Octave 3.8, jcobi/4

Percentage Accurate: 15.3% → 83.5%
Time: 7.3s
Alternatives: 9
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);
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(alpha, beta, i)
use fmin_fmax_functions
    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 9 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: 15.3% 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);
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

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

real(8) function code(alpha, beta, i)
use fmin_fmax_functions
    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: 83.5% accurate, 0.3× speedup?

\[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_1 := t\_0 \cdot t\_0\\ t_2 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ t_3 := \left(\alpha + \beta\right) - -2 \cdot i\\ \mathbf{if}\;\frac{\frac{t\_2 \cdot \left(\beta \cdot \alpha + t\_2\right)}{t\_1}}{t\_1 - 1} \leq \infty:\\ \;\;\;\;\frac{\frac{t\_2}{t\_3} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, t\_2\right)}{t\_3}}{\left(i \cdot i\right) \cdot \left(4 - \frac{\mathsf{fma}\left(-4, \alpha + \beta, \frac{{\left(\alpha + \beta\right)}^{2}}{-i}\right)}{i}\right) - 1}\\ \mathbf{else}:\\ \;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\ \end{array} \end{array} \]
NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (+ (+ alpha beta) (* 2.0 i)))
        (t_1 (* t_0 t_0))
        (t_2 (* i (+ (+ alpha beta) i)))
        (t_3 (- (+ alpha beta) (* -2.0 i))))
   (if (<= (/ (/ (* t_2 (+ (* beta alpha) t_2)) t_1) (- t_1 1.0)) INFINITY)
     (/
      (* (/ t_2 t_3) (/ (fma beta alpha t_2) t_3))
      (-
       (*
        (* i i)
        (-
         4.0
         (/ (fma -4.0 (+ alpha beta) (/ (pow (+ alpha beta) 2.0) (- i))) i)))
       1.0))
     (- (/ (fma 0.0625 i (* 0.125 (+ alpha beta))) i) (* 0.125 (/ beta i))))))
assert(alpha < beta && beta < i);
double code(double alpha, double beta, double i) {
	double t_0 = (alpha + beta) + (2.0 * i);
	double t_1 = t_0 * t_0;
	double t_2 = i * ((alpha + beta) + i);
	double t_3 = (alpha + beta) - (-2.0 * i);
	double tmp;
	if ((((t_2 * ((beta * alpha) + t_2)) / t_1) / (t_1 - 1.0)) <= ((double) INFINITY)) {
		tmp = ((t_2 / t_3) * (fma(beta, alpha, t_2) / t_3)) / (((i * i) * (4.0 - (fma(-4.0, (alpha + beta), (pow((alpha + beta), 2.0) / -i)) / i))) - 1.0);
	} else {
		tmp = (fma(0.0625, i, (0.125 * (alpha + beta))) / i) - (0.125 * (beta / i));
	}
	return tmp;
}
alpha, beta, i = sort([alpha, beta, i])
function code(alpha, beta, i)
	t_0 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
	t_1 = Float64(t_0 * t_0)
	t_2 = Float64(i * Float64(Float64(alpha + beta) + i))
	t_3 = Float64(Float64(alpha + beta) - Float64(-2.0 * i))
	tmp = 0.0
	if (Float64(Float64(Float64(t_2 * Float64(Float64(beta * alpha) + t_2)) / t_1) / Float64(t_1 - 1.0)) <= Inf)
		tmp = Float64(Float64(Float64(t_2 / t_3) * Float64(fma(beta, alpha, t_2) / t_3)) / Float64(Float64(Float64(i * i) * Float64(4.0 - Float64(fma(-4.0, Float64(alpha + beta), Float64((Float64(alpha + beta) ^ 2.0) / Float64(-i))) / i))) - 1.0));
	else
		tmp = Float64(Float64(fma(0.0625, i, Float64(0.125 * Float64(alpha + beta))) / i) - Float64(0.125 * 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_] := Block[{t$95$0 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(alpha + beta), $MachinePrecision] - N[(-2.0 * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[(t$95$2 * N[(N[(beta * alpha), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision] / t$95$1), $MachinePrecision] / N[(t$95$1 - 1.0), $MachinePrecision]), $MachinePrecision], Infinity], N[(N[(N[(t$95$2 / t$95$3), $MachinePrecision] * N[(N[(beta * alpha + t$95$2), $MachinePrecision] / t$95$3), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(i * i), $MachinePrecision] * N[(4.0 - N[(N[(-4.0 * N[(alpha + beta), $MachinePrecision] + N[(N[Power[N[(alpha + beta), $MachinePrecision], 2.0], $MachinePrecision] / (-i)), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision], N[(N[(N[(0.0625 * i + N[(0.125 * N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] - N[(0.125 * N[(beta / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
[alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
\\
\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_1 := t\_0 \cdot t\_0\\
t_2 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
t_3 := \left(\alpha + \beta\right) - -2 \cdot i\\
\mathbf{if}\;\frac{\frac{t\_2 \cdot \left(\beta \cdot \alpha + t\_2\right)}{t\_1}}{t\_1 - 1} \leq \infty:\\
\;\;\;\;\frac{\frac{t\_2}{t\_3} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, t\_2\right)}{t\_3}}{\left(i \cdot i\right) \cdot \left(4 - \frac{\mathsf{fma}\left(-4, \alpha + \beta, \frac{{\left(\alpha + \beta\right)}^{2}}{-i}\right)}{i}\right) - 1}\\

\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (/.f64 (/.f64 (*.f64 (*.f64 i (+.f64 (+.f64 alpha beta) i)) (+.f64 (*.f64 beta alpha) (*.f64 i (+.f64 (+.f64 alpha beta) i)))) (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)))) (-.f64 (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i))) #s(literal 1 binary64))) < +inf.0

    1. Initial program 46.1%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + \color{blue}{2 \cdot i}\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
    4. Applied rewrites99.6%

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

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

        \[\leadsto \frac{\frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\alpha + \beta\right) - -2 \cdot i}}{{i}^{2} \cdot \color{blue}{\left(4 + -1 \cdot \frac{-4 \cdot \left(\alpha + \beta\right) + -1 \cdot \frac{{\left(\alpha + \beta\right)}^{2}}{i}}{i}\right)} - 1} \]
      2. unpow2N/A

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

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

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

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

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

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

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

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

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

        \[\leadsto \frac{\frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\alpha + \beta\right) - -2 \cdot i}}{\left(i \cdot i\right) \cdot \left(4 + -1 \cdot \frac{\mathsf{fma}\left(-4, \alpha + \beta, -1 \cdot \frac{{\left(\alpha + \beta\right)}^{2}}{i}\right)}{i}\right) - 1} \]
      12. lift-+.f6499.6

        \[\leadsto \frac{\frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\alpha + \beta\right) - -2 \cdot i}}{\left(i \cdot i\right) \cdot \left(4 + -1 \cdot \frac{\mathsf{fma}\left(-4, \alpha + \beta, -1 \cdot \frac{{\left(\alpha + \beta\right)}^{2}}{i}\right)}{i}\right) - 1} \]
    7. Applied rewrites99.6%

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

    if +inf.0 < (/.f64 (/.f64 (*.f64 (*.f64 i (+.f64 (+.f64 alpha beta) i)) (+.f64 (*.f64 beta alpha) (*.f64 i (+.f64 (+.f64 alpha beta) i)))) (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)))) (-.f64 (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i))) #s(literal 1 binary64)))

    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 i around inf

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

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

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

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

        \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
      5. distribute-lft-outN/A

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

        \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
      7. lift-+.f64N/A

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

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

        \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{\color{blue}{i}} \]
      10. lift-+.f6479.4

        \[\leadsto \left(0.0625 + 0.0625 \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
    5. Applied rewrites79.4%

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

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

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

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

        \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{16}, i, \frac{1}{8} \cdot \left(\alpha + \beta\right)\right)}{i} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
      4. lift-+.f6479.4

        \[\leadsto \frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\alpha + \beta}{i} \]
    8. Applied rewrites79.4%

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{16}, i, \frac{1}{8} \cdot \left(\alpha + \beta\right)\right)}{i} - \frac{1}{8} \cdot \frac{\beta}{i} \]
    10. Step-by-step derivation
      1. Applied rewrites73.4%

        \[\leadsto \frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i} \]
    11. Recombined 2 regimes into one program.
    12. Final simplification83.9%

      \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \leq \infty:\\ \;\;\;\;\frac{\frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\alpha + \beta\right) - -2 \cdot i}}{\left(i \cdot i\right) \cdot \left(4 - \frac{\mathsf{fma}\left(-4, \alpha + \beta, \frac{{\left(\alpha + \beta\right)}^{2}}{-i}\right)}{i}\right) - 1}\\ \mathbf{else}:\\ \;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\ \end{array} \]
    13. Add Preprocessing

    Alternative 2: 83.5% accurate, 0.5× speedup?

    \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_1 := t\_0 \cdot t\_0\\ t_2 := t\_1 - 1\\ t_3 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ t_4 := \left(\alpha + \beta\right) - -2 \cdot i\\ \mathbf{if}\;\frac{\frac{t\_3 \cdot \left(\beta \cdot \alpha + t\_3\right)}{t\_1}}{t\_2} \leq \infty:\\ \;\;\;\;\frac{\frac{t\_3}{t\_4} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, t\_3\right)}{t\_4}}{t\_2}\\ \mathbf{else}:\\ \;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\ \end{array} \end{array} \]
    NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
    (FPCore (alpha beta i)
     :precision binary64
     (let* ((t_0 (+ (+ alpha beta) (* 2.0 i)))
            (t_1 (* t_0 t_0))
            (t_2 (- t_1 1.0))
            (t_3 (* i (+ (+ alpha beta) i)))
            (t_4 (- (+ alpha beta) (* -2.0 i))))
       (if (<= (/ (/ (* t_3 (+ (* beta alpha) t_3)) t_1) t_2) INFINITY)
         (/ (* (/ t_3 t_4) (/ (fma beta alpha t_3) t_4)) t_2)
         (- (/ (fma 0.0625 i (* 0.125 (+ alpha beta))) i) (* 0.125 (/ beta i))))))
    assert(alpha < beta && beta < i);
    double code(double alpha, double beta, double i) {
    	double t_0 = (alpha + beta) + (2.0 * i);
    	double t_1 = t_0 * t_0;
    	double t_2 = t_1 - 1.0;
    	double t_3 = i * ((alpha + beta) + i);
    	double t_4 = (alpha + beta) - (-2.0 * i);
    	double tmp;
    	if ((((t_3 * ((beta * alpha) + t_3)) / t_1) / t_2) <= ((double) INFINITY)) {
    		tmp = ((t_3 / t_4) * (fma(beta, alpha, t_3) / t_4)) / t_2;
    	} else {
    		tmp = (fma(0.0625, i, (0.125 * (alpha + beta))) / i) - (0.125 * (beta / i));
    	}
    	return tmp;
    }
    
    alpha, beta, i = sort([alpha, beta, i])
    function code(alpha, beta, i)
    	t_0 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
    	t_1 = Float64(t_0 * t_0)
    	t_2 = Float64(t_1 - 1.0)
    	t_3 = Float64(i * Float64(Float64(alpha + beta) + i))
    	t_4 = Float64(Float64(alpha + beta) - Float64(-2.0 * i))
    	tmp = 0.0
    	if (Float64(Float64(Float64(t_3 * Float64(Float64(beta * alpha) + t_3)) / t_1) / t_2) <= Inf)
    		tmp = Float64(Float64(Float64(t_3 / t_4) * Float64(fma(beta, alpha, t_3) / t_4)) / t_2);
    	else
    		tmp = Float64(Float64(fma(0.0625, i, Float64(0.125 * Float64(alpha + beta))) / i) - Float64(0.125 * 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_] := Block[{t$95$0 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 - 1.0), $MachinePrecision]}, Block[{t$95$3 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(alpha + beta), $MachinePrecision] - N[(-2.0 * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[(t$95$3 * N[(N[(beta * alpha), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision] / t$95$1), $MachinePrecision] / t$95$2), $MachinePrecision], Infinity], N[(N[(N[(t$95$3 / t$95$4), $MachinePrecision] * N[(N[(beta * alpha + t$95$3), $MachinePrecision] / t$95$4), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision], N[(N[(N[(0.0625 * i + N[(0.125 * N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] - N[(0.125 * N[(beta / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
    
    \begin{array}{l}
    [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
    \\
    \begin{array}{l}
    t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
    t_1 := t\_0 \cdot t\_0\\
    t_2 := t\_1 - 1\\
    t_3 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
    t_4 := \left(\alpha + \beta\right) - -2 \cdot i\\
    \mathbf{if}\;\frac{\frac{t\_3 \cdot \left(\beta \cdot \alpha + t\_3\right)}{t\_1}}{t\_2} \leq \infty:\\
    \;\;\;\;\frac{\frac{t\_3}{t\_4} \cdot \frac{\mathsf{fma}\left(\beta, \alpha, t\_3\right)}{t\_4}}{t\_2}\\
    
    \mathbf{else}:\\
    \;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (/.f64 (/.f64 (*.f64 (*.f64 i (+.f64 (+.f64 alpha beta) i)) (+.f64 (*.f64 beta alpha) (*.f64 i (+.f64 (+.f64 alpha beta) i)))) (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)))) (-.f64 (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i))) #s(literal 1 binary64))) < +inf.0

      1. Initial program 46.1%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

          \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + \color{blue}{2 \cdot i}\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
      4. Applied rewrites99.6%

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

      if +inf.0 < (/.f64 (/.f64 (*.f64 (*.f64 i (+.f64 (+.f64 alpha beta) i)) (+.f64 (*.f64 beta alpha) (*.f64 i (+.f64 (+.f64 alpha beta) i)))) (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)))) (-.f64 (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i))) #s(literal 1 binary64)))

      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 i around inf

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

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

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

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

          \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
        5. distribute-lft-outN/A

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

          \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
        7. lift-+.f64N/A

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

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

          \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{\color{blue}{i}} \]
        10. lift-+.f6479.4

          \[\leadsto \left(0.0625 + 0.0625 \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
      5. Applied rewrites79.4%

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

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

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

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

          \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{16}, i, \frac{1}{8} \cdot \left(\alpha + \beta\right)\right)}{i} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
        4. lift-+.f6479.4

          \[\leadsto \frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\alpha + \beta}{i} \]
      8. Applied rewrites79.4%

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

        \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{16}, i, \frac{1}{8} \cdot \left(\alpha + \beta\right)\right)}{i} - \frac{1}{8} \cdot \frac{\beta}{i} \]
      10. Step-by-step derivation
        1. Applied rewrites73.4%

          \[\leadsto \frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i} \]
      11. Recombined 2 regimes into one program.
      12. Add Preprocessing

      Alternative 3: 83.0% accurate, 0.5× speedup?

      \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\ t_1 := t\_0 \cdot t\_0\\ t_2 := t\_1 - 1\\ t_3 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\ \mathbf{if}\;\frac{\frac{t\_3 \cdot \left(\beta \cdot \alpha + t\_3\right)}{t\_1}}{t\_2} \leq \infty:\\ \;\;\;\;\frac{\frac{t\_3}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{i \cdot \left(\beta + i\right)}{\beta - -2 \cdot i}}{t\_2}\\ \mathbf{else}:\\ \;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\ \end{array} \end{array} \]
      NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
      (FPCore (alpha beta i)
       :precision binary64
       (let* ((t_0 (+ (+ alpha beta) (* 2.0 i)))
              (t_1 (* t_0 t_0))
              (t_2 (- t_1 1.0))
              (t_3 (* i (+ (+ alpha beta) i))))
         (if (<= (/ (/ (* t_3 (+ (* beta alpha) t_3)) t_1) t_2) INFINITY)
           (/
            (*
             (/ t_3 (- (+ alpha beta) (* -2.0 i)))
             (/ (* i (+ beta i)) (- beta (* -2.0 i))))
            t_2)
           (- (/ (fma 0.0625 i (* 0.125 (+ alpha beta))) i) (* 0.125 (/ beta i))))))
      assert(alpha < beta && beta < i);
      double code(double alpha, double beta, double i) {
      	double t_0 = (alpha + beta) + (2.0 * i);
      	double t_1 = t_0 * t_0;
      	double t_2 = t_1 - 1.0;
      	double t_3 = i * ((alpha + beta) + i);
      	double tmp;
      	if ((((t_3 * ((beta * alpha) + t_3)) / t_1) / t_2) <= ((double) INFINITY)) {
      		tmp = ((t_3 / ((alpha + beta) - (-2.0 * i))) * ((i * (beta + i)) / (beta - (-2.0 * i)))) / t_2;
      	} else {
      		tmp = (fma(0.0625, i, (0.125 * (alpha + beta))) / i) - (0.125 * (beta / i));
      	}
      	return tmp;
      }
      
      alpha, beta, i = sort([alpha, beta, i])
      function code(alpha, beta, i)
      	t_0 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
      	t_1 = Float64(t_0 * t_0)
      	t_2 = Float64(t_1 - 1.0)
      	t_3 = Float64(i * Float64(Float64(alpha + beta) + i))
      	tmp = 0.0
      	if (Float64(Float64(Float64(t_3 * Float64(Float64(beta * alpha) + t_3)) / t_1) / t_2) <= Inf)
      		tmp = Float64(Float64(Float64(t_3 / Float64(Float64(alpha + beta) - Float64(-2.0 * i))) * Float64(Float64(i * Float64(beta + i)) / Float64(beta - Float64(-2.0 * i)))) / t_2);
      	else
      		tmp = Float64(Float64(fma(0.0625, i, Float64(0.125 * Float64(alpha + beta))) / i) - Float64(0.125 * 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_] := Block[{t$95$0 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 - 1.0), $MachinePrecision]}, Block[{t$95$3 = N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[(t$95$3 * N[(N[(beta * alpha), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision] / t$95$1), $MachinePrecision] / t$95$2), $MachinePrecision], Infinity], N[(N[(N[(t$95$3 / N[(N[(alpha + beta), $MachinePrecision] - N[(-2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(i * N[(beta + i), $MachinePrecision]), $MachinePrecision] / N[(beta - N[(-2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision], N[(N[(N[(0.0625 * i + N[(0.125 * N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] - N[(0.125 * N[(beta / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
      
      \begin{array}{l}
      [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
      \\
      \begin{array}{l}
      t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
      t_1 := t\_0 \cdot t\_0\\
      t_2 := t\_1 - 1\\
      t_3 := i \cdot \left(\left(\alpha + \beta\right) + i\right)\\
      \mathbf{if}\;\frac{\frac{t\_3 \cdot \left(\beta \cdot \alpha + t\_3\right)}{t\_1}}{t\_2} \leq \infty:\\
      \;\;\;\;\frac{\frac{t\_3}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{i \cdot \left(\beta + i\right)}{\beta - -2 \cdot i}}{t\_2}\\
      
      \mathbf{else}:\\
      \;\;\;\;\frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (/.f64 (/.f64 (*.f64 (*.f64 i (+.f64 (+.f64 alpha beta) i)) (+.f64 (*.f64 beta alpha) (*.f64 i (+.f64 (+.f64 alpha beta) i)))) (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)))) (-.f64 (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i))) #s(literal 1 binary64))) < +inf.0

        1. Initial program 46.1%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + \color{blue}{2 \cdot i}\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        4. Applied rewrites99.6%

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

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

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

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

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

            \[\leadsto \frac{\frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{i \cdot \left(\beta + i\right)}{\beta - \color{blue}{-2 \cdot i}}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
          5. lift-*.f6488.0

            \[\leadsto \frac{\frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) - -2 \cdot i} \cdot \frac{i \cdot \left(\beta + i\right)}{\beta - -2 \cdot \color{blue}{i}}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
        7. Applied rewrites88.0%

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

        if +inf.0 < (/.f64 (/.f64 (*.f64 (*.f64 i (+.f64 (+.f64 alpha beta) i)) (+.f64 (*.f64 beta alpha) (*.f64 i (+.f64 (+.f64 alpha beta) i)))) (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)))) (-.f64 (*.f64 (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i)) (+.f64 (+.f64 alpha beta) (*.f64 #s(literal 2 binary64) i))) #s(literal 1 binary64)))

        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 i around inf

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

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

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

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

            \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \alpha + 2 \cdot \beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          5. distribute-lft-outN/A

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

            \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          7. lift-+.f64N/A

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

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

            \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{\color{blue}{i}} \]
          10. lift-+.f6479.4

            \[\leadsto \left(0.0625 + 0.0625 \cdot \frac{2 \cdot \left(\alpha + \beta\right)}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
        5. Applied rewrites79.4%

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

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

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

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

            \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{16}, i, \frac{1}{8} \cdot \left(\alpha + \beta\right)\right)}{i} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
          4. lift-+.f6479.4

            \[\leadsto \frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\alpha + \beta}{i} \]
        8. Applied rewrites79.4%

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

          \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{16}, i, \frac{1}{8} \cdot \left(\alpha + \beta\right)\right)}{i} - \frac{1}{8} \cdot \frac{\beta}{i} \]
        10. Step-by-step derivation
          1. Applied rewrites73.4%

            \[\leadsto \frac{\mathsf{fma}\left(0.0625, i, 0.125 \cdot \left(\alpha + \beta\right)\right)}{i} - 0.125 \cdot \frac{\beta}{i} \]
        11. Recombined 2 regimes into one program.
        12. Add Preprocessing

        Alternative 4: 85.9% accurate, 3.1× speedup?

        \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 1.1 \cdot 10^{+143}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta} \cdot \frac{\alpha + i}{\beta}\\ \end{array} \end{array} \]
        NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
        (FPCore (alpha beta i)
         :precision binary64
         (if (<= beta 1.1e+143) 0.0625 (* (/ i beta) (/ (+ alpha i) beta))))
        assert(alpha < beta && beta < i);
        double code(double alpha, double beta, double i) {
        	double tmp;
        	if (beta <= 1.1e+143) {
        		tmp = 0.0625;
        	} else {
        		tmp = (i / beta) * ((alpha + i) / beta);
        	}
        	return tmp;
        }
        
        NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
        module fmin_fmax_functions
            implicit none
            private
            public fmax
            public fmin
        
            interface fmax
                module procedure fmax88
                module procedure fmax44
                module procedure fmax84
                module procedure fmax48
            end interface
            interface fmin
                module procedure fmin88
                module procedure fmin44
                module procedure fmin84
                module procedure fmin48
            end interface
        contains
            real(8) function fmax88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(4) function fmax44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(8) function fmax84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmax48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
            end function
            real(8) function fmin88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(4) function fmin44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(8) function fmin84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmin48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
            end function
        end module
        
        real(8) function code(alpha, beta, i)
        use fmin_fmax_functions
            real(8), intent (in) :: alpha
            real(8), intent (in) :: beta
            real(8), intent (in) :: i
            real(8) :: tmp
            if (beta <= 1.1d+143) then
                tmp = 0.0625d0
            else
                tmp = (i / beta) * ((alpha + 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 <= 1.1e+143) {
        		tmp = 0.0625;
        	} else {
        		tmp = (i / beta) * ((alpha + i) / beta);
        	}
        	return tmp;
        }
        
        [alpha, beta, i] = sort([alpha, beta, i])
        def code(alpha, beta, i):
        	tmp = 0
        	if beta <= 1.1e+143:
        		tmp = 0.0625
        	else:
        		tmp = (i / beta) * ((alpha + i) / beta)
        	return tmp
        
        alpha, beta, i = sort([alpha, beta, i])
        function code(alpha, beta, i)
        	tmp = 0.0
        	if (beta <= 1.1e+143)
        		tmp = 0.0625;
        	else
        		tmp = Float64(Float64(i / beta) * Float64(Float64(alpha + 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 <= 1.1e+143)
        		tmp = 0.0625;
        	else
        		tmp = (i / beta) * ((alpha + 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, 1.1e+143], 0.0625, N[(N[(i / beta), $MachinePrecision] * N[(N[(alpha + i), $MachinePrecision] / beta), $MachinePrecision]), $MachinePrecision]]
        
        \begin{array}{l}
        [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
        \\
        \begin{array}{l}
        \mathbf{if}\;\beta \leq 1.1 \cdot 10^{+143}:\\
        \;\;\;\;0.0625\\
        
        \mathbf{else}:\\
        \;\;\;\;\frac{i}{\beta} \cdot \frac{\alpha + i}{\beta}\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if beta < 1.10000000000000007e143

          1. Initial program 21.1%

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

            \[\leadsto \color{blue}{\frac{1}{16}} \]
          4. Step-by-step derivation
            1. Applied rewrites79.5%

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

            if 1.10000000000000007e143 < beta

            1. Initial program 0.2%

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

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

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

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

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

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

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

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

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

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

                \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\alpha + \beta\right)} + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
              11. fp-cancel-sign-sub-invN/A

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

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

                \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\color{blue}{\left(\alpha + \beta\right)} - \left(\mathsf{neg}\left(2\right)\right) \cdot i\right) \cdot \left(\alpha + \beta\right) + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
              14. metadata-evalN/A

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

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

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

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

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

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

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

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

                \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}} \]
              4. pow2N/A

                \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
              5. lift-*.f6423.2

                \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
            7. Applied rewrites23.2%

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

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

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

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

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

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

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

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

                \[\leadsto \frac{i}{\beta} \cdot \frac{\alpha + i}{\color{blue}{\beta}} \]
              9. lift-+.f6464.8

                \[\leadsto \frac{i}{\beta} \cdot \frac{\alpha + i}{\beta} \]
            9. Applied rewrites64.8%

              \[\leadsto \color{blue}{\frac{i}{\beta} \cdot \frac{\alpha + i}{\beta}} \]
          5. Recombined 2 regimes into one program.
          6. Add Preprocessing

          Alternative 5: 75.7% accurate, 3.4× speedup?

          \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 1.25 \cdot 10^{+216}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{i}{\beta} \cdot \frac{\alpha}{\beta}\\ \end{array} \end{array} \]
          NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
          (FPCore (alpha beta i)
           :precision binary64
           (if (<= beta 1.25e+216) 0.0625 (* (/ i beta) (/ alpha beta))))
          assert(alpha < beta && beta < i);
          double code(double alpha, double beta, double i) {
          	double tmp;
          	if (beta <= 1.25e+216) {
          		tmp = 0.0625;
          	} else {
          		tmp = (i / beta) * (alpha / beta);
          	}
          	return tmp;
          }
          
          NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
          module fmin_fmax_functions
              implicit none
              private
              public fmax
              public fmin
          
              interface fmax
                  module procedure fmax88
                  module procedure fmax44
                  module procedure fmax84
                  module procedure fmax48
              end interface
              interface fmin
                  module procedure fmin88
                  module procedure fmin44
                  module procedure fmin84
                  module procedure fmin48
              end interface
          contains
              real(8) function fmax88(x, y) result (res)
                  real(8), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(x, max(x, y), y /= y), x /= x)
              end function
              real(4) function fmax44(x, y) result (res)
                  real(4), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(y, merge(x, max(x, y), y /= y), x /= x)
              end function
              real(8) function fmax84(x, y) result(res)
                  real(8), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
              end function
              real(8) function fmax48(x, y) result(res)
                  real(4), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
              end function
              real(8) function fmin88(x, y) result (res)
                  real(8), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(x, min(x, y), y /= y), x /= x)
              end function
              real(4) function fmin44(x, y) result (res)
                  real(4), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(y, merge(x, min(x, y), y /= y), x /= x)
              end function
              real(8) function fmin84(x, y) result(res)
                  real(8), intent (in) :: x
                  real(4), intent (in) :: y
                  res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
              end function
              real(8) function fmin48(x, y) result(res)
                  real(4), intent (in) :: x
                  real(8), intent (in) :: y
                  res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
              end function
          end module
          
          real(8) function code(alpha, beta, i)
          use fmin_fmax_functions
              real(8), intent (in) :: alpha
              real(8), intent (in) :: beta
              real(8), intent (in) :: i
              real(8) :: tmp
              if (beta <= 1.25d+216) then
                  tmp = 0.0625d0
              else
                  tmp = (i / beta) * (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 <= 1.25e+216) {
          		tmp = 0.0625;
          	} else {
          		tmp = (i / beta) * (alpha / beta);
          	}
          	return tmp;
          }
          
          [alpha, beta, i] = sort([alpha, beta, i])
          def code(alpha, beta, i):
          	tmp = 0
          	if beta <= 1.25e+216:
          		tmp = 0.0625
          	else:
          		tmp = (i / beta) * (alpha / beta)
          	return tmp
          
          alpha, beta, i = sort([alpha, beta, i])
          function code(alpha, beta, i)
          	tmp = 0.0
          	if (beta <= 1.25e+216)
          		tmp = 0.0625;
          	else
          		tmp = Float64(Float64(i / beta) * Float64(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 <= 1.25e+216)
          		tmp = 0.0625;
          	else
          		tmp = (i / beta) * (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, 1.25e+216], 0.0625, N[(N[(i / beta), $MachinePrecision] * N[(alpha / beta), $MachinePrecision]), $MachinePrecision]]
          
          \begin{array}{l}
          [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
          \\
          \begin{array}{l}
          \mathbf{if}\;\beta \leq 1.25 \cdot 10^{+216}:\\
          \;\;\;\;0.0625\\
          
          \mathbf{else}:\\
          \;\;\;\;\frac{i}{\beta} \cdot \frac{\alpha}{\beta}\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if beta < 1.24999999999999995e216

            1. Initial program 19.5%

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

              \[\leadsto \color{blue}{\frac{1}{16}} \]
            4. Step-by-step derivation
              1. Applied rewrites76.7%

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

              if 1.24999999999999995e216 < 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

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

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

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

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

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

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

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

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

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

                  \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\alpha + \beta\right)} + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                11. fp-cancel-sign-sub-invN/A

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

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

                  \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\color{blue}{\left(\alpha + \beta\right)} - \left(\mathsf{neg}\left(2\right)\right) \cdot i\right) \cdot \left(\alpha + \beta\right) + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                14. metadata-evalN/A

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

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

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

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

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

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

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

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

                  \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}} \]
                4. pow2N/A

                  \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                5. lift-*.f6422.2

                  \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
              7. Applied rewrites22.2%

                \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
              8. Taylor expanded in alpha around inf

                \[\leadsto \frac{i \cdot \alpha}{\beta \cdot \beta} \]
              9. Step-by-step derivation
                1. Applied rewrites23.8%

                  \[\leadsto \frac{i \cdot \alpha}{\beta \cdot \beta} \]
                2. Step-by-step derivation
                  1. lift-/.f64N/A

                    \[\leadsto \frac{i \cdot \alpha}{\color{blue}{\beta \cdot \beta}} \]
                  2. lift-*.f64N/A

                    \[\leadsto \frac{i \cdot \alpha}{\color{blue}{\beta} \cdot \beta} \]
                  3. lift-*.f64N/A

                    \[\leadsto \frac{i \cdot \alpha}{\beta \cdot \color{blue}{\beta}} \]
                  4. times-fracN/A

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

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

                    \[\leadsto \frac{i}{\beta} \cdot \frac{\color{blue}{\alpha}}{\beta} \]
                  7. lower-/.f6443.3

                    \[\leadsto \frac{i}{\beta} \cdot \frac{\alpha}{\color{blue}{\beta}} \]
                3. Applied rewrites43.3%

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

              Alternative 6: 71.7% accurate, 3.7× speedup?

              \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;i \leq 7.5 \cdot 10^{+31}:\\ \;\;\;\;i \cdot \frac{\alpha + i}{\beta \cdot \beta}\\ \mathbf{else}:\\ \;\;\;\;0.0625\\ \end{array} \end{array} \]
              NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
              (FPCore (alpha beta i)
               :precision binary64
               (if (<= i 7.5e+31) (* i (/ (+ alpha i) (* beta beta))) 0.0625))
              assert(alpha < beta && beta < i);
              double code(double alpha, double beta, double i) {
              	double tmp;
              	if (i <= 7.5e+31) {
              		tmp = i * ((alpha + i) / (beta * beta));
              	} else {
              		tmp = 0.0625;
              	}
              	return tmp;
              }
              
              NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
              module fmin_fmax_functions
                  implicit none
                  private
                  public fmax
                  public fmin
              
                  interface fmax
                      module procedure fmax88
                      module procedure fmax44
                      module procedure fmax84
                      module procedure fmax48
                  end interface
                  interface fmin
                      module procedure fmin88
                      module procedure fmin44
                      module procedure fmin84
                      module procedure fmin48
                  end interface
              contains
                  real(8) function fmax88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmax44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmax84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmax48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                  end function
                  real(8) function fmin88(x, y) result (res)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(4) function fmin44(x, y) result (res)
                      real(4), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                  end function
                  real(8) function fmin84(x, y) result(res)
                      real(8), intent (in) :: x
                      real(4), intent (in) :: y
                      res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                  end function
                  real(8) function fmin48(x, y) result(res)
                      real(4), intent (in) :: x
                      real(8), intent (in) :: y
                      res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                  end function
              end module
              
              real(8) function code(alpha, beta, i)
              use fmin_fmax_functions
                  real(8), intent (in) :: alpha
                  real(8), intent (in) :: beta
                  real(8), intent (in) :: i
                  real(8) :: tmp
                  if (i <= 7.5d+31) then
                      tmp = i * ((alpha + i) / (beta * beta))
                  else
                      tmp = 0.0625d0
                  end if
                  code = tmp
              end function
              
              assert alpha < beta && beta < i;
              public static double code(double alpha, double beta, double i) {
              	double tmp;
              	if (i <= 7.5e+31) {
              		tmp = i * ((alpha + i) / (beta * beta));
              	} else {
              		tmp = 0.0625;
              	}
              	return tmp;
              }
              
              [alpha, beta, i] = sort([alpha, beta, i])
              def code(alpha, beta, i):
              	tmp = 0
              	if i <= 7.5e+31:
              		tmp = i * ((alpha + i) / (beta * beta))
              	else:
              		tmp = 0.0625
              	return tmp
              
              alpha, beta, i = sort([alpha, beta, i])
              function code(alpha, beta, i)
              	tmp = 0.0
              	if (i <= 7.5e+31)
              		tmp = Float64(i * Float64(Float64(alpha + i) / Float64(beta * beta)));
              	else
              		tmp = 0.0625;
              	end
              	return tmp
              end
              
              alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
              function tmp_2 = code(alpha, beta, i)
              	tmp = 0.0;
              	if (i <= 7.5e+31)
              		tmp = i * ((alpha + i) / (beta * beta));
              	else
              		tmp = 0.0625;
              	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[i, 7.5e+31], N[(i * N[(N[(alpha + i), $MachinePrecision] / N[(beta * beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 0.0625]
              
              \begin{array}{l}
              [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
              \\
              \begin{array}{l}
              \mathbf{if}\;i \leq 7.5 \cdot 10^{+31}:\\
              \;\;\;\;i \cdot \frac{\alpha + i}{\beta \cdot \beta}\\
              
              \mathbf{else}:\\
              \;\;\;\;0.0625\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if i < 7.5e31

                1. Initial program 71.0%

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

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

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

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

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

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

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

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

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

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

                    \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\alpha + \beta\right)} + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                  11. fp-cancel-sign-sub-invN/A

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

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

                    \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\color{blue}{\left(\alpha + \beta\right)} - \left(\mathsf{neg}\left(2\right)\right) \cdot i\right) \cdot \left(\alpha + \beta\right) + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                  14. metadata-evalN/A

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

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

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

                    \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) - -2 \cdot i\right) \cdot \left(\alpha + \beta\right) + \color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                4. Applied rewrites71.1%

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

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

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

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

                    \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}} \]
                  4. pow2N/A

                    \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                  5. lift-*.f6422.9

                    \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                7. Applied rewrites22.9%

                  \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
                8. Taylor expanded in i around 0

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

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

                    \[\leadsto i \cdot \frac{\alpha + i}{{\beta}^{\color{blue}{2}}} \]
                  3. lower-/.f64N/A

                    \[\leadsto i \cdot \frac{\alpha + i}{{\beta}^{\color{blue}{2}}} \]
                  4. lift-+.f64N/A

                    \[\leadsto i \cdot \frac{\alpha + i}{{\beta}^{2}} \]
                  5. pow2N/A

                    \[\leadsto i \cdot \frac{\alpha + i}{\beta \cdot \beta} \]
                  6. lift-*.f6422.9

                    \[\leadsto i \cdot \frac{\alpha + i}{\beta \cdot \beta} \]
                10. Applied rewrites22.9%

                  \[\leadsto i \cdot \color{blue}{\frac{\alpha + i}{\beta \cdot \beta}} \]

                if 7.5e31 < i

                1. Initial program 12.1%

                  \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                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%

                    \[\leadsto \color{blue}{0.0625} \]
                5. Recombined 2 regimes into one program.
                6. Add Preprocessing

                Alternative 7: 71.7% accurate, 3.7× speedup?

                \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;i \leq 7.5 \cdot 10^{+31}:\\ \;\;\;\;\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}\\ \mathbf{else}:\\ \;\;\;\;0.0625\\ \end{array} \end{array} \]
                NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                (FPCore (alpha beta i)
                 :precision binary64
                 (if (<= i 7.5e+31) (/ (* i (+ alpha i)) (* beta beta)) 0.0625))
                assert(alpha < beta && beta < i);
                double code(double alpha, double beta, double i) {
                	double tmp;
                	if (i <= 7.5e+31) {
                		tmp = (i * (alpha + i)) / (beta * beta);
                	} else {
                		tmp = 0.0625;
                	}
                	return tmp;
                }
                
                NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                module fmin_fmax_functions
                    implicit none
                    private
                    public fmax
                    public fmin
                
                    interface fmax
                        module procedure fmax88
                        module procedure fmax44
                        module procedure fmax84
                        module procedure fmax48
                    end interface
                    interface fmin
                        module procedure fmin88
                        module procedure fmin44
                        module procedure fmin84
                        module procedure fmin48
                    end interface
                contains
                    real(8) function fmax88(x, y) result (res)
                        real(8), intent (in) :: x
                        real(8), intent (in) :: y
                        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                    end function
                    real(4) function fmax44(x, y) result (res)
                        real(4), intent (in) :: x
                        real(4), intent (in) :: y
                        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                    end function
                    real(8) function fmax84(x, y) result(res)
                        real(8), intent (in) :: x
                        real(4), intent (in) :: y
                        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                    end function
                    real(8) function fmax48(x, y) result(res)
                        real(4), intent (in) :: x
                        real(8), intent (in) :: y
                        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                    end function
                    real(8) function fmin88(x, y) result (res)
                        real(8), intent (in) :: x
                        real(8), intent (in) :: y
                        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                    end function
                    real(4) function fmin44(x, y) result (res)
                        real(4), intent (in) :: x
                        real(4), intent (in) :: y
                        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                    end function
                    real(8) function fmin84(x, y) result(res)
                        real(8), intent (in) :: x
                        real(4), intent (in) :: y
                        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                    end function
                    real(8) function fmin48(x, y) result(res)
                        real(4), intent (in) :: x
                        real(8), intent (in) :: y
                        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                    end function
                end module
                
                real(8) function code(alpha, beta, i)
                use fmin_fmax_functions
                    real(8), intent (in) :: alpha
                    real(8), intent (in) :: beta
                    real(8), intent (in) :: i
                    real(8) :: tmp
                    if (i <= 7.5d+31) then
                        tmp = (i * (alpha + i)) / (beta * beta)
                    else
                        tmp = 0.0625d0
                    end if
                    code = tmp
                end function
                
                assert alpha < beta && beta < i;
                public static double code(double alpha, double beta, double i) {
                	double tmp;
                	if (i <= 7.5e+31) {
                		tmp = (i * (alpha + i)) / (beta * beta);
                	} else {
                		tmp = 0.0625;
                	}
                	return tmp;
                }
                
                [alpha, beta, i] = sort([alpha, beta, i])
                def code(alpha, beta, i):
                	tmp = 0
                	if i <= 7.5e+31:
                		tmp = (i * (alpha + i)) / (beta * beta)
                	else:
                		tmp = 0.0625
                	return tmp
                
                alpha, beta, i = sort([alpha, beta, i])
                function code(alpha, beta, i)
                	tmp = 0.0
                	if (i <= 7.5e+31)
                		tmp = Float64(Float64(i * Float64(alpha + i)) / Float64(beta * beta));
                	else
                		tmp = 0.0625;
                	end
                	return tmp
                end
                
                alpha, beta, i = num2cell(sort([alpha, beta, i])){:}
                function tmp_2 = code(alpha, beta, i)
                	tmp = 0.0;
                	if (i <= 7.5e+31)
                		tmp = (i * (alpha + i)) / (beta * beta);
                	else
                		tmp = 0.0625;
                	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[i, 7.5e+31], N[(N[(i * N[(alpha + i), $MachinePrecision]), $MachinePrecision] / N[(beta * beta), $MachinePrecision]), $MachinePrecision], 0.0625]
                
                \begin{array}{l}
                [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                \\
                \begin{array}{l}
                \mathbf{if}\;i \leq 7.5 \cdot 10^{+31}:\\
                \;\;\;\;\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}\\
                
                \mathbf{else}:\\
                \;\;\;\;0.0625\\
                
                
                \end{array}
                \end{array}
                
                Derivation
                1. Split input into 2 regimes
                2. if i < 7.5e31

                  1. Initial program 71.0%

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

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

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

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

                      \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                    5. lower-*.f6422.9

                      \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                  5. Applied rewrites22.9%

                    \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]

                  if 7.5e31 < i

                  1. Initial program 12.1%

                    \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                  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%

                      \[\leadsto \color{blue}{0.0625} \]
                  5. Recombined 2 regimes into one program.
                  6. Add Preprocessing

                  Alternative 8: 74.3% accurate, 4.1× speedup?

                  \[\begin{array}{l} [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\ \\ \begin{array}{l} \mathbf{if}\;\beta \leq 10^{+230}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\alpha \cdot \frac{i}{\beta \cdot \beta}\\ \end{array} \end{array} \]
                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                  (FPCore (alpha beta i)
                   :precision binary64
                   (if (<= beta 1e+230) 0.0625 (* alpha (/ i (* beta beta)))))
                  assert(alpha < beta && beta < i);
                  double code(double alpha, double beta, double i) {
                  	double tmp;
                  	if (beta <= 1e+230) {
                  		tmp = 0.0625;
                  	} else {
                  		tmp = alpha * (i / (beta * beta));
                  	}
                  	return tmp;
                  }
                  
                  NOTE: alpha, beta, and i should be sorted in increasing order before calling this function.
                  module fmin_fmax_functions
                      implicit none
                      private
                      public fmax
                      public fmin
                  
                      interface fmax
                          module procedure fmax88
                          module procedure fmax44
                          module procedure fmax84
                          module procedure fmax48
                      end interface
                      interface fmin
                          module procedure fmin88
                          module procedure fmin44
                          module procedure fmin84
                          module procedure fmin48
                      end interface
                  contains
                      real(8) function fmax88(x, y) result (res)
                          real(8), intent (in) :: x
                          real(8), intent (in) :: y
                          res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                      end function
                      real(4) function fmax44(x, y) result (res)
                          real(4), intent (in) :: x
                          real(4), intent (in) :: y
                          res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                      end function
                      real(8) function fmax84(x, y) result(res)
                          real(8), intent (in) :: x
                          real(4), intent (in) :: y
                          res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                      end function
                      real(8) function fmax48(x, y) result(res)
                          real(4), intent (in) :: x
                          real(8), intent (in) :: y
                          res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                      end function
                      real(8) function fmin88(x, y) result (res)
                          real(8), intent (in) :: x
                          real(8), intent (in) :: y
                          res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                      end function
                      real(4) function fmin44(x, y) result (res)
                          real(4), intent (in) :: x
                          real(4), intent (in) :: y
                          res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                      end function
                      real(8) function fmin84(x, y) result(res)
                          real(8), intent (in) :: x
                          real(4), intent (in) :: y
                          res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                      end function
                      real(8) function fmin48(x, y) result(res)
                          real(4), intent (in) :: x
                          real(8), intent (in) :: y
                          res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                      end function
                  end module
                  
                  real(8) function code(alpha, beta, i)
                  use fmin_fmax_functions
                      real(8), intent (in) :: alpha
                      real(8), intent (in) :: beta
                      real(8), intent (in) :: i
                      real(8) :: tmp
                      if (beta <= 1d+230) then
                          tmp = 0.0625d0
                      else
                          tmp = alpha * (i / (beta * 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 <= 1e+230) {
                  		tmp = 0.0625;
                  	} else {
                  		tmp = alpha * (i / (beta * beta));
                  	}
                  	return tmp;
                  }
                  
                  [alpha, beta, i] = sort([alpha, beta, i])
                  def code(alpha, beta, i):
                  	tmp = 0
                  	if beta <= 1e+230:
                  		tmp = 0.0625
                  	else:
                  		tmp = alpha * (i / (beta * beta))
                  	return tmp
                  
                  alpha, beta, i = sort([alpha, beta, i])
                  function code(alpha, beta, i)
                  	tmp = 0.0
                  	if (beta <= 1e+230)
                  		tmp = 0.0625;
                  	else
                  		tmp = Float64(alpha * Float64(i / Float64(beta * 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 <= 1e+230)
                  		tmp = 0.0625;
                  	else
                  		tmp = alpha * (i / (beta * 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, 1e+230], 0.0625, N[(alpha * N[(i / N[(beta * beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
                  
                  \begin{array}{l}
                  [alpha, beta, i] = \mathsf{sort}([alpha, beta, i])\\
                  \\
                  \begin{array}{l}
                  \mathbf{if}\;\beta \leq 10^{+230}:\\
                  \;\;\;\;0.0625\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;\alpha \cdot \frac{i}{\beta \cdot \beta}\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if beta < 1.0000000000000001e230

                    1. Initial program 19.4%

                      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                    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 1.0000000000000001e230 < 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

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

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

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

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

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

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

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

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

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

                          \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\alpha + \beta\right)} + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                        11. fp-cancel-sign-sub-invN/A

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

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

                          \[\leadsto \frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\color{blue}{\left(\alpha + \beta\right)} - \left(\mathsf{neg}\left(2\right)\right) \cdot i\right) \cdot \left(\alpha + \beta\right) + \left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1} \]
                        14. metadata-evalN/A

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

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

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

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

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

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

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

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

                          \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{{\beta}^{2}} \]
                        4. pow2N/A

                          \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                        5. lift-*.f6426.3

                          \[\leadsto \frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \color{blue}{\beta}} \]
                      7. Applied rewrites26.3%

                        \[\leadsto \color{blue}{\frac{i \cdot \left(\alpha + i\right)}{\beta \cdot \beta}} \]
                      8. Taylor expanded in alpha around inf

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

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

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

                          \[\leadsto \alpha \cdot \left(\frac{i}{{\beta}^{2}} + \frac{{i}^{2}}{\color{blue}{\alpha} \cdot {\beta}^{2}}\right) \]
                        4. pow2N/A

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

                          \[\leadsto \alpha \cdot \left(\frac{i}{\beta \cdot \beta} + \frac{{i}^{2}}{\alpha \cdot {\beta}^{2}}\right) \]
                        6. lower-/.f64N/A

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

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

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

                          \[\leadsto \alpha \cdot \left(\frac{i}{\beta \cdot \beta} + \frac{i \cdot i}{\alpha \cdot {\beta}^{\color{blue}{2}}}\right) \]
                        10. pow2N/A

                          \[\leadsto \alpha \cdot \left(\frac{i}{\beta \cdot \beta} + \frac{i \cdot i}{\alpha \cdot \left(\beta \cdot \beta\right)}\right) \]
                        11. lift-*.f6427.2

                          \[\leadsto \alpha \cdot \left(\frac{i}{\beta \cdot \beta} + \frac{i \cdot i}{\alpha \cdot \left(\beta \cdot \beta\right)}\right) \]
                      10. Applied rewrites27.2%

                        \[\leadsto \alpha \cdot \color{blue}{\left(\frac{i}{\beta \cdot \beta} + \frac{i \cdot i}{\alpha \cdot \left(\beta \cdot \beta\right)}\right)} \]
                      11. Taylor expanded in alpha around inf

                        \[\leadsto \alpha \cdot \frac{i}{{\beta}^{\color{blue}{2}}} \]
                      12. Step-by-step derivation
                        1. pow2N/A

                          \[\leadsto \alpha \cdot \frac{i}{\beta \cdot \beta} \]
                        2. lift-*.f64N/A

                          \[\leadsto \alpha \cdot \frac{i}{\beta \cdot \beta} \]
                        3. lift-/.f6429.4

                          \[\leadsto \alpha \cdot \frac{i}{\beta \cdot \beta} \]
                      13. Applied rewrites29.4%

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

                    Alternative 9: 71.2% 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.
                    module fmin_fmax_functions
                        implicit none
                        private
                        public fmax
                        public fmin
                    
                        interface fmax
                            module procedure fmax88
                            module procedure fmax44
                            module procedure fmax84
                            module procedure fmax48
                        end interface
                        interface fmin
                            module procedure fmin88
                            module procedure fmin44
                            module procedure fmin84
                            module procedure fmin48
                        end interface
                    contains
                        real(8) function fmax88(x, y) result (res)
                            real(8), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                        end function
                        real(4) function fmax44(x, y) result (res)
                            real(4), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                        end function
                        real(8) function fmax84(x, y) result(res)
                            real(8), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                        end function
                        real(8) function fmax48(x, y) result(res)
                            real(4), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                        end function
                        real(8) function fmin88(x, y) result (res)
                            real(8), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                        end function
                        real(4) function fmin44(x, y) result (res)
                            real(4), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                        end function
                        real(8) function fmin84(x, y) result(res)
                            real(8), intent (in) :: x
                            real(4), intent (in) :: y
                            res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                        end function
                        real(8) function fmin48(x, y) result(res)
                            real(4), intent (in) :: x
                            real(8), intent (in) :: y
                            res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                        end function
                    end module
                    
                    real(8) function code(alpha, beta, i)
                    use fmin_fmax_functions
                        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 18.5%

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

                      \[\leadsto \color{blue}{\frac{1}{16}} \]
                    4. Step-by-step derivation
                      1. Applied rewrites73.4%

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

                      Reproduce

                      ?
                      herbie shell --seed 2025027 
                      (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)))