How to unit test a pseudo random number generator?

Question

I have a pseudo random number generator (PRNG) class that I want to unit test. There are two approaches:

1. write a test case that takes a large amount of samples and test whether they are properly distributed. This approach may lead to a fairly long execution time for the test case;
2. calculate a small series of samples 'by hand' and verify if the PRNG algorithm reproduces it. This approach may lead to a not random sequence being generated without being noticed;

I would say that the first approach is not really unit testing because it does not perform a white box test of the generator, but on the other hand it properly tests the responsibility of the class. The second approach is more like a real unit test, focusing on the algorithm, but it does not provide as much evidence as to whether the class fulfills its responsibility.

Which approach do you prefer, and why?

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Answer 1

Here's a CodeProject article that includes an implementation of the Kolmogorov-Smirnov test mentioned in Donald Knuth's volume 2, Seminumerical Algorithms. As InSciTek Jeff mentioned above, there are two issues: testing the algorithm and testing your implementation of the algorithm. The K-S test is likely to find bugs in the implementation, and it's a good start toward testing the quality of the algorithm itself.