\frac{1 + \left(2 - \frac{\frac{2}{t}}{1 + \frac{1}{t}}\right) \cdot \left(2 - \frac{\frac{2}{t}}{1 + \frac{1}{t}}\right)}{2 + \left(2 - \frac{\frac{2}{t}}{1 + \frac{1}{t}}\right) \cdot \left(2 - \frac{\frac{2}{t}}{1 + \frac{1}{t}}\right)}
\begin{array}{l}
t_1 := \frac{2}{1 + t}\\
t_2 := t_1 + -4\\
\frac{\mathsf{fma}\left(t_1, t_2, 5\right)}{\mathsf{fma}\left(t_1, t_2, 6\right)}
\end{array}
(FPCore (t)
:precision binary64
(/
(+
1.0
(*
(- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t))))
(- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t))))))
(+
2.0
(*
(- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t))))
(- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t))))))))(FPCore (t) :precision binary64 (let* ((t_1 (/ 2.0 (+ 1.0 t))) (t_2 (+ t_1 -4.0))) (/ (fma t_1 t_2 5.0) (fma t_1 t_2 6.0))))
double code(double t) {
return (1.0 + ((2.0 - ((2.0 / t) / (1.0 + (1.0 / t)))) * (2.0 - ((2.0 / t) / (1.0 + (1.0 / t)))))) / (2.0 + ((2.0 - ((2.0 / t) / (1.0 + (1.0 / t)))) * (2.0 - ((2.0 / t) / (1.0 + (1.0 / t))))));
}
double code(double t) {
double t_1 = 2.0 / (1.0 + t);
double t_2 = t_1 + -4.0;
return fma(t_1, t_2, 5.0) / fma(t_1, t_2, 6.0);
}



Bits error versus t
Initial program 0.0
Simplified0.0
Final simplification0.0
herbie shell --seed 2022067
(FPCore (t)
:name "Kahan p13 Example 2"
:precision binary64
(/ (+ 1.0 (* (- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t)))) (- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t)))))) (+ 2.0 (* (- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t)))) (- 2.0 (/ (/ 2.0 t) (+ 1.0 (/ 1.0 t))))))))