Average Error: 3.9 → 1.3
Time: 2.9m
Precision: 64
Internal Precision: 320
\[\frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
\[\begin{array}{l} \mathbf{if}\;\alpha \le 8.887050974210865 \cdot 10^{+159}:\\ \;\;\;\;\frac{\frac{1}{\left(\alpha + 2\right) + \left(\beta + 1.0\right)}}{\left(\beta + \alpha\right) + 2} \cdot \frac{\left(\alpha + \left(\beta + 1.0\right)\right) + \beta \cdot \alpha}{\left(\beta + \alpha\right) + 2}\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{1}{\frac{\left(\beta + \alpha\right) + 2}{\frac{1}{\left(\frac{1}{\beta} + \frac{1}{\alpha}\right) - \frac{1}{{\alpha}^{2}}}}}}{1.0 + \left(\left(\beta + \alpha\right) + 2\right)}\\ \end{array}\]

Error

Bits error versus alpha

Bits error versus beta

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Split input into 2 regimes
  2. if alpha < 8.887050974210865e+159

    1. Initial program 1.2

      \[\frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    2. Using strategy rm
    3. Applied *-un-lft-identity1.2

      \[\leadsto \frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\color{blue}{1 \cdot \left(\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0\right)}}\]
    4. Applied div-inv1.2

      \[\leadsto \frac{\color{blue}{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1} \cdot \frac{1}{\left(\alpha + \beta\right) + 2 \cdot 1}}}{1 \cdot \left(\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0\right)}\]
    5. Applied times-frac1.5

      \[\leadsto \color{blue}{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{1} \cdot \frac{\frac{1}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}}\]
    6. Simplified1.5

      \[\leadsto \color{blue}{\frac{\alpha \cdot \beta + \left(\alpha + \left(\beta + 1.0\right)\right)}{2 + \left(\beta + \alpha\right)}} \cdot \frac{\frac{1}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    7. Simplified1.5

      \[\leadsto \frac{\alpha \cdot \beta + \left(\alpha + \left(\beta + 1.0\right)\right)}{2 + \left(\beta + \alpha\right)} \cdot \color{blue}{\frac{\frac{1}{\left(\alpha + 2\right) + \left(1.0 + \beta\right)}}{\left(\alpha + \beta\right) + 2}}\]

    if 8.887050974210865e+159 < alpha

    1. Initial program 18.0

      \[\frac{\frac{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    2. Using strategy rm
    3. Applied *-un-lft-identity18.0

      \[\leadsto \frac{\frac{\color{blue}{1 \cdot \frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}}{\left(\alpha + \beta\right) + 2 \cdot 1}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    4. Applied associate-/l*18.0

      \[\leadsto \frac{\color{blue}{\frac{1}{\frac{\left(\alpha + \beta\right) + 2 \cdot 1}{\frac{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}{\left(\alpha + \beta\right) + 2 \cdot 1}}}}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    5. Using strategy rm
    6. Applied *-un-lft-identity18.0

      \[\leadsto \frac{\frac{1}{\frac{\left(\alpha + \beta\right) + 2 \cdot 1}{\frac{\color{blue}{1 \cdot \left(\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0\right)}}{\left(\alpha + \beta\right) + 2 \cdot 1}}}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    7. Applied associate-/l*18.0

      \[\leadsto \frac{\frac{1}{\frac{\left(\alpha + \beta\right) + 2 \cdot 1}{\color{blue}{\frac{1}{\frac{\left(\alpha + \beta\right) + 2 \cdot 1}{\left(\left(\alpha + \beta\right) + \beta \cdot \alpha\right) + 1.0}}}}}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
    8. Taylor expanded around -inf 0.1

      \[\leadsto \frac{\frac{1}{\frac{\left(\alpha + \beta\right) + 2 \cdot 1}{\frac{1}{\color{blue}{\left(\frac{1}{\alpha} + \frac{1}{\beta}\right) - \frac{1}{{\alpha}^{2}}}}}}}{\left(\left(\alpha + \beta\right) + 2 \cdot 1\right) + 1.0}\]
  3. Recombined 2 regimes into one program.
  4. Final simplification1.3

    \[\leadsto \begin{array}{l} \mathbf{if}\;\alpha \le 8.887050974210865 \cdot 10^{+159}:\\ \;\;\;\;\frac{\frac{1}{\left(\alpha + 2\right) + \left(\beta + 1.0\right)}}{\left(\beta + \alpha\right) + 2} \cdot \frac{\left(\alpha + \left(\beta + 1.0\right)\right) + \beta \cdot \alpha}{\left(\beta + \alpha\right) + 2}\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{1}{\frac{\left(\beta + \alpha\right) + 2}{\frac{1}{\left(\frac{1}{\beta} + \frac{1}{\alpha}\right) - \frac{1}{{\alpha}^{2}}}}}}{1.0 + \left(\left(\beta + \alpha\right) + 2\right)}\\ \end{array}\]

Runtime

Time bar (total: 2.9m)Debug logProfile

BaselineHerbieOracleSpan%
Regimes3.91.30.03.867.6%
herbie shell --seed 2018274 
(FPCore (alpha beta)
  :name "Octave 3.8, jcobi/3"
  :pre (and (> alpha -1) (> beta -1))
  (/ (/ (/ (+ (+ (+ alpha beta) (* beta alpha)) 1.0) (+ (+ alpha beta) (* 2 1))) (+ (+ alpha beta) (* 2 1))) (+ (+ (+ alpha beta) (* 2 1)) 1.0)))