Question

I have some code which delivers things based on weighted random. Things with more weight are more likely to be randomly chosen. Now being a good rubyist I of couse want to cover all this code with tests. And I want to test that things are getting fetched according the correct probabilities.

So how do I test this? Creating tests for something that should be random make it very hard to compare actual vs expected. A few ideas I have, and why they wont work great:

• Stub Kernel.rand in my tests to return fixed values. This is cool, but rand() gets called multiple times and I’m not sure I can rig this with enough control to test what I need to.

• Fetch a random item a HUGE number of times and compare the actual ratio vs the expected ratio. But unless I can run it an infinite number of times, this will never be perfect and could intermittently fail if I get some bad luck in the RNG.

• Use a consistent random seed. This makes the RNG repeatable but it still doesn’t give me any verification that item A will happen 80% of the time (for example).

So what kind of approach can I use to write test coverage for random probabilities?

Answer 1

I think you should separate your goals. One is to stub Kernel.rand as you mention. With rspec for example, you can do something like this:

test_values = [1, 2, 3]
Kernel.stub!(:rand).and_return( *test_values )

Note that this stub won’t work unless you call rand with Kernel as the receiver. If you just call “rand” then the current “self” will receive the message, and you’ll actually get a random number instead of the test_values.

The second goal is to do something like a field test where you actually generate random numbers. You’d then use some kind of tolerance to ensure you get close to the desired percentage. This is never going to be perfect though, and will probably need a human to evaluate the results. But it still is useful to do because you might realize that another random number generator might be better, like reading from /dev/random. Also, it’s good to have this kind of test because let’s say you decide to migrate to a new kind of platform whose system libraries aren’t as good at generating randomness, or there’s some bug in a certain version. The test could be a warning sign.

It really depends on your goals. Do you only want to test your weighting algorithm, or also the randomness?