I’m observing unexpected behavior in `SimpleNonlinearSolve`

/`NonlinearSolve`

’s algorithm `Falsi`

(an algorithm for finding roots of nonlinear functions). I expect `Falsi`

to return a successful return code if it converged, and an unsuccessful one if it couldn’t.

Here is a MWE that contradicts this behavior: For f(x) = 1, `Falsi`

shouldn’t be able to converge, and for f(x) = x, `Falsi`

should converge with result x=0. Here, exactly the opposite happens:

```
using SimpleNonlinearSolve, SciMLBase.ReturnCode
np1 = IntervalNonlinearProblem((x, p) -> 1., (0., 1.))
sol1 = solve(np1, Falsi(); abstol=1e-10)
SciMLBase.successful_retcode(sol1) # returns true (FloatingPointLimit)
np2 = IntervalNonlinearProblem((x, p) -> x, (-1., 1.))
sol2 = solve(np2, Falsi(); abstol=1e-10)
SciMLBase.successful_retcode(sol2) # returns false (MaxIters)
```

Executed using `SciMLBase`

v1.94.0 and `SimpleNonlinearSolve`

v0.1.18.

Is there something I’m missing/misusing here? I guess I could check for `sign(sol.left) == sign(sol.right)`

as a workaround to see if a root could be found.