Average Error: 53.7 → 10.7
Time: 12.1s
Precision: binary64
\[\alpha > -1 \land \beta > -1 \land i > 1\]
\[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1}\]
↓
\[\begin{array}{l} \mathbf{if}\;i \leq 2.839314184964972 \cdot 10^{+143}:\\ \;\;\;\;\frac{\frac{i}{\frac{\left(\beta + i \cdot 2\right) + \alpha}{\alpha + \left(i + \beta\right)}}}{\left(\left(\beta + i \cdot 2\right) + \alpha\right) + 1} \cdot \frac{\frac{\beta \cdot \alpha + i \cdot \left(\alpha + \left(i + \beta\right)\right)}{\left(\beta + i \cdot 2\right) + \alpha}}{\left(\left(\beta + i \cdot 2\right) + \alpha\right) - 1}\\ \mathbf{else}:\\ \;\;\;\;0.0625\\ \end{array}\]
\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}
↓
\begin{array}{l}
\mathbf{if}\;i \leq 2.839314184964972 \cdot 10^{+143}:\\
\;\;\;\;\frac{\frac{i}{\frac{\left(\beta + i \cdot 2\right) + \alpha}{\alpha + \left(i + \beta\right)}}}{\left(\left(\beta + i \cdot 2\right) + \alpha\right) + 1} \cdot \frac{\frac{\beta \cdot \alpha + i \cdot \left(\alpha + \left(i + \beta\right)\right)}{\left(\beta + i \cdot 2\right) + \alpha}}{\left(\left(\beta + i \cdot 2\right) + \alpha\right) - 1}\\

\mathbf{else}:\\
\;\;\;\;0.0625\\

\end{array}
(FPCore (alpha beta i)
 :precision binary64
 (/
  (/
   (* (* 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)))
↓
(FPCore (alpha beta i)
 :precision binary64
 (if (<= i 2.839314184964972e+143)
   (*
    (/
     (/ i (/ (+ (+ beta (* i 2.0)) alpha) (+ alpha (+ i beta))))
     (+ (+ (+ beta (* i 2.0)) alpha) 1.0))
    (/
     (/
      (+ (* beta alpha) (* i (+ alpha (+ i beta))))
      (+ (+ beta (* i 2.0)) alpha))
     (- (+ (+ beta (* i 2.0)) alpha) 1.0)))
   0.0625))
double code(double alpha, double beta, double i) {
	return (((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);
}
↓
double code(double alpha, double beta, double i) {
	double tmp;
	if (i <= 2.839314184964972e+143) {
		tmp = ((i / (((beta + (i * 2.0)) + alpha) / (alpha + (i + beta)))) / (((beta + (i * 2.0)) + alpha) + 1.0)) * ((((beta * alpha) + (i * (alpha + (i + beta)))) / ((beta + (i * 2.0)) + alpha)) / (((beta + (i * 2.0)) + alpha) - 1.0));
	} else {
		tmp = 0.0625;
	}
	return tmp;
}

Error

Bits error versus alpha

Bits error versus beta

Bits error versus i

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Split input into 2 regimes

  2. if i < 2.839314184964972e143

    1. Initial program 42.5

      \[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1}\]
    2. Using strategy rm

    3. Applied difference-of-sqr-1_binary6442.5

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

    4. Applied times-frac_binary6415.4

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

    5. Applied times-frac_binary6411.4

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

    6. Simplified11.4

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

    7. Simplified11.4

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

    9. Applied associate-/l*_binary6411.4

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

    10. Simplified11.4

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

    if 2.839314184964972e143 < i

    1. Initial program 64.0

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

    2. Taylor expanded around inf 10.1

      \[\leadsto \color{blue}{0.0625}\]
  3. Recombined 2 regimes into one program.

  4. Final simplification10.7

    \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq 2.839314184964972 \cdot 10^{+143}:\\ \;\;\;\;\frac{\frac{i}{\frac{\left(\beta + i \cdot 2\right) + \alpha}{\alpha + \left(i + \beta\right)}}}{\left(\left(\beta + i \cdot 2\right) + \alpha\right) + 1} \cdot \frac{\frac{\beta \cdot \alpha + i \cdot \left(\alpha + \left(i + \beta\right)\right)}{\left(\beta + i \cdot 2\right) + \alpha}}{\left(\left(\beta + i \cdot 2\right) + \alpha\right) - 1}\\ \mathbf{else}:\\ \;\;\;\;0.0625\\ \end{array}\]

Alternatives

Reproduce

herbie shell --seed 2021106 
(FPCore (alpha beta i)
  :name "Octave 3.8, jcobi/4"
  :precision binary64
  :pre (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)))