[MATRIX-SIG] Question: [Numeric/Numerical Recipes/Regression tests]

[Mike Miller]

Something Paul Dubois said a few days ago reminded me that I
hadn't followed up here about the solution to my random.gauss
problems. 

>>>>> "Paul" == Paul F Dubois <dubois1@llnl.gov> writes:
    > I have the view that the most important reason to strive
    > for reusable components is not the time it saves you to
    > write them but the reliability of reusing a well-tested
    > component. 

I second this very strongly.  In my experience there has been no
doubt that code that is widely used and believed to have been
well tested gets much more use than something that is less well
known, even if the latter has a lot of potential.  Example: there
is a package that I've used regularly for graphics for some
years now, but I'm very hesitant to use it's built-in
computational capabilities because it had some serious problems
with memory management in it's youth.  Even though those problems
are long gone, I still remember being bitten by them and a bit
shy because of it.  

I bring this up here because of the problem I found with
random.gauss.  It was simple to fix this routine so that it does
what it is advertised to do (there is a patch available).
Nonetheless, this has put me off somewhat because it was, IMHO,
an obvious error, visible on first glance at the distribution,
yet the author of the algorithm needed some convincing to see
that it was there.

This all came up the other day when I was trying to explain to a
perl-advocating colleague that Python is a useful object, rather
than a poor second place to perl as he thought.  But I had to
admit to him that I found faulty code in my first effort to use
Python for a rigorous calculation.

This is a bit rambly, so let me get to my question: How does one
know what has been carefully tested in Python and what has been
given only a cursory look and declared correct?  If someone came
to me and wanted to know about the reliability of some module,
what would I say to them?

Mike


-- 
Michael A. Miller                                miller5@uiuc.edu
  Department of Physics, University of Illinois, Urbana-Champaign
  PGP public key available on request

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