{\alpha + \beta}{i}} \]
            9. lower-/.f64N/A

              \[\leadsto \mathsf{fma}\left(\frac{1}{16}, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, \frac{1}{16}\right) - \frac{1}{8} \cdot \color{blue}{\frac{\alpha + \beta}{i}} \]
            10. lower-+.f6482.4

              \[\leadsto \mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\color{blue}{\alpha + \beta}}{i} \]
          9. Applied rewrites82.4%

            \[\leadsto \color{blue}{\mathsf{fma}\left(0.0625, \frac{2 \cdot \left(\alpha + \beta\right)}{i}, 0.0625\right) - 0.125 \cdot \frac{\alpha + \beta}{i}} \]
          10. Taylor expanded in alpha around 0

            \[\leadsto \left(\frac{1}{16} + \frac{1}{8} \cdot \frac{\beta}{i}\right) - \color{blue}{\frac{1}{8}} \cdot \frac{\alpha + \beta}{i} \]
          11. Step-by-step derivation
            1. Applied rewrites77.6%

              \[\leadsto \mathsf{fma}\left(0.125, \frac{\beta}{i}, 0.0625\right) - \color{blue}{0.125} \cdot \frac{\alpha + \beta}{i} \]

            if 3.6000000000000002e216 < beta

            1. Initial program 0.0%

              \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
            2. Add Preprocessing
            3. Taylor expanded in beta around inf

              \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
            4. Step-by-step derivation
              1. *-commutativeN/A

                \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
              2. unpow2N/A

                \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
              3. times-fracN/A

                \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
              4. lower-*.f64N/A

                \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
              5. lower-/.f64N/A

                \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
              6. +-commutativeN/A

                \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
              7. lower-+.f64N/A

                \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
              8. lower-/.f6482.2

                \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
            5. Applied rewrites82.2%

              \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
            6. Step-by-step derivation
              1. Applied rewrites82.4%

                \[\leadsto \frac{\frac{\alpha + i}{\beta}}{\color{blue}{\frac{\beta}{i}}} \]
            7. Recombined 2 regimes into one program.
            8. Final simplification78.1%

              \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;\mathsf{fma}\left(0.125, \frac{\beta}{i}, 0.0625\right) - \frac{\alpha + \beta}{i} \cdot 0.125\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\ \end{array} \]
            9. Add Preprocessing

            Alternative 7: 83.5% accurate, 2.7× speedup?

            \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\ \end{array} \end{array} \]
            NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
            (FPCore (alpha beta i)
             :precision binary64
             (if (<= beta 3.6e+216) 0.0625 (/ (/ (+ i alpha) beta) (/ beta i))))
            assert(alpha < beta && beta < i);
            double code(double alpha, double beta, double i) {
            	double tmp;
            	if (beta <= 3.6e+216) {
            		tmp = 0.0625;
            	} else {
            		tmp = ((i + alpha) / beta) / (beta / i);
            	}
            	return tmp;
            }
            
            NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
            real(8) function code(alpha, beta, i)
                real(8), intent (in) :: alpha
                real(8), intent (in) :: beta
                real(8), intent (in) :: i
                real(8) :: tmp
                if (beta <= 3.6d+216) then
                    tmp = 0.0625d0
                else
                    tmp = ((i + alpha) / beta) / (beta / i)
                end if
                code = tmp
            end function
            
            assert alpha < beta && beta < i;
            public static double code(double alpha, double beta, double i) {
            	double tmp;
            	if (beta <= 3.6e+216) {
            		tmp = 0.0625;
            	} else {
            		tmp = ((i + alpha) / beta) / (beta / i);
            	}
            	return tmp;
            }
            
            [alpha, beta, i] = sort([alpha, beta, i])
            def code(alpha, beta, i):
            	tmp = 0
            	if beta <= 3.6e+216:
            		tmp = 0.0625
            	else:
            		tmp = ((i + alpha) / beta) / (beta / i)
            	return tmp
            
            alpha, beta, i = sort([alpha, beta, i])
            function code(alpha, beta, i)
            	tmp = 0.0
            	if (beta <= 3.6e+216)
            		tmp = 0.0625;
            	else
            		tmp = Float64(Float64(Float64(i + alpha) / beta) / Float64(beta / i));
            	end
            	return tmp
            end
            
            alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
            function tmp_2 = code(alpha, beta, i)
            	tmp = 0.0;
            	if (beta <= 3.6e+216)
            		tmp = 0.0625;
            	else
            		tmp = ((i + alpha) / beta) / (beta / i);
            	end
            	tmp_2 = tmp;
            end
            
            NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
            code[alpha_, beta_, i_] := If[LessEqual[beta, 3.6e+216], 0.0625, N[(N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision] / N[(beta / i), $MachinePrecision]), $MachinePrecision]]
            
            \begin{array}{l}
            [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
            \\
            \begin{array}{l}
            \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
            \;\;\;\;0.0625\\
            
            \mathbf{else}:\\
            \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if beta < 3.6000000000000002e216

              1. Initial program 21.2%

                \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
              2. Add Preprocessing
              3. Taylor expanded in i around inf

                \[\leadsto \color{blue}{\frac{1}{16}} \]
              4. Step-by-step derivation
                1. Applied rewrites78.7%

                  \[\leadsto \color{blue}{0.0625} \]

                if 3.6000000000000002e216 < beta

                1. Initial program 0.0%

                  \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                2. Add Preprocessing
                3. Taylor expanded in beta around inf

                  \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
                4. Step-by-step derivation
                  1. *-commutativeN/A

                    \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
                  2. unpow2N/A

                    \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
                  3. times-fracN/A

                    \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                  4. lower-*.f64N/A

                    \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                  5. lower-/.f64N/A

                    \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
                  6. +-commutativeN/A

                    \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                  7. lower-+.f64N/A

                    \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                  8. lower-/.f6482.2

                    \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
                5. Applied rewrites82.2%

                  \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
                6. Step-by-step derivation
                  1. Applied rewrites82.4%

                    \[\leadsto \frac{\frac{\alpha + i}{\beta}}{\color{blue}{\frac{\beta}{i}}} \]
                7. Recombined 2 regimes into one program.
                8. Final simplification79.0%

                  \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i + \alpha}{\beta}}{\frac{\beta}{i}}\\ \end{array} \]
                9. Add Preprocessing

                Alternative 8: 83.5% accurate, 3.1× speedup?

                \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta} \cdot \frac{i + \alpha}{\beta}\\ \end{array} \end{array} \]
                NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                (FPCore (alpha beta i)
                 :precision binary64
                 (if (<= beta 3.6e+216) 0.0625 (* (/ i beta) (/ (+ i alpha) beta))))
                assert(alpha < beta && beta < i);
                double code(double alpha, double beta, double i) {
                	double tmp;
                	if (beta <= 3.6e+216) {
                		tmp = 0.0625;
                	} else {
                		tmp = (i / beta) * ((i + alpha) / beta);
                	}
                	return tmp;
                }
                
                NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                real(8) function code(alpha, beta, i)
                    real(8), intent (in) :: alpha
                    real(8), intent (in) :: beta
                    real(8), intent (in) :: i
                    real(8) :: tmp
                    if (beta <= 3.6d+216) then
                        tmp = 0.0625d0
                    else
                        tmp = (i / beta) * ((i + alpha) / beta)
                    end if
                    code = tmp
                end function
                
                assert alpha < beta && beta < i;
                public static double code(double alpha, double beta, double i) {
                	double tmp;
                	if (beta <= 3.6e+216) {
                		tmp = 0.0625;
                	} else {
                		tmp = (i / beta) * ((i + alpha) / beta);
                	}
                	return tmp;
                }
                
                [alpha, beta, i] = sort([alpha, beta, i])
                def code(alpha, beta, i):
                	tmp = 0
                	if beta <= 3.6e+216:
                		tmp = 0.0625
                	else:
                		tmp = (i / beta) * ((i + alpha) / beta)
                	return tmp
                
                alpha, beta, i = sort([alpha, beta, i])
                function code(alpha, beta, i)
                	tmp = 0.0
                	if (beta <= 3.6e+216)
                		tmp = 0.0625;
                	else
                		tmp = Float64(Float64(i / beta) * Float64(Float64(i + alpha) / beta));
                	end
                	return tmp
                end
                
                alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
                function tmp_2 = code(alpha, beta, i)
                	tmp = 0.0;
                	if (beta <= 3.6e+216)
                		tmp = 0.0625;
                	else
                		tmp = (i / beta) * ((i + alpha) / beta);
                	end
                	tmp_2 = tmp;
                end
                
                NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                code[alpha_, beta_, i_] := If[LessEqual[beta, 3.6e+216], 0.0625, N[(N[(i / beta), $MachinePrecision] * N[(N[(i + alpha), $MachinePrecision] / beta), $MachinePrecision]), $MachinePrecision]]
                
                \begin{array}{l}
                [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                \\
                \begin{array}{l}
                \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
                \;\;\;\;0.0625\\
                
                \mathbf{else}:\\
                \;\;\;\;\frac{i}{\beta} \cdot \frac{i + \alpha}{\beta}\\
                
                
                \end{array}
                \end{array}
                
                Derivation
                1. Split input into 2 regimes
                2. if beta < 3.6000000000000002e216

                  1. Initial program 21.2%

                    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                  2. Add Preprocessing
                  3. Taylor expanded in i around inf

                    \[\leadsto \color{blue}{\frac{1}{16}} \]
                  4. Step-by-step derivation
                    1. Applied rewrites78.7%

                      \[\leadsto \color{blue}{0.0625} \]

                    if 3.6000000000000002e216 < beta

                    1. Initial program 0.0%

                      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                    2. Add Preprocessing
                    3. Taylor expanded in beta around inf

                      \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
                    4. Step-by-step derivation
                      1. *-commutativeN/A

                        \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
                      2. unpow2N/A

                        \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
                      3. times-fracN/A

                        \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                      4. lower-*.f64N/A

                        \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                      5. lower-/.f64N/A

                        \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
                      6. +-commutativeN/A

                        \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                      7. lower-+.f64N/A

                        \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                      8. lower-/.f6482.2

                        \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
                    5. Applied rewrites82.2%

                      \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
                  5. Recombined 2 regimes into one program.
                  6. Final simplification79.0%

                    \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta} \cdot \frac{i + \alpha}{\beta}\\ \end{array} \]
                  7. Add Preprocessing

                  Alternative 9: 82.1% accurate, 3.4× speedup?

                  \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta} \cdot \frac{i}{\beta}\\ \end{array} \end{array} \]
                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                  (FPCore (alpha beta i)
                   :precision binary64
                   (if (<= beta 3.6e+216) 0.0625 (* (/ i beta) (/ i beta))))
                  assert(alpha < beta && beta < i);
                  double code(double alpha, double beta, double i) {
                  	double tmp;
                  	if (beta <= 3.6e+216) {
                  		tmp = 0.0625;
                  	} else {
                  		tmp = (i / beta) * (i / beta);
                  	}
                  	return tmp;
                  }
                  
                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                  real(8) function code(alpha, beta, i)
                      real(8), intent (in) :: alpha
                      real(8), intent (in) :: beta
                      real(8), intent (in) :: i
                      real(8) :: tmp
                      if (beta <= 3.6d+216) then
                          tmp = 0.0625d0
                      else
                          tmp = (i / beta) * (i / beta)
                      end if
                      code = tmp
                  end function
                  
                  assert alpha < beta && beta < i;
                  public static double code(double alpha, double beta, double i) {
                  	double tmp;
                  	if (beta <= 3.6e+216) {
                  		tmp = 0.0625;
                  	} else {
                  		tmp = (i / beta) * (i / beta);
                  	}
                  	return tmp;
                  }
                  
                  [alpha, beta, i] = sort([alpha, beta, i])
                  def code(alpha, beta, i):
                  	tmp = 0
                  	if beta <= 3.6e+216:
                  		tmp = 0.0625
                  	else:
                  		tmp = (i / beta) * (i / beta)
                  	return tmp
                  
                  alpha, beta, i = sort([alpha, beta, i])
                  function code(alpha, beta, i)
                  	tmp = 0.0
                  	if (beta <= 3.6e+216)
                  		tmp = 0.0625;
                  	else
                  		tmp = Float64(Float64(i / beta) * Float64(i / beta));
                  	end
                  	return tmp
                  end
                  
                  alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
                  function tmp_2 = code(alpha, beta, i)
                  	tmp = 0.0;
                  	if (beta <= 3.6e+216)
                  		tmp = 0.0625;
                  	else
                  		tmp = (i / beta) * (i / beta);
                  	end
                  	tmp_2 = tmp;
                  end
                  
                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                  code[alpha_, beta_, i_] := If[LessEqual[beta, 3.6e+216], 0.0625, N[(N[(i / beta), $MachinePrecision] * N[(i / beta), $MachinePrecision]), $MachinePrecision]]
                  
                  \begin{array}{l}
                  [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                  \\
                  \begin{array}{l}
                  \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
                  \;\;\;\;0.0625\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;\frac{i}{\beta} \cdot \frac{i}{\beta}\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if beta < 3.6000000000000002e216

                    1. Initial program 21.2%

                      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                    2. Add Preprocessing
                    3. Taylor expanded in i around inf

                      \[\leadsto \color{blue}{\frac{1}{16}} \]
                    4. Step-by-step derivation
                      1. Applied rewrites78.7%

                        \[\leadsto \color{blue}{0.0625} \]

                      if 3.6000000000000002e216 < beta

                      1. Initial program 0.0%

                        \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                      2. Add Preprocessing
                      3. Taylor expanded in beta around inf

                        \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
                      4. Step-by-step derivation
                        1. *-commutativeN/A

                          \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
                        2. unpow2N/A

                          \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
                        3. times-fracN/A

                          \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                        4. lower-*.f64N/A

                          \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                        5. lower-/.f64N/A

                          \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
                        6. +-commutativeN/A

                          \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                        7. lower-+.f64N/A

                          \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                        8. lower-/.f6482.2

                          \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
                      5. Applied rewrites82.2%

                        \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
                      6. Taylor expanded in alpha around 0

                        \[\leadsto \frac{i}{\beta} \cdot \frac{\color{blue}{i}}{\beta} \]
                      7. Step-by-step derivation
                        1. Applied rewrites78.4%

                          \[\leadsto \frac{i}{\beta} \cdot \frac{\color{blue}{i}}{\beta} \]
                      8. Recombined 2 regimes into one program.
                      9. Add Preprocessing

                      Alternative 10: 76.8% accurate, 3.4× speedup?

                      \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{i}{\beta}}{\beta} \cdot i\\ \end{array} \end{array} \]
                      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                      (FPCore (alpha beta i)
                       :precision binary64
                       (if (<= beta 3.6e+216) 0.0625 (* (/ (/ i beta) beta) i)))
                      assert(alpha < beta && beta < i);
                      double code(double alpha, double beta, double i) {
                      	double tmp;
                      	if (beta <= 3.6e+216) {
                      		tmp = 0.0625;
                      	} else {
                      		tmp = ((i / beta) / beta) * i;
                      	}
                      	return tmp;
                      }
                      
                      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                      real(8) function code(alpha, beta, i)
                          real(8), intent (in) :: alpha
                          real(8), intent (in) :: beta
                          real(8), intent (in) :: i
                          real(8) :: tmp
                          if (beta <= 3.6d+216) then
                              tmp = 0.0625d0
                          else
                              tmp = ((i / beta) / beta) * i
                          end if
                          code = tmp
                      end function
                      
                      assert alpha < beta && beta < i;
                      public static double code(double alpha, double beta, double i) {
                      	double tmp;
                      	if (beta <= 3.6e+216) {
                      		tmp = 0.0625;
                      	} else {
                      		tmp = ((i / beta) / beta) * i;
                      	}
                      	return tmp;
                      }
                      
                      [alpha, beta, i] = sort([alpha, beta, i])
                      def code(alpha, beta, i):
                      	tmp = 0
                      	if beta <= 3.6e+216:
                      		tmp = 0.0625
                      	else:
                      		tmp = ((i / beta) / beta) * i
                      	return tmp
                      
                      alpha, beta, i = sort([alpha, beta, i])
                      function code(alpha, beta, i)
                      	tmp = 0.0
                      	if (beta <= 3.6e+216)
                      		tmp = 0.0625;
                      	else
                      		tmp = Float64(Float64(Float64(i / beta) / beta) * i);
                      	end
                      	return tmp
                      end
                      
                      alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
                      function tmp_2 = code(alpha, beta, i)
                      	tmp = 0.0;
                      	if (beta <= 3.6e+216)
                      		tmp = 0.0625;
                      	else
                      		tmp = ((i / beta) / beta) * i;
                      	end
                      	tmp_2 = tmp;
                      end
                      
                      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                      code[alpha_, beta_, i_] := If[LessEqual[beta, 3.6e+216], 0.0625, N[(N[(N[(i / beta), $MachinePrecision] / beta), $MachinePrecision] * i), $MachinePrecision]]
                      
                      \begin{array}{l}
                      [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                      \\
                      \begin{array}{l}
                      \mathbf{if}\;\beta \leq 3.6 \cdot 10^{+216}:\\
                      \;\;\;\;0.0625\\
                      
                      \mathbf{else}:\\
                      \;\;\;\;\frac{\frac{i}{\beta}}{\beta} \cdot i\\
                      
                      
                      \end{array}
                      \end{array}
                      
                      Derivation
                      1. Split input into 2 regimes
                      2. if beta < 3.6000000000000002e216

                        1. Initial program 21.2%

                          \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                        2. Add Preprocessing
                        3. Taylor expanded in i around inf

                          \[\leadsto \color{blue}{\frac{1}{16}} \]
                        4. Step-by-step derivation
                          1. Applied rewrites78.7%

                            \[\leadsto \color{blue}{0.0625} \]

                          if 3.6000000000000002e216 < beta

                          1. Initial program 0.0%

                            \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                          2. Add Preprocessing
                          3. Taylor expanded in beta around inf

                            \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
                          4. Step-by-step derivation
                            1. *-commutativeN/A

                              \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
                            2. unpow2N/A

                              \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
                            3. times-fracN/A

                              \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                            4. lower-*.f64N/A

                              \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                            5. lower-/.f64N/A

                              \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
                            6. +-commutativeN/A

                              \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                            7. lower-+.f64N/A

                              \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                            8. lower-/.f6482.2

                              \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
                          5. Applied rewrites82.2%

                            \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
                          6. Step-by-step derivation
                            1. Applied rewrites82.3%

                              \[\leadsto \frac{\frac{\alpha + i}{\beta} \cdot i}{\color{blue}{\beta}} \]
                            2. Taylor expanded in alpha around 0

                              \[\leadsto \frac{{i}^{2}}{\color{blue}{{\beta}^{2}}} \]
                            3. Step-by-step derivation
                              1. Applied rewrites27.5%

                                \[\leadsto \frac{i \cdot i}{\color{blue}{\beta \cdot \beta}} \]
                              2. Step-by-step derivation
                                1. Applied rewrites41.9%

                                  \[\leadsto \frac{\frac{i}{\beta}}{\beta} \cdot i \]
                              3. Recombined 2 regimes into one program.
                              4. Add Preprocessing

                              Alternative 11: 73.6% accurate, 4.1× speedup?

                              \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 3 \cdot 10^{+267}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta \cdot \beta} \cdot \alpha\\ \end{array} \end{array} \]
                              NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                              (FPCore (alpha beta i)
                               :precision binary64
                               (if (<= beta 3e+267) 0.0625 (* (/ i (* beta beta)) alpha)))
                              assert(alpha < beta && beta < i);
                              double code(double alpha, double beta, double i) {
                              	double tmp;
                              	if (beta <= 3e+267) {
                              		tmp = 0.0625;
                              	} else {
                              		tmp = (i / (beta * beta)) * alpha;
                              	}
                              	return tmp;
                              }
                              
                              NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                              real(8) function code(alpha, beta, i)
                                  real(8), intent (in) :: alpha
                                  real(8), intent (in) :: beta
                                  real(8), intent (in) :: i
                                  real(8) :: tmp
                                  if (beta <= 3d+267) then
                                      tmp = 0.0625d0
                                  else
                                      tmp = (i / (beta * beta)) * alpha
                                  end if
                                  code = tmp
                              end function
                              
                              assert alpha < beta && beta < i;
                              public static double code(double alpha, double beta, double i) {
                              	double tmp;
                              	if (beta <= 3e+267) {
                              		tmp = 0.0625;
                              	} else {
                              		tmp = (i / (beta * beta)) * alpha;
                              	}
                              	return tmp;
                              }
                              
                              [alpha, beta, i] = sort([alpha, beta, i])
                              def code(alpha, beta, i):
                              	tmp = 0
                              	if beta <= 3e+267:
                              		tmp = 0.0625
                              	else:
                              		tmp = (i / (beta * beta)) * alpha
                              	return tmp
                              
                              alpha, beta, i = sort([alpha, beta, i])
                              function code(alpha, beta, i)
                              	tmp = 0.0
                              	if (beta <= 3e+267)
                              		tmp = 0.0625;
                              	else
                              		tmp = Float64(Float64(i / Float64(beta * beta)) * alpha);
                              	end
                              	return tmp
                              end
                              
                              alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
                              function tmp_2 = code(alpha, beta, i)
                              	tmp = 0.0;
                              	if (beta <= 3e+267)
                              		tmp = 0.0625;
                              	else
                              		tmp = (i / (beta * beta)) * alpha;
                              	end
                              	tmp_2 = tmp;
                              end
                              
                              NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                              code[alpha_, beta_, i_] := If[LessEqual[beta, 3e+267], 0.0625, N[(N[(i / N[(beta * beta), $MachinePrecision]), $MachinePrecision] * alpha), $MachinePrecision]]
                              
                              \begin{array}{l}
                              [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                              \\
                              \begin{array}{l}
                              \mathbf{if}\;\beta \leq 3 \cdot 10^{+267}:\\
                              \;\;\;\;0.0625\\
                              
                              \mathbf{else}:\\
                              \;\;\;\;\frac{i}{\beta \cdot \beta} \cdot \alpha\\
                              
                              
                              \end{array}
                              \end{array}
                              
                              Derivation
                              1. Split input into 2 regimes
                              2. if beta < 2.9999999999999999e267

                                1. Initial program 20.4%

                                  \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                                2. Add Preprocessing
                                3. Taylor expanded in i around inf

                                  \[\leadsto \color{blue}{\frac{1}{16}} \]
                                4. Step-by-step derivation
                                  1. Applied rewrites76.2%

                                    \[\leadsto \color{blue}{0.0625} \]

                                  if 2.9999999999999999e267 < beta

                                  1. Initial program 0.0%

                                    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                                  2. Add Preprocessing
                                  3. Taylor expanded in beta around inf

                                    \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}}} \]
                                  4. Step-by-step derivation
                                    1. *-commutativeN/A

                                      \[\leadsto \frac{\color{blue}{\left(\alpha + i\right) \cdot i}}{{\beta}^{2}} \]
                                    2. unpow2N/A

                                      \[\leadsto \frac{\left(\alpha + i\right) \cdot i}{\color{blue}{\beta \cdot \beta}} \]
                                    3. times-fracN/A

                                      \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                                    4. lower-*.f64N/A

                                      \[\leadsto \color{blue}{\frac{\alpha + i}{\beta} \cdot \frac{i}{\beta}} \]
                                    5. lower-/.f64N/A

                                      \[\leadsto \color{blue}{\frac{\alpha + i}{\beta}} \cdot \frac{i}{\beta} \]
                                    6. +-commutativeN/A

                                      \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                                    7. lower-+.f64N/A

                                      \[\leadsto \frac{\color{blue}{i + \alpha}}{\beta} \cdot \frac{i}{\beta} \]
                                    8. lower-/.f6494.6

                                      \[\leadsto \frac{i + \alpha}{\beta} \cdot \color{blue}{\frac{i}{\beta}} \]
                                  5. Applied rewrites94.6%

                                    \[\leadsto \color{blue}{\frac{i + \alpha}{\beta} \cdot \frac{i}{\beta}} \]
                                  6. Taylor expanded in alpha around inf

                                    \[\leadsto \frac{\alpha \cdot i}{\color{blue}{{\beta}^{2}}} \]
                                  7. Step-by-step derivation
                                    1. Applied rewrites42.1%

                                      \[\leadsto \alpha \cdot \color{blue}{\frac{i}{\beta \cdot \beta}} \]
                                  8. Recombined 2 regimes into one program.
                                  9. Final simplification74.4%

                                    \[\leadsto \begin{array}{l} \mathbf{if}\;\beta \leq 3 \cdot 10^{+267}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta \cdot \beta} \cdot \alpha\\ \end{array} \]
                                  10. Add Preprocessing

                                  Alternative 12: 71.3% accurate, 115.0× speedup?

                                  \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ 0.0625 \end{array} \]
                                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                                  (FPCore (alpha beta i) :precision binary64 0.0625)
                                  assert(alpha < beta && beta < i);
                                  double code(double alpha, double beta, double i) {
                                  	return 0.0625;
                                  }
                                  
                                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                                  real(8) function code(alpha, beta, i)
                                      real(8), intent (in) :: alpha
                                      real(8), intent (in) :: beta
                                      real(8), intent (in) :: i
                                      code = 0.0625d0
                                  end function
                                  
                                  assert alpha < beta && beta < i;
                                  public static double code(double alpha, double beta, double i) {
                                  	return 0.0625;
                                  }
                                  
                                  [alpha, beta, i] = sort([alpha, beta, i])
                                  def code(alpha, beta, i):
                                  	return 0.0625
                                  
                                  alpha, beta, i = sort([alpha, beta, i])
                                  function code(alpha, beta, i)
                                  	return 0.0625
                                  end
                                  
                                  alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
                                  function tmp = code(alpha, beta, i)
                                  	tmp = 0.0625;
                                  end
                                  
                                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                                  code[alpha_, beta_, i_] := 0.0625
                                  
                                  \begin{array}{l}
                                  [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                                  \\
                                  0.0625
                                  \end{array}
                                  
                                  Derivation
                                  1. Initial program 19.3%

                                    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                                  2. Add Preprocessing
                                  3. Taylor expanded in i around inf

                                    \[\leadsto \color{blue}{\frac{1}{16}} \]
                                  4. Step-by-step derivation
                                    1. Applied rewrites72.5%

                                      \[\leadsto \color{blue}{0.0625} \]
                                    2. Add Preprocessing

                                    Reproduce

                                    ?
                                    herbie shell --seed 2024283 
                                    (FPCore (alpha beta i)
                                      :name "Octave 3.8, jcobi/4"
                                      :precision binary64
                                      :pre (and (and (> alpha -1.0) (> beta -1.0)) (> i 1.0))
                                      (/ (/ (* (* i (+ (+ alpha beta) i)) (+ (* beta alpha) (* i (+ (+ alpha beta) i)))) (* (+ (+ alpha beta) (* 2.0 i)) (+ (+ alpha beta) (* 2.0 i)))) (- (* (+ (+ alpha beta) (* 2.0 i)) (+ (+ alpha beta) (* 2.0 i))) 1.0)))