SciPy has been switched over to use numpy.testing, scipy.testing has been removed, and it seems like everything is ok with the unit tests. Unlike NumPy, SciPy doesn't import all its subpackages on "import scipy", so the doctests need some slightly different execution context rules. Right now it looks like tests will have the module in which they are declared made available to them. So, for example, a doctest for scipy.linalg.qr will have linalg available in its context (an implicit "from scipy import linalg"). Of course this means there's a ton of SciPy doctests that need to be updated so that they'll run again.
The monkeypatching of the nose doctest plugin in numpy.testing.nosetester, which was originally a method or two, has gotten a little out of hand (as pointed out by others on the numpy-discussion list), so I'm in the process of changing over to use a new plugin (subclassed from the nose doctest plugin, numpy.plugins.doctest.Doctest). I'm also going to replace the decorators used to write the NoseTester method docstrings; since there's no other decorators used in NumPy, I'm not going to be the one that adds them. ;) Hopefully all that should be done tomorrow.
The __mul__ issue for defchararray was interesting; it appears if you pass a NumPy integer type to ndarray.__new__ as the itemsize argument, it uses the itemsize of the integer object rather than the value held by it, so (on my 32-bit machine) this meant that the return array always used an itemsize of 4 bytes. I'm not sure if this behavior is intentional.