John, thanks for starting (or restarting) this thread.? I'd like to add to the discussion with another concrete example, about as simple as it gets, which may help focus at least part of this discussion. I have worked with Taylor Arnold to implement a method developed in Conover (1972) for Kolmogorov-Smirnov goodness-of-fit tests for discrete distributions (one-sample only).? We needed this for an applied problem.? It seemed to be a natural extension to stats::ks.test(), so we modified that code (commenting every addition very carefully) and modifying ks.test.Rd in parallel (and with commenting).? For convenience, we put this in a package ks.test that is on R-Forge but not submitted to CRAN.? We've written a short paper about this (and also implemented similar Cramer-von Mises tests in package cvm.test). 1. I think the cvm.test function/package is suitable for CRAN (rather, I can't make a compelling argument it should be added to the base distribution).? It doesn't directly extend anything in the base R distribution at the moment (at least, to my knowledge). 2. I think it would be ideal for stats::ks.test() to be updated using the new ks.test.R and ks.test.Rd. I'll spare you the longer argument, but there are simple examples of a "bug" (quotes intended, because it surrounds non-intended functionality with discrete distributions) in stats::ks.test(). 3. Finally, I note the presence of a <FIXME> in stats::ks.test() that looks rather straightforward.? I'd be happy to do this <FIXME> as part of this contribution (though perhaps I should read the cited paper and conduct some simple simulations). A simple, "that would be great, Jay" or "don't bother" would suffice -- it may be that someone else is working on it. Thoughts welcome, either on these particular issues, or on the manner in which they relate to John's thread. Cheers, Jay -- John W. Emerson (Jay) Associate Professor of Statistics Department of Statistics Yale University http://www.stat.yale.edu/~jay