[SciPy-Dev] User Acceptance Testing

[Joshua Grant]

Well, first off, let me say that if there are any packages missing unit
tests or lacking coverage, I would definitely look into making that a
project for myself :)

As for the functional testing, that's more or less what I was thinking of
doing. Basically, a test could be a block of code that does some nontrivial
task (eg computing and plotting results from a SDE) using different parts of
the numpy/scipy libraries. The idea is see how different functions from
different modules interact with each other, and how they work "in the wild".
However, I'm fairly confident that if the unit testing returns positive, the
functions would work correctly. I'm open to more discussion about testing /
QA aspects of numpy/scipy though.

On Sat, May 14, 2011 at 11:45 AM, <josef.pktd at gmail.com> wrote:

> On Sat, May 14, 2011 at 11:16 AM, Robert Kern <robert.kern at gmail.com>
> wrote:
> > On Sat, May 14, 2011 at 08:02,  <josef.pktd at gmail.com> wrote:
> >
> >> And as an acceptance
> >> test, I have never heard of anyone running numpy.random through the
> >> randomness test suites http://en.wikipedia.org/wiki/Diehard_tests .
> >
> > The DIEHARD tests are for uniform RNGs. For that, we use the original
> > Mersenne Twister code directly, and that has already been thoroughly
> > tested by DIEHARD and other such suites.
>
> Thanks, good to hear, I didn't know the implementation in numpy has
> been tested.
>
> I'm pretty confident about the transformed random variables that are
> used in scipy.stats.distributions, since I have tortured them enough,
> I think.
>
> Josef
>
> >
> > --
> > Robert Kern
> >
> > "I have come to believe that the whole world is an enigma, a harmless
> > enigma that is made terrible by our own mad attempt to interpret it as
> > though it had an underlying truth."
> >   -- Umberto Eco
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> >
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