> Always include some randomness in test values.
If this isn't a joke, I'd be very interested in the reasoning behind that statement, and whether or not there are some qualifications on when it applies.
Must be some Mandela effect about some TDD documentation I read a long time ago.
If you test math_add(1,2) and it returns 3, you don't know if the code does `return 3` or `return x+y`.
It seems I might need to revise my view.
humans are very good at overlooking edge cases, off by one errors etc.
so if you generate test data randomly you have a higher chance of "accidentally" running into overlooked edge cases
you could say there is a "adding more random -> cost" ladder like
- no randomness, no cost, nothing gained
- a bit of randomness, very small cost, very rarely beneficial (<- doable in unit tests)
- (limited) prop testing, high cost (test runs multiple times with many random values), decent chance to find incorrect edge cases (<- can be barely doable in unit tests, if limited enough, often feature gates as too expensive)
- (full) prop testing/fuzzing, very very high cost, very high chance incorrect edge cases are found IFF the domain isn't too large (<- a full test run might need days to complete)