\[\frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
Test:
Octave 3.8, jcobi/3
Bits:
128 bits
Bits error versus alpha
Bits error versus beta
Time: 31.8 s
Input Error: 3.5
Output Error: 3.6
Log:
Profile: 🕒
\(\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot {\left(\frac{\sqrt{\beta + \left(\alpha \cdot \beta + \left(\alpha + 1.0\right)\right)}}{\left(2 + \alpha\right) + \beta}\right)}^2\)
  1. Started with
    \[\frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    3.5
  2. Applied simplify to get
    \[\color{red}{\frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}} \leadsto \color{blue}{\frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)}}\]
    4.3
  3. Using strategy rm
    4.3
  4. Applied *-un-lft-identity to get
    \[\frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\color{red}{\alpha + \left(2 + \beta\right)}}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)} \leadsto \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\color{blue}{1 \cdot \left(\alpha + \left(2 + \beta\right)\right)}}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)}\]
    4.3
  5. Applied *-un-lft-identity to get
    \[\frac{\frac{\color{red}{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}}{1 \cdot \left(\alpha + \left(2 + \beta\right)\right)}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)} \leadsto \frac{\frac{\color{blue}{1 \cdot \left(\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)\right)}}{1 \cdot \left(\alpha + \left(2 + \beta\right)\right)}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)}\]
    4.3
  6. Applied times-frac to get
    \[\frac{\color{red}{\frac{1 \cdot \left(\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)\right)}{1 \cdot \left(\alpha + \left(2 + \beta\right)\right)}}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)} \leadsto \frac{\color{blue}{\frac{1}{1} \cdot \frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)}\]
    4.3
  7. Applied times-frac to get
    \[\color{red}{\frac{\frac{1}{1} \cdot \frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\left(\left(\alpha + 1.0\right) + \left(2 + \beta\right)\right) \cdot \left(\alpha + \left(2 + \beta\right)\right)}} \leadsto \color{blue}{\frac{\frac{1}{1}}{\left(\alpha + 1.0\right) + \left(2 + \beta\right)} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\alpha + \left(2 + \beta\right)}}\]
    3.6
  8. Applied simplify to get
    \[\color{red}{\frac{\frac{1}{1}}{\left(\alpha + 1.0\right) + \left(2 + \beta\right)}} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\alpha + \left(2 + \beta\right)} \leadsto \color{blue}{\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)}} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\alpha + \left(2 + \beta\right)}\]
    3.6
  9. Using strategy rm
    3.6
  10. Applied add-sqr-sqrt to get
    \[\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\color{red}{\alpha + \left(2 + \beta\right)}} \leadsto \frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\alpha + \left(2 + \beta\right)}}{\color{blue}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}}\]
    4.0
  11. Applied add-sqr-sqrt to get
    \[\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\color{red}{\alpha + \left(2 + \beta\right)}}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2} \leadsto \frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\frac{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}{\color{blue}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}\]
    4.5
  12. Applied add-sqr-sqrt to get
    \[\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\frac{\color{red}{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2} \leadsto \frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\frac{\color{blue}{{\left(\sqrt{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}\right)}^2}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}\]
    4.5
  13. Applied square-undiv to get
    \[\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\color{red}{\frac{{\left(\sqrt{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}\right)}^2}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2} \leadsto \frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \frac{\color{blue}{{\left(\frac{\sqrt{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}}{\sqrt{\alpha + \left(2 + \beta\right)}}\right)}^2}}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}\]
    4.5
  14. Applied square-undiv to get
    \[\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \color{red}{\frac{{\left(\frac{\sqrt{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}}{\sqrt{\alpha + \left(2 + \beta\right)}}\right)}^2}{{\left(\sqrt{\alpha + \left(2 + \beta\right)}\right)}^2}} \leadsto \frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot \color{blue}{{\left(\frac{\frac{\sqrt{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}}{\sqrt{\alpha + \left(2 + \beta\right)}}}{\sqrt{\alpha + \left(2 + \beta\right)}}\right)}^2}\]
    4.1
  15. Applied simplify to get
    \[\frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot {\color{red}{\left(\frac{\frac{\sqrt{\left(\alpha + 1.0\right) + \left(\beta + \beta \cdot \alpha\right)}}{\sqrt{\alpha + \left(2 + \beta\right)}}}{\sqrt{\alpha + \left(2 + \beta\right)}}\right)}}^2 \leadsto \frac{1}{\left(\beta + 1.0\right) + \left(\alpha + 2\right)} \cdot {\color{blue}{\left(\frac{\sqrt{\beta + \left(\alpha \cdot \beta + \left(\alpha + 1.0\right)\right)}}{\left(2 + \alpha\right) + \beta}\right)}}^2\]
    3.6

Original test:


(lambda ((alpha default) (beta default))
  #:name "Octave 3.8, jcobi/3"
  (/ (/ (/ (+ (+ (+ alpha beta) (* beta alpha)) 1.0) (+ (+ alpha beta) (* 2 1))) (+ (+ alpha beta) (* 2 1))) (+ (+ (+ alpha beta) (* 2 1)) 1.0)))