I have an algorithm that produces non-deterministic results due to in-built fuzziness, i.e. it is intended to return unpredictable results about 20% of the time.

My query is how best to build a test case for this. Obviously I could just throw 100000 tests against the code and verify that e.g. 78-82% of the results were expected, but I'm wondering if there's a more efficient way to do it?

I fully expect that one day the results will fall 0.1% outside the threshold and thus the test will fail, so I'd also like to guard against that if possible - that is, the testing method used should perhaps take an average over three or five runs.

In reply to Non-deterministic Testing by moot

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