Implement true floating point semantics

[pschanely]

One big gotcha with CrossHair and floats: For performance reasons CrossHair approximates floating point behavior using true (arbitrary precision) real numbers.

Z3 is technically capable of doing floating-point-accurate symbolic execution. However, those capabilities are very slow; it might take O(minutes) to reason about a single floating point operation. In an ideal world, we might try both approaches.

Originally posted by @pschanely in #188 (comment)

[pschanely]

@Zac-HD and anyone else following along: I've been busy working on this recently. I can safely say that this mode will be quite slow, and suspect that the conversions between floats and unbounded integers (which are uniquely bountiful in Python) could turn even simple cases to impossible. Still, I think some use cases could benefit from it, and then we'll be prepared for advances on the solving side.

Hoping to have something by this weekend!

[pschanely]

I have an initial version shipped in 0.0.72; this version will, with a low probability, attempt executions down a parallel path tree that implements true-float semantics instead of the real-based ones. The main thing I'm still missing is something to validate real-based executions. In other words, this version attempts to find bugs that the previously implementation missed, but does not help with false positive reports. I'll address those in #309.

@Zac-HD Although this should fix a test or two, there's a good chance that I'll regress on a few, due to the shiny new surface area for bugs.