Octave 3.8, jcobi/4

Percentage Accurate: 16.5% → 99.6%
Time: 6.3s
Alternatives: 13
Speedup: 75.4×

Specification

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

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 13 alternatives:

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

Initial Program: 16.5% accurate, 1.0× speedup?

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

Alternative 1: 99.6% accurate, 0.8× speedup?

\[\begin{array}{l} t_0 := \left(\left(\alpha + i\right) + \beta\right) + i\\ t_1 := \frac{i}{t\_0}\\ t_2 := \left(\beta + \alpha\right) + i\\ \frac{\mathsf{fma}\left(t\_1, t\_2, \beta \cdot \frac{\alpha}{t\_0}\right)}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (+ (+ (+ alpha i) beta) i))
        (t_1 (/ i t_0))
        (t_2 (+ (+ beta alpha) i)))
   (*
    (/ (fma t_1 t_2 (* beta (/ alpha t_0))) (- t_0 1.0))
    (/ (* t_2 t_1) (- t_0 -1.0)))))
double code(double alpha, double beta, double i) {
	double t_0 = ((alpha + i) + beta) + i;
	double t_1 = i / t_0;
	double t_2 = (beta + alpha) + i;
	return (fma(t_1, t_2, (beta * (alpha / t_0))) / (t_0 - 1.0)) * ((t_2 * t_1) / (t_0 - -1.0));
}
function code(alpha, beta, i)
	t_0 = Float64(Float64(Float64(alpha + i) + beta) + i)
	t_1 = Float64(i / t_0)
	t_2 = Float64(Float64(beta + alpha) + i)
	return Float64(Float64(fma(t_1, t_2, Float64(beta * Float64(alpha / t_0))) / Float64(t_0 - 1.0)) * Float64(Float64(t_2 * t_1) / Float64(t_0 - -1.0)))
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(N[(N[(alpha + i), $MachinePrecision] + beta), $MachinePrecision] + i), $MachinePrecision]}, Block[{t$95$1 = N[(i / t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(beta + alpha), $MachinePrecision] + i), $MachinePrecision]}, N[(N[(N[(t$95$1 * t$95$2 + N[(beta * N[(alpha / t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t$95$0 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(t$95$2 * t$95$1), $MachinePrecision] / N[(t$95$0 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
t_0 := \left(\left(\alpha + i\right) + \beta\right) + i\\
t_1 := \frac{i}{t\_0}\\
t_2 := \left(\beta + \alpha\right) + i\\
\frac{\mathsf{fma}\left(t\_1, t\_2, \beta \cdot \frac{\alpha}{t\_0}\right)}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1}
\end{array}
Derivation
  1. Initial program 16.5%

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

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

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

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

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

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

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

      \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
  3. Applied rewrites42.6%

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}, \left(\beta + \alpha\right) + i, \color{blue}{\beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    11. lower-/.f6499.6%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.7%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.7%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.7%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.6%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}}{\left(\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i\right) - -1} \]
    12. lower-+.f6499.6%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}}{\left(\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i\right) - -1} \]
    18. lower-+.f6499.6%

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

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

Alternative 2: 99.6% accurate, 0.9× speedup?

\[\begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \beta + \alpha\right)\\ t_1 := \frac{i}{t\_0}\\ t_2 := \left(\beta + \alpha\right) + i\\ \frac{\mathsf{fma}\left(t\_1, t\_2, \beta \cdot \frac{\alpha}{t\_0}\right)}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (fma 2.0 i (+ beta alpha)))
        (t_1 (/ i t_0))
        (t_2 (+ (+ beta alpha) i)))
   (*
    (/ (fma t_1 t_2 (* beta (/ alpha t_0))) (- t_0 1.0))
    (/ (* t_2 t_1) (- t_0 -1.0)))))
double code(double alpha, double beta, double i) {
	double t_0 = fma(2.0, i, (beta + alpha));
	double t_1 = i / t_0;
	double t_2 = (beta + alpha) + i;
	return (fma(t_1, t_2, (beta * (alpha / t_0))) / (t_0 - 1.0)) * ((t_2 * t_1) / (t_0 - -1.0));
}
function code(alpha, beta, i)
	t_0 = fma(2.0, i, Float64(beta + alpha))
	t_1 = Float64(i / t_0)
	t_2 = Float64(Float64(beta + alpha) + i)
	return Float64(Float64(fma(t_1, t_2, Float64(beta * Float64(alpha / t_0))) / Float64(t_0 - 1.0)) * Float64(Float64(t_2 * t_1) / Float64(t_0 - -1.0)))
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[(beta + alpha), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(i / t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(beta + alpha), $MachinePrecision] + i), $MachinePrecision]}, N[(N[(N[(t$95$1 * t$95$2 + N[(beta * N[(alpha / t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t$95$0 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(t$95$2 * t$95$1), $MachinePrecision] / N[(t$95$0 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
t_0 := \mathsf{fma}\left(2, i, \beta + \alpha\right)\\
t_1 := \frac{i}{t\_0}\\
t_2 := \left(\beta + \alpha\right) + i\\
\frac{\mathsf{fma}\left(t\_1, t\_2, \beta \cdot \frac{\alpha}{t\_0}\right)}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1}
\end{array}
Derivation
  1. Initial program 16.5%

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

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

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

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

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

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

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

      \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
  3. Applied rewrites42.6%

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}, \left(\beta + \alpha\right) + i, \color{blue}{\beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    11. lower-/.f6499.6%

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

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

Alternative 3: 99.6% accurate, 0.9× speedup?

\[\begin{array}{l} t_0 := \left(\beta + \alpha\right) + i\\ t_1 := \mathsf{fma}\left(2, i, \beta + \alpha\right)\\ \frac{\mathsf{fma}\left(i, \frac{t\_0}{t\_1}, \beta \cdot \frac{\alpha}{t\_1}\right)}{t\_1 - 1} \cdot \frac{t\_0 \cdot \frac{i}{t\_1}}{t\_1 - -1} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (+ (+ beta alpha) i)) (t_1 (fma 2.0 i (+ beta alpha))))
   (*
    (/ (fma i (/ t_0 t_1) (* beta (/ alpha t_1))) (- t_1 1.0))
    (/ (* t_0 (/ i t_1)) (- t_1 -1.0)))))
double code(double alpha, double beta, double i) {
	double t_0 = (beta + alpha) + i;
	double t_1 = fma(2.0, i, (beta + alpha));
	return (fma(i, (t_0 / t_1), (beta * (alpha / t_1))) / (t_1 - 1.0)) * ((t_0 * (i / t_1)) / (t_1 - -1.0));
}
function code(alpha, beta, i)
	t_0 = Float64(Float64(beta + alpha) + i)
	t_1 = fma(2.0, i, Float64(beta + alpha))
	return Float64(Float64(fma(i, Float64(t_0 / t_1), Float64(beta * Float64(alpha / t_1))) / Float64(t_1 - 1.0)) * Float64(Float64(t_0 * Float64(i / t_1)) / Float64(t_1 - -1.0)))
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(N[(beta + alpha), $MachinePrecision] + i), $MachinePrecision]}, Block[{t$95$1 = N[(2.0 * i + N[(beta + alpha), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[(i * N[(t$95$0 / t$95$1), $MachinePrecision] + N[(beta * N[(alpha / t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t$95$1 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(t$95$0 * N[(i / t$95$1), $MachinePrecision]), $MachinePrecision] / N[(t$95$1 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
t_0 := \left(\beta + \alpha\right) + i\\
t_1 := \mathsf{fma}\left(2, i, \beta + \alpha\right)\\
\frac{\mathsf{fma}\left(i, \frac{t\_0}{t\_1}, \beta \cdot \frac{\alpha}{t\_1}\right)}{t\_1 - 1} \cdot \frac{t\_0 \cdot \frac{i}{t\_1}}{t\_1 - -1}
\end{array}
Derivation
  1. Initial program 16.5%

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

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

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

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

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

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

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

      \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
  3. Applied rewrites42.6%

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(i, \frac{\left(\beta + \alpha\right) + i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}, \color{blue}{\beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    11. lower-/.f6499.6%

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

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

Alternative 4: 99.3% accurate, 0.7× speedup?

\[\begin{array}{l} t_0 := \left(i + \mathsf{max}\left(\alpha, \beta\right)\right) + i\\ t_1 := \frac{i}{t\_0}\\ t_2 := \left(\mathsf{max}\left(\alpha, \beta\right) + \mathsf{min}\left(\alpha, \beta\right)\right) + i\\ \frac{\mathsf{fma}\left(t\_1, t\_2, \mathsf{max}\left(\alpha, \beta\right) \cdot \frac{\mathsf{min}\left(\alpha, \beta\right)}{t\_0}\right)}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1} \end{array} \]
(FPCore (alpha beta i)
 :precision binary64
 (let* ((t_0 (+ (+ i (fmax alpha beta)) i))
        (t_1 (/ i t_0))
        (t_2 (+ (+ (fmax alpha beta) (fmin alpha beta)) i)))
   (*
    (/
     (fma t_1 t_2 (* (fmax alpha beta) (/ (fmin alpha beta) t_0)))
     (- t_0 1.0))
    (/ (* t_2 t_1) (- t_0 -1.0)))))
double code(double alpha, double beta, double i) {
	double t_0 = (i + fmax(alpha, beta)) + i;
	double t_1 = i / t_0;
	double t_2 = (fmax(alpha, beta) + fmin(alpha, beta)) + i;
	return (fma(t_1, t_2, (fmax(alpha, beta) * (fmin(alpha, beta) / t_0))) / (t_0 - 1.0)) * ((t_2 * t_1) / (t_0 - -1.0));
}
function code(alpha, beta, i)
	t_0 = Float64(Float64(i + fmax(alpha, beta)) + i)
	t_1 = Float64(i / t_0)
	t_2 = Float64(Float64(fmax(alpha, beta) + fmin(alpha, beta)) + i)
	return Float64(Float64(fma(t_1, t_2, Float64(fmax(alpha, beta) * Float64(fmin(alpha, beta) / t_0))) / Float64(t_0 - 1.0)) * Float64(Float64(t_2 * t_1) / Float64(t_0 - -1.0)))
end
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(N[(i + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision] + i), $MachinePrecision]}, Block[{t$95$1 = N[(i / t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Max[alpha, beta], $MachinePrecision] + N[Min[alpha, beta], $MachinePrecision]), $MachinePrecision] + i), $MachinePrecision]}, N[(N[(N[(t$95$1 * t$95$2 + N[(N[Max[alpha, beta], $MachinePrecision] * N[(N[Min[alpha, beta], $MachinePrecision] / t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t$95$0 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(t$95$2 * t$95$1), $MachinePrecision] / N[(t$95$0 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
t_0 := \left(i + \mathsf{max}\left(\alpha, \beta\right)\right) + i\\
t_1 := \frac{i}{t\_0}\\
t_2 := \left(\mathsf{max}\left(\alpha, \beta\right) + \mathsf{min}\left(\alpha, \beta\right)\right) + i\\
\frac{\mathsf{fma}\left(t\_1, t\_2, \mathsf{max}\left(\alpha, \beta\right) \cdot \frac{\mathsf{min}\left(\alpha, \beta\right)}{t\_0}\right)}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1}
\end{array}
Derivation
  1. Initial program 16.5%

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

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

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

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

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

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

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

      \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
  3. Applied rewrites42.6%

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}, \left(\beta + \alpha\right) + i, \color{blue}{\beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    11. lower-/.f6499.6%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.7%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i}\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.7%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.7%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    12. lower-+.f6499.7%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
    18. lower-+.f6499.6%

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

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}}{\left(\left(\color{blue}{\left(\beta + \alpha\right)} + i\right) + i\right) - -1} \]
    12. lower-+.f6499.6%

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

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

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

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

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

      \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}}{\left(\color{blue}{\left(\left(\alpha + i\right) + \beta\right)} + i\right) - -1} \]
    18. lower-+.f6499.6%

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

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

    \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(\color{blue}{i} + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(\left(\alpha + i\right) + \beta\right) + i}\right)}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - -1} \]
  17. Step-by-step derivation
    1. Applied rewrites86.2%

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

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

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

        \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(i + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(i + \beta\right) + i}\right)}{\left(\left(\color{blue}{i} + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\left(\alpha + i\right) + \beta\right) + i}}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - -1} \]
      3. Step-by-step derivation
        1. Applied rewrites84.9%

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

          \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(i + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(i + \beta\right) + i}\right)}{\left(\left(i + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(\color{blue}{i} + \beta\right) + i}}{\left(\left(\left(\alpha + i\right) + \beta\right) + i\right) - -1} \]
        3. Step-by-step derivation
          1. Applied rewrites84.7%

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

            \[\leadsto \frac{\mathsf{fma}\left(\frac{i}{\left(i + \beta\right) + i}, \left(\beta + \alpha\right) + i, \beta \cdot \frac{\alpha}{\left(i + \beta\right) + i}\right)}{\left(\left(i + \beta\right) + i\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\left(i + \beta\right) + i}}{\left(\left(\color{blue}{i} + \beta\right) + i\right) - -1} \]
          3. Step-by-step derivation
            1. Applied rewrites84.6%

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

            Alternative 5: 96.6% accurate, 1.1× speedup?

            \[\begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\ t_1 := \frac{i}{t\_0}\\ t_2 := \mathsf{max}\left(\alpha, \beta\right) + i\\ \frac{t\_1 \cdot t\_2}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1} \end{array} \]
            (FPCore (alpha beta i)
             :precision binary64
             (let* ((t_0 (fma 2.0 i (fmax alpha beta)))
                    (t_1 (/ i t_0))
                    (t_2 (+ (fmax alpha beta) i)))
               (* (/ (* t_1 t_2) (- t_0 1.0)) (/ (* t_2 t_1) (- t_0 -1.0)))))
            double code(double alpha, double beta, double i) {
            	double t_0 = fma(2.0, i, fmax(alpha, beta));
            	double t_1 = i / t_0;
            	double t_2 = fmax(alpha, beta) + i;
            	return ((t_1 * t_2) / (t_0 - 1.0)) * ((t_2 * t_1) / (t_0 - -1.0));
            }
            
            function code(alpha, beta, i)
            	t_0 = fma(2.0, i, fmax(alpha, beta))
            	t_1 = Float64(i / t_0)
            	t_2 = Float64(fmax(alpha, beta) + i)
            	return Float64(Float64(Float64(t_1 * t_2) / Float64(t_0 - 1.0)) * Float64(Float64(t_2 * t_1) / Float64(t_0 - -1.0)))
            end
            
            code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(i / t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[Max[alpha, beta], $MachinePrecision] + i), $MachinePrecision]}, N[(N[(N[(t$95$1 * t$95$2), $MachinePrecision] / N[(t$95$0 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(t$95$2 * t$95$1), $MachinePrecision] / N[(t$95$0 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
            
            \begin{array}{l}
            t_0 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\
            t_1 := \frac{i}{t\_0}\\
            t_2 := \mathsf{max}\left(\alpha, \beta\right) + i\\
            \frac{t\_1 \cdot t\_2}{t\_0 - 1} \cdot \frac{t\_2 \cdot t\_1}{t\_0 - -1}
            \end{array}
            
            Derivation
            1. Initial program 16.5%

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

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

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

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

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

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

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

                \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
            3. Applied rewrites42.6%

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

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

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

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

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

                \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + \color{blue}{2 \cdot i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
              5. lower-*.f6440.3%

                \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot \color{blue}{i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
            6. Applied rewrites40.3%

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

              \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
            8. Step-by-step derivation
              1. Applied rewrites36.5%

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

                \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\color{blue}{\beta} + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
              3. Step-by-step derivation
                1. Applied rewrites40.2%

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

                  \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                3. Step-by-step derivation
                  1. Applied rewrites36.4%

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

                    \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - -1} \]
                  3. Step-by-step derivation
                    1. Applied rewrites36.2%

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

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

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

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

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

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

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

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

                        \[\leadsto \frac{\frac{i}{\mathsf{fma}\left(2, i, \beta\right)} \cdot \left(\color{blue}{\beta} + i\right)}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                      9. lower-*.f6483.9%

                        \[\leadsto \frac{\frac{i}{\mathsf{fma}\left(2, i, \beta\right)} \cdot \color{blue}{\left(\beta + i\right)}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                    3. Applied rewrites83.9%

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

                    Alternative 6: 96.6% accurate, 1.1× speedup?

                    \[\begin{array}{l} t_0 := \mathsf{max}\left(\alpha, \beta\right) + i\\ t_1 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\ \frac{i \cdot \frac{t\_0}{t\_1}}{t\_1 - 1} \cdot \frac{t\_0 \cdot \frac{i}{t\_1}}{t\_1 - -1} \end{array} \]
                    (FPCore (alpha beta i)
                     :precision binary64
                     (let* ((t_0 (+ (fmax alpha beta) i)) (t_1 (fma 2.0 i (fmax alpha beta))))
                       (* (/ (* i (/ t_0 t_1)) (- t_1 1.0)) (/ (* t_0 (/ i t_1)) (- t_1 -1.0)))))
                    double code(double alpha, double beta, double i) {
                    	double t_0 = fmax(alpha, beta) + i;
                    	double t_1 = fma(2.0, i, fmax(alpha, beta));
                    	return ((i * (t_0 / t_1)) / (t_1 - 1.0)) * ((t_0 * (i / t_1)) / (t_1 - -1.0));
                    }
                    
                    function code(alpha, beta, i)
                    	t_0 = Float64(fmax(alpha, beta) + i)
                    	t_1 = fma(2.0, i, fmax(alpha, beta))
                    	return Float64(Float64(Float64(i * Float64(t_0 / t_1)) / Float64(t_1 - 1.0)) * Float64(Float64(t_0 * Float64(i / t_1)) / Float64(t_1 - -1.0)))
                    end
                    
                    code[alpha_, beta_, i_] := Block[{t$95$0 = N[(N[Max[alpha, beta], $MachinePrecision] + i), $MachinePrecision]}, Block[{t$95$1 = N[(2.0 * i + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[(i * N[(t$95$0 / t$95$1), $MachinePrecision]), $MachinePrecision] / N[(t$95$1 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(t$95$0 * N[(i / t$95$1), $MachinePrecision]), $MachinePrecision] / N[(t$95$1 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
                    
                    \begin{array}{l}
                    t_0 := \mathsf{max}\left(\alpha, \beta\right) + i\\
                    t_1 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\
                    \frac{i \cdot \frac{t\_0}{t\_1}}{t\_1 - 1} \cdot \frac{t\_0 \cdot \frac{i}{t\_1}}{t\_1 - -1}
                    \end{array}
                    
                    Derivation
                    1. Initial program 16.5%

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

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

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

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

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

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

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

                        \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
                    3. Applied rewrites42.6%

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

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

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

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

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

                        \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + \color{blue}{2 \cdot i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                      5. lower-*.f6440.3%

                        \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot \color{blue}{i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                    6. Applied rewrites40.3%

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

                      \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                    8. Step-by-step derivation
                      1. Applied rewrites36.5%

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

                        \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\color{blue}{\beta} + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                      3. Step-by-step derivation
                        1. Applied rewrites40.2%

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

                          \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                        3. Step-by-step derivation
                          1. Applied rewrites36.4%

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

                            \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - -1} \]
                          3. Step-by-step derivation
                            1. Applied rewrites36.2%

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

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

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

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

                                \[\leadsto \frac{i \cdot \color{blue}{\frac{\beta + i}{\beta + 2 \cdot i}}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                              5. lower-/.f6483.9%

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

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

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

                                \[\leadsto \frac{i \cdot \frac{\beta + i}{2 \cdot i + \color{blue}{\beta}}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                              9. lift-fma.f6483.9%

                                \[\leadsto \frac{i \cdot \frac{\beta + i}{\mathsf{fma}\left(2, \color{blue}{i}, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                            3. Applied rewrites83.9%

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

                            Alternative 7: 86.1% accurate, 1.0× speedup?

                            \[\begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\ \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 1.1 \cdot 10^{+135}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{-1 \cdot \mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{t\_0 - 1} \cdot \frac{\left(\mathsf{max}\left(\alpha, \beta\right) + i\right) \cdot \frac{i}{t\_0}}{t\_0 - -1}\\ \end{array} \]
                            (FPCore (alpha beta i)
                             :precision binary64
                             (let* ((t_0 (fma 2.0 i (fmax alpha beta))))
                               (if (<= (fmax alpha beta) 1.1e+135)
                                 0.0625
                                 (*
                                  (/ (* -1.0 (fma -1.0 (fmin alpha beta) (* -1.0 i))) (- t_0 1.0))
                                  (/ (* (+ (fmax alpha beta) i) (/ i t_0)) (- t_0 -1.0))))))
                            double code(double alpha, double beta, double i) {
                            	double t_0 = fma(2.0, i, fmax(alpha, beta));
                            	double tmp;
                            	if (fmax(alpha, beta) <= 1.1e+135) {
                            		tmp = 0.0625;
                            	} else {
                            		tmp = ((-1.0 * fma(-1.0, fmin(alpha, beta), (-1.0 * i))) / (t_0 - 1.0)) * (((fmax(alpha, beta) + i) * (i / t_0)) / (t_0 - -1.0));
                            	}
                            	return tmp;
                            }
                            
                            function code(alpha, beta, i)
                            	t_0 = fma(2.0, i, fmax(alpha, beta))
                            	tmp = 0.0
                            	if (fmax(alpha, beta) <= 1.1e+135)
                            		tmp = 0.0625;
                            	else
                            		tmp = Float64(Float64(Float64(-1.0 * fma(-1.0, fmin(alpha, beta), Float64(-1.0 * i))) / Float64(t_0 - 1.0)) * Float64(Float64(Float64(fmax(alpha, beta) + i) * Float64(i / t_0)) / Float64(t_0 - -1.0)));
                            	end
                            	return tmp
                            end
                            
                            code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[Max[alpha, beta], $MachinePrecision], 1.1e+135], 0.0625, N[(N[(N[(-1.0 * N[(-1.0 * N[Min[alpha, beta], $MachinePrecision] + N[(-1.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t$95$0 - 1.0), $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[Max[alpha, beta], $MachinePrecision] + i), $MachinePrecision] * N[(i / t$95$0), $MachinePrecision]), $MachinePrecision] / N[(t$95$0 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
                            
                            \begin{array}{l}
                            t_0 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\
                            \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 1.1 \cdot 10^{+135}:\\
                            \;\;\;\;0.0625\\
                            
                            \mathbf{else}:\\
                            \;\;\;\;\frac{-1 \cdot \mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{t\_0 - 1} \cdot \frac{\left(\mathsf{max}\left(\alpha, \beta\right) + i\right) \cdot \frac{i}{t\_0}}{t\_0 - -1}\\
                            
                            
                            \end{array}
                            
                            Derivation
                            1. Split input into 2 regimes
                            2. if beta < 1.1e135

                              1. Initial program 16.5%

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

                                \[\leadsto \color{blue}{\frac{1}{16}} \]
                              3. Step-by-step derivation
                                1. Applied rewrites70.6%

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

                                if 1.1e135 < beta

                                1. Initial program 16.5%

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

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

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

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

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

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

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

                                    \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
                                3. Applied rewrites42.6%

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

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

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

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

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

                                    \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + \color{blue}{2 \cdot i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                  5. lower-*.f6440.3%

                                    \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot \color{blue}{i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                6. Applied rewrites40.3%

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

                                  \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                8. Step-by-step derivation
                                  1. Applied rewrites36.5%

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

                                    \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\color{blue}{\beta} + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                  3. Step-by-step derivation
                                    1. Applied rewrites40.2%

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

                                      \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                    3. Step-by-step derivation
                                      1. Applied rewrites36.4%

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

                                        \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - -1} \]
                                      3. Step-by-step derivation
                                        1. Applied rewrites36.2%

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

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

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

                                            \[\leadsto \frac{-1 \cdot \mathsf{fma}\left(-1, \color{blue}{\alpha}, -1 \cdot i\right)}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                                          3. lower-*.f6427.9%

                                            \[\leadsto \frac{-1 \cdot \mathsf{fma}\left(-1, \alpha, -1 \cdot i\right)}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                                        4. Applied rewrites27.9%

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

                                      Alternative 8: 85.3% accurate, 1.2× speedup?

                                      \[\begin{array}{l} t_0 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\ \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 5.5 \cdot 10^{+143}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\left(-1 \cdot \frac{\mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{\mathsf{max}\left(\alpha, \beta\right)}\right) \cdot \frac{\left(\mathsf{max}\left(\alpha, \beta\right) + i\right) \cdot \frac{i}{t\_0}}{t\_0 - -1}\\ \end{array} \]
                                      (FPCore (alpha beta i)
                                       :precision binary64
                                       (let* ((t_0 (fma 2.0 i (fmax alpha beta))))
                                         (if (<= (fmax alpha beta) 5.5e+143)
                                           0.0625
                                           (*
                                            (* -1.0 (/ (fma -1.0 (fmin alpha beta) (* -1.0 i)) (fmax alpha beta)))
                                            (/ (* (+ (fmax alpha beta) i) (/ i t_0)) (- t_0 -1.0))))))
                                      double code(double alpha, double beta, double i) {
                                      	double t_0 = fma(2.0, i, fmax(alpha, beta));
                                      	double tmp;
                                      	if (fmax(alpha, beta) <= 5.5e+143) {
                                      		tmp = 0.0625;
                                      	} else {
                                      		tmp = (-1.0 * (fma(-1.0, fmin(alpha, beta), (-1.0 * i)) / fmax(alpha, beta))) * (((fmax(alpha, beta) + i) * (i / t_0)) / (t_0 - -1.0));
                                      	}
                                      	return tmp;
                                      }
                                      
                                      function code(alpha, beta, i)
                                      	t_0 = fma(2.0, i, fmax(alpha, beta))
                                      	tmp = 0.0
                                      	if (fmax(alpha, beta) <= 5.5e+143)
                                      		tmp = 0.0625;
                                      	else
                                      		tmp = Float64(Float64(-1.0 * Float64(fma(-1.0, fmin(alpha, beta), Float64(-1.0 * i)) / fmax(alpha, beta))) * Float64(Float64(Float64(fmax(alpha, beta) + i) * Float64(i / t_0)) / Float64(t_0 - -1.0)));
                                      	end
                                      	return tmp
                                      end
                                      
                                      code[alpha_, beta_, i_] := Block[{t$95$0 = N[(2.0 * i + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[Max[alpha, beta], $MachinePrecision], 5.5e+143], 0.0625, N[(N[(-1.0 * N[(N[(-1.0 * N[Min[alpha, beta], $MachinePrecision] + N[(-1.0 * i), $MachinePrecision]), $MachinePrecision] / N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(N[(N[Max[alpha, beta], $MachinePrecision] + i), $MachinePrecision] * N[(i / t$95$0), $MachinePrecision]), $MachinePrecision] / N[(t$95$0 - -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
                                      
                                      \begin{array}{l}
                                      t_0 := \mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right)\right)\\
                                      \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 5.5 \cdot 10^{+143}:\\
                                      \;\;\;\;0.0625\\
                                      
                                      \mathbf{else}:\\
                                      \;\;\;\;\left(-1 \cdot \frac{\mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{\mathsf{max}\left(\alpha, \beta\right)}\right) \cdot \frac{\left(\mathsf{max}\left(\alpha, \beta\right) + i\right) \cdot \frac{i}{t\_0}}{t\_0 - -1}\\
                                      
                                      
                                      \end{array}
                                      
                                      Derivation
                                      1. Split input into 2 regimes
                                      2. if beta < 5.4999999999999997e143

                                        1. Initial program 16.5%

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

                                          \[\leadsto \color{blue}{\frac{1}{16}} \]
                                        3. Step-by-step derivation
                                          1. Applied rewrites70.6%

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

                                          if 5.4999999999999997e143 < beta

                                          1. Initial program 16.5%

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

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

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

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

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

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

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

                                              \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
                                          3. Applied rewrites42.6%

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

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

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

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

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

                                              \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + \color{blue}{2 \cdot i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                            5. lower-*.f6440.3%

                                              \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot \color{blue}{i}}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                          6. Applied rewrites40.3%

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

                                            \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - 1} \cdot \frac{\left(\left(\beta + \alpha\right) + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                          8. Step-by-step derivation
                                            1. Applied rewrites36.5%

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

                                              \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\color{blue}{\beta} + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                            3. Step-by-step derivation
                                              1. Applied rewrites40.2%

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

                                                \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - -1} \]
                                              3. Step-by-step derivation
                                                1. Applied rewrites36.4%

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

                                                  \[\leadsto \frac{\frac{i \cdot \left(\beta + i\right)}{\beta + 2 \cdot i}}{\mathsf{fma}\left(2, i, \beta\right) - 1} \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \color{blue}{\beta}\right) - -1} \]
                                                3. Step-by-step derivation
                                                  1. Applied rewrites36.2%

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

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

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

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

                                                      \[\leadsto \left(-1 \cdot \frac{\mathsf{fma}\left(-1, \alpha, -1 \cdot i\right)}{\beta}\right) \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                                                    4. lower-*.f6416.7%

                                                      \[\leadsto \left(-1 \cdot \frac{\mathsf{fma}\left(-1, \alpha, -1 \cdot i\right)}{\beta}\right) \cdot \frac{\left(\beta + i\right) \cdot \frac{i}{\mathsf{fma}\left(2, i, \beta\right)}}{\mathsf{fma}\left(2, i, \beta\right) - -1} \]
                                                  4. Applied rewrites16.7%

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

                                                Alternative 9: 85.3% accurate, 1.3× speedup?

                                                \[\begin{array}{l} \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 5.5 \cdot 10^{+143}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\frac{-1 \cdot \mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{\mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right) + \mathsf{min}\left(\alpha, \beta\right)\right) - 1} \cdot \frac{i}{1 + \left(\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)\right)}\\ \end{array} \]
                                                (FPCore (alpha beta i)
                                                 :precision binary64
                                                 (if (<= (fmax alpha beta) 5.5e+143)
                                                   0.0625
                                                   (*
                                                    (/
                                                     (* -1.0 (fma -1.0 (fmin alpha beta) (* -1.0 i)))
                                                     (- (fma 2.0 i (+ (fmax alpha beta) (fmin alpha beta))) 1.0))
                                                    (/ i (+ 1.0 (+ (fmin alpha beta) (fmax alpha beta)))))))
                                                double code(double alpha, double beta, double i) {
                                                	double tmp;
                                                	if (fmax(alpha, beta) <= 5.5e+143) {
                                                		tmp = 0.0625;
                                                	} else {
                                                		tmp = ((-1.0 * fma(-1.0, fmin(alpha, beta), (-1.0 * i))) / (fma(2.0, i, (fmax(alpha, beta) + fmin(alpha, beta))) - 1.0)) * (i / (1.0 + (fmin(alpha, beta) + fmax(alpha, beta))));
                                                	}
                                                	return tmp;
                                                }
                                                
                                                function code(alpha, beta, i)
                                                	tmp = 0.0
                                                	if (fmax(alpha, beta) <= 5.5e+143)
                                                		tmp = 0.0625;
                                                	else
                                                		tmp = Float64(Float64(Float64(-1.0 * fma(-1.0, fmin(alpha, beta), Float64(-1.0 * i))) / Float64(fma(2.0, i, Float64(fmax(alpha, beta) + fmin(alpha, beta))) - 1.0)) * Float64(i / Float64(1.0 + Float64(fmin(alpha, beta) + fmax(alpha, beta)))));
                                                	end
                                                	return tmp
                                                end
                                                
                                                code[alpha_, beta_, i_] := If[LessEqual[N[Max[alpha, beta], $MachinePrecision], 5.5e+143], 0.0625, N[(N[(N[(-1.0 * N[(-1.0 * N[Min[alpha, beta], $MachinePrecision] + N[(-1.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(2.0 * i + N[(N[Max[alpha, beta], $MachinePrecision] + N[Min[alpha, beta], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision] * N[(i / N[(1.0 + N[(N[Min[alpha, beta], $MachinePrecision] + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
                                                
                                                \begin{array}{l}
                                                \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 5.5 \cdot 10^{+143}:\\
                                                \;\;\;\;0.0625\\
                                                
                                                \mathbf{else}:\\
                                                \;\;\;\;\frac{-1 \cdot \mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{\mathsf{fma}\left(2, i, \mathsf{max}\left(\alpha, \beta\right) + \mathsf{min}\left(\alpha, \beta\right)\right) - 1} \cdot \frac{i}{1 + \left(\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)\right)}\\
                                                
                                                
                                                \end{array}
                                                
                                                Derivation
                                                1. Split input into 2 regimes
                                                2. if beta < 5.4999999999999997e143

                                                  1. Initial program 16.5%

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

                                                    \[\leadsto \color{blue}{\frac{1}{16}} \]
                                                  3. Step-by-step derivation
                                                    1. Applied rewrites70.6%

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

                                                    if 5.4999999999999997e143 < beta

                                                    1. Initial program 16.5%

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

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

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

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

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

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

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

                                                        \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
                                                    3. Applied rewrites42.6%

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

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

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

                                                        \[\leadsto \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{i}{1 + \color{blue}{\left(\alpha + \beta\right)}} \]
                                                      3. lower-+.f6416.0%

                                                        \[\leadsto \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{i}{1 + \left(\alpha + \color{blue}{\beta}\right)} \]
                                                    6. Applied rewrites16.0%

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

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

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

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

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

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

                                                  Alternative 10: 85.1% accurate, 1.6× speedup?

                                                  \[\begin{array}{l} \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 5.5 \cdot 10^{+143}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\left(-1 \cdot \frac{\mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{\mathsf{max}\left(\alpha, \beta\right)}\right) \cdot \frac{i}{1 + \left(\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)\right)}\\ \end{array} \]
                                                  (FPCore (alpha beta i)
                                                   :precision binary64
                                                   (if (<= (fmax alpha beta) 5.5e+143)
                                                     0.0625
                                                     (*
                                                      (* -1.0 (/ (fma -1.0 (fmin alpha beta) (* -1.0 i)) (fmax alpha beta)))
                                                      (/ i (+ 1.0 (+ (fmin alpha beta) (fmax alpha beta)))))))
                                                  double code(double alpha, double beta, double i) {
                                                  	double tmp;
                                                  	if (fmax(alpha, beta) <= 5.5e+143) {
                                                  		tmp = 0.0625;
                                                  	} else {
                                                  		tmp = (-1.0 * (fma(-1.0, fmin(alpha, beta), (-1.0 * i)) / fmax(alpha, beta))) * (i / (1.0 + (fmin(alpha, beta) + fmax(alpha, beta))));
                                                  	}
                                                  	return tmp;
                                                  }
                                                  
                                                  function code(alpha, beta, i)
                                                  	tmp = 0.0
                                                  	if (fmax(alpha, beta) <= 5.5e+143)
                                                  		tmp = 0.0625;
                                                  	else
                                                  		tmp = Float64(Float64(-1.0 * Float64(fma(-1.0, fmin(alpha, beta), Float64(-1.0 * i)) / fmax(alpha, beta))) * Float64(i / Float64(1.0 + Float64(fmin(alpha, beta) + fmax(alpha, beta)))));
                                                  	end
                                                  	return tmp
                                                  end
                                                  
                                                  code[alpha_, beta_, i_] := If[LessEqual[N[Max[alpha, beta], $MachinePrecision], 5.5e+143], 0.0625, N[(N[(-1.0 * N[(N[(-1.0 * N[Min[alpha, beta], $MachinePrecision] + N[(-1.0 * i), $MachinePrecision]), $MachinePrecision] / N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(i / N[(1.0 + N[(N[Min[alpha, beta], $MachinePrecision] + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
                                                  
                                                  \begin{array}{l}
                                                  \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 5.5 \cdot 10^{+143}:\\
                                                  \;\;\;\;0.0625\\
                                                  
                                                  \mathbf{else}:\\
                                                  \;\;\;\;\left(-1 \cdot \frac{\mathsf{fma}\left(-1, \mathsf{min}\left(\alpha, \beta\right), -1 \cdot i\right)}{\mathsf{max}\left(\alpha, \beta\right)}\right) \cdot \frac{i}{1 + \left(\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)\right)}\\
                                                  
                                                  
                                                  \end{array}
                                                  
                                                  Derivation
                                                  1. Split input into 2 regimes
                                                  2. if beta < 5.4999999999999997e143

                                                    1. Initial program 16.5%

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

                                                      \[\leadsto \color{blue}{\frac{1}{16}} \]
                                                    3. Step-by-step derivation
                                                      1. Applied rewrites70.6%

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

                                                      if 5.4999999999999997e143 < beta

                                                      1. Initial program 16.5%

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

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

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

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

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

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

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

                                                          \[\leadsto \frac{\frac{\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i} \cdot \frac{i \cdot \left(\left(\alpha + \beta\right) + i\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\color{blue}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)} - 1} \]
                                                      3. Applied rewrites42.6%

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

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

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

                                                          \[\leadsto \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{i}{1 + \color{blue}{\left(\alpha + \beta\right)}} \]
                                                        3. lower-+.f6416.0%

                                                          \[\leadsto \frac{\frac{\mathsf{fma}\left(\left(\beta + \alpha\right) + i, i, \beta \cdot \alpha\right)}{\mathsf{fma}\left(2, i, \beta + \alpha\right)}}{\mathsf{fma}\left(2, i, \beta + \alpha\right) - 1} \cdot \frac{i}{1 + \left(\alpha + \color{blue}{\beta}\right)} \]
                                                      6. Applied rewrites16.0%

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

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

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

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

                                                          \[\leadsto \left(-1 \cdot \frac{\mathsf{fma}\left(-1, \alpha, -1 \cdot i\right)}{\beta}\right) \cdot \frac{i}{1 + \left(\alpha + \beta\right)} \]
                                                        4. lower-*.f6416.4%

                                                          \[\leadsto \left(-1 \cdot \frac{\mathsf{fma}\left(-1, \alpha, -1 \cdot i\right)}{\beta}\right) \cdot \frac{i}{1 + \left(\alpha + \beta\right)} \]
                                                      9. Applied rewrites16.4%

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

                                                    Alternative 11: 77.2% accurate, 2.4× speedup?

                                                    \[\left(0.0625 + 0.125 \cdot \frac{\mathsf{max}\left(\alpha, \beta\right)}{i}\right) - 0.125 \cdot \frac{\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)}{i} \]
                                                    (FPCore (alpha beta i)
                                                     :precision binary64
                                                     (-
                                                      (+ 0.0625 (* 0.125 (/ (fmax alpha beta) i)))
                                                      (* 0.125 (/ (+ (fmin alpha beta) (fmax alpha beta)) i))))
                                                    double code(double alpha, double beta, double i) {
                                                    	return (0.0625 + (0.125 * (fmax(alpha, beta) / i))) - (0.125 * ((fmin(alpha, beta) + fmax(alpha, beta)) / i));
                                                    }
                                                    
                                                    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 + (0.125d0 * (fmax(alpha, beta) / i))) - (0.125d0 * ((fmin(alpha, beta) + fmax(alpha, beta)) / i))
                                                    end function
                                                    
                                                    public static double code(double alpha, double beta, double i) {
                                                    	return (0.0625 + (0.125 * (fmax(alpha, beta) / i))) - (0.125 * ((fmin(alpha, beta) + fmax(alpha, beta)) / i));
                                                    }
                                                    
                                                    def code(alpha, beta, i):
                                                    	return (0.0625 + (0.125 * (fmax(alpha, beta) / i))) - (0.125 * ((fmin(alpha, beta) + fmax(alpha, beta)) / i))
                                                    
                                                    function code(alpha, beta, i)
                                                    	return Float64(Float64(0.0625 + Float64(0.125 * Float64(fmax(alpha, beta) / i))) - Float64(0.125 * Float64(Float64(fmin(alpha, beta) + fmax(alpha, beta)) / i)))
                                                    end
                                                    
                                                    function tmp = code(alpha, beta, i)
                                                    	tmp = (0.0625 + (0.125 * (max(alpha, beta) / i))) - (0.125 * ((min(alpha, beta) + max(alpha, beta)) / i));
                                                    end
                                                    
                                                    code[alpha_, beta_, i_] := N[(N[(0.0625 + N[(0.125 * N[(N[Max[alpha, beta], $MachinePrecision] / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(0.125 * N[(N[(N[Min[alpha, beta], $MachinePrecision] + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
                                                    
                                                    \left(0.0625 + 0.125 \cdot \frac{\mathsf{max}\left(\alpha, \beta\right)}{i}\right) - 0.125 \cdot \frac{\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)}{i}
                                                    
                                                    Derivation
                                                    1. Initial program 16.5%

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

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

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

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

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

                                                        \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{\mathsf{fma}\left(2, \alpha, 2 \cdot \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{\color{blue}{i}} \]
                                                      9. lower-+.f6477.2%

                                                        \[\leadsto \left(0.0625 + 0.0625 \cdot \frac{\mathsf{fma}\left(2, \alpha, 2 \cdot \beta\right)}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
                                                    4. Applied rewrites77.2%

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

                                                      \[\leadsto \left(0.0625 + \frac{1}{8} \cdot \frac{\beta}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
                                                    6. Step-by-step derivation
                                                      1. lower-*.f64N/A

                                                        \[\leadsto \left(\frac{1}{16} + \frac{1}{8} \cdot \frac{\beta}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
                                                      2. lower-/.f6472.9%

                                                        \[\leadsto \left(0.0625 + 0.125 \cdot \frac{\beta}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
                                                    7. Applied rewrites72.9%

                                                      \[\leadsto \left(0.0625 + 0.125 \cdot \frac{\beta}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
                                                    8. Add Preprocessing

                                                    Alternative 12: 74.0% accurate, 2.2× speedup?

                                                    \[\begin{array}{l} \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 1.1 \cdot 10^{+249}:\\ \;\;\;\;0.0625\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\frac{\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)}{i}, -0.125, 0.125 \cdot \frac{\mathsf{max}\left(\alpha, \beta\right)}{i}\right)\\ \end{array} \]
                                                    (FPCore (alpha beta i)
                                                     :precision binary64
                                                     (if (<= (fmax alpha beta) 1.1e+249)
                                                       0.0625
                                                       (fma
                                                        (/ (+ (fmin alpha beta) (fmax alpha beta)) i)
                                                        -0.125
                                                        (* 0.125 (/ (fmax alpha beta) i)))))
                                                    double code(double alpha, double beta, double i) {
                                                    	double tmp;
                                                    	if (fmax(alpha, beta) <= 1.1e+249) {
                                                    		tmp = 0.0625;
                                                    	} else {
                                                    		tmp = fma(((fmin(alpha, beta) + fmax(alpha, beta)) / i), -0.125, (0.125 * (fmax(alpha, beta) / i)));
                                                    	}
                                                    	return tmp;
                                                    }
                                                    
                                                    function code(alpha, beta, i)
                                                    	tmp = 0.0
                                                    	if (fmax(alpha, beta) <= 1.1e+249)
                                                    		tmp = 0.0625;
                                                    	else
                                                    		tmp = fma(Float64(Float64(fmin(alpha, beta) + fmax(alpha, beta)) / i), -0.125, Float64(0.125 * Float64(fmax(alpha, beta) / i)));
                                                    	end
                                                    	return tmp
                                                    end
                                                    
                                                    code[alpha_, beta_, i_] := If[LessEqual[N[Max[alpha, beta], $MachinePrecision], 1.1e+249], 0.0625, N[(N[(N[(N[Min[alpha, beta], $MachinePrecision] + N[Max[alpha, beta], $MachinePrecision]), $MachinePrecision] / i), $MachinePrecision] * -0.125 + N[(0.125 * N[(N[Max[alpha, beta], $MachinePrecision] / i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
                                                    
                                                    \begin{array}{l}
                                                    \mathbf{if}\;\mathsf{max}\left(\alpha, \beta\right) \leq 1.1 \cdot 10^{+249}:\\
                                                    \;\;\;\;0.0625\\
                                                    
                                                    \mathbf{else}:\\
                                                    \;\;\;\;\mathsf{fma}\left(\frac{\mathsf{min}\left(\alpha, \beta\right) + \mathsf{max}\left(\alpha, \beta\right)}{i}, -0.125, 0.125 \cdot \frac{\mathsf{max}\left(\alpha, \beta\right)}{i}\right)\\
                                                    
                                                    
                                                    \end{array}
                                                    
                                                    Derivation
                                                    1. Split input into 2 regimes
                                                    2. if beta < 1.0999999999999999e249

                                                      1. Initial program 16.5%

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

                                                        \[\leadsto \color{blue}{\frac{1}{16}} \]
                                                      3. Step-by-step derivation
                                                        1. Applied rewrites70.6%

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

                                                        if 1.0999999999999999e249 < beta

                                                        1. Initial program 16.5%

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

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

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

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

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

                                                            \[\leadsto \left(\frac{1}{16} + \frac{1}{16} \cdot \frac{\mathsf{fma}\left(2, \alpha, 2 \cdot \beta\right)}{i}\right) - \frac{1}{8} \cdot \frac{\alpha + \beta}{\color{blue}{i}} \]
                                                          9. lower-+.f6477.2%

                                                            \[\leadsto \left(0.0625 + 0.0625 \cdot \frac{\mathsf{fma}\left(2, \alpha, 2 \cdot \beta\right)}{i}\right) - 0.125 \cdot \frac{\alpha + \beta}{i} \]
                                                        4. Applied rewrites77.2%

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

                                                          \[\leadsto \frac{1}{8} \cdot \frac{\alpha}{i} - \color{blue}{0.125} \cdot \frac{\alpha + \beta}{i} \]
                                                        6. Step-by-step derivation
                                                          1. lower-*.f64N/A

                                                            \[\leadsto \frac{1}{8} \cdot \frac{\alpha}{i} - \frac{1}{8} \cdot \frac{\alpha + \beta}{i} \]
                                                          2. lower-/.f646.5%

                                                            \[\leadsto 0.125 \cdot \frac{\alpha}{i} - 0.125 \cdot \frac{\alpha + \beta}{i} \]
                                                        7. Applied rewrites6.5%

                                                          \[\leadsto 0.125 \cdot \frac{\alpha}{i} - \color{blue}{0.125} \cdot \frac{\alpha + \beta}{i} \]
                                                        8. Step-by-step derivation
                                                          1. lift--.f64N/A

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

                                                            \[\leadsto \frac{1}{8} \cdot \frac{\alpha}{i} - \frac{1}{8} \cdot \color{blue}{\frac{\alpha + \beta}{i}} \]
                                                          3. fp-cancel-sub-sign-invN/A

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

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

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

                                                            \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, \color{blue}{\mathsf{neg}\left(\frac{1}{8}\right)}, \frac{1}{8} \cdot \frac{\alpha}{i}\right) \]
                                                          7. metadata-eval6.5%

                                                            \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, -0.125, 0.125 \cdot \frac{\alpha}{i}\right) \]
                                                          8. lift-*.f64N/A

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

                                                            \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, \frac{-1}{8}, \frac{\alpha}{i} \cdot \frac{1}{8}\right) \]
                                                          10. lower-*.f646.5%

                                                            \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, -0.125, \frac{\alpha}{i} \cdot 0.125\right) \]
                                                        9. Applied rewrites6.5%

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

                                                          \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, -0.125, \frac{1}{8} \cdot \frac{\beta}{i}\right) \]
                                                        11. Step-by-step derivation
                                                          1. lower-*.f64N/A

                                                            \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, \frac{-1}{8}, \frac{1}{8} \cdot \frac{\beta}{i}\right) \]
                                                          2. lower-/.f646.1%

                                                            \[\leadsto \mathsf{fma}\left(\frac{\alpha + \beta}{i}, -0.125, 0.125 \cdot \frac{\beta}{i}\right) \]
                                                        12. Applied rewrites6.1%

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

                                                      Alternative 13: 70.6% accurate, 75.4× speedup?

                                                      \[0.0625 \]
                                                      (FPCore (alpha beta i) :precision binary64 0.0625)
                                                      double code(double alpha, double beta, double i) {
                                                      	return 0.0625;
                                                      }
                                                      
                                                      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
                                                      
                                                      public static double code(double alpha, double beta, double i) {
                                                      	return 0.0625;
                                                      }
                                                      
                                                      def code(alpha, beta, i):
                                                      	return 0.0625
                                                      
                                                      function code(alpha, beta, i)
                                                      	return 0.0625
                                                      end
                                                      
                                                      function tmp = code(alpha, beta, i)
                                                      	tmp = 0.0625;
                                                      end
                                                      
                                                      code[alpha_, beta_, i_] := 0.0625
                                                      
                                                      0.0625
                                                      
                                                      Derivation
                                                      1. Initial program 16.5%

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

                                                        \[\leadsto \color{blue}{\frac{1}{16}} \]
                                                      3. Step-by-step derivation
                                                        1. Applied rewrites70.6%

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

                                                        Reproduce

                                                        ?
                                                        herbie shell --seed 2025183 
                                                        (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)))