  The two-sample Kolmogorov-Smirnov test is a widely used statistical test for
detecting whether two samples are likely to come from the same distribution.
Implementations typically recur on an article of Hodges from 1957. The advances
in computation speed make it feasible to compute exact p-values for a much
larger range of problem sizes, but these run into numerical stability problems
from floating point operations. We provide a simple transformation of the
defining recurrence for the two-side two-sample KS test that avoids this.
