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Comment by alkonaut | Hacker News Reader

I think it goes without saying. PBT shouldn't be random-random (e.g. use a timestamp or cryptographic seed), it should be deterministically pseudorandom if it uses random values. You shouldn't be able to run it 10 times and get 9 pass and one failure. It's either 10 passes or 10 failures.

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> You shouldn't be able to run it 10 times and get 9 pass and one failure. It's either 10 passes or 10 failures.

With property based testing, it actually CAN be 9 passes and 1 failure, because that one single fail can be hitting an edge case the others just aren't. In fact, only a few failures are more likely than it being all failures

That is the one thing about PBT that worries me. I can write code and all tests pass, then next week the edge case I missed randomly is hit by a coworker who now has to figure out why their change broke my code (it didn't).

I can tell you from experience that random failures cause loss of trust. People learn to ignore failures and just keep hitting rebuild until the tests pass. People will not investigate test failures in code that they don't understand.

That's a fair concern. I can only really suggest upping the amount of test cases that are ran when merging so that you get a much more extensive run for that time, and later dial it back. Along with having the seed included in the failure case, so that you can bisect to check what actually broke that test. Also, implementing a standard test alongside the property based on, for all bugs you encounter over time (basically "hard coding" one of the failure cases)

But yeah, probabilistic testing isn't perfect.

Potentially using the git hash as a seed would make sense, so for a given snapshot of code it is always going to be deterministic. When the git hash changes (i.e. your code) then that would result in a different set of test inputs running.

Allowing reproducibility for a given change set.

That's a pretty good idea, actually. Using the git hash as a seed to seed the rng for the different runs of the PB tests.

Didn't even enter my mind.

Using a git hash still has the problem of a co-worker's changes (which alter the git commit) causing an unrelated property to fail.

Hypothesis has a nice option, to pick the seed for each property by hashing that property's code. It's a nice idea, but relies on Python's highly dynamic nature; so may not be easy/possible in other languages (especially compiled ones).

So lock the seed in that case?

If you lock your seed you are worse than unit tests - odds are you are not testing some interesting cases ever. The whole point of PBT is there are some properties that hold in all cases (well technically in the domain of the function inputs), so try random examples to see if I missed something. Generally the domain of all possible function inputs is a very large set such that exhaustive testing is impossible. The more different random seeds we try the better the odds we eventually catch some case that we didn't handle correctly.

This is fair, but also a tooling or process problem.

The co-worker should add the test to a new branch / test it on main. If it fails that's a new ticket (with the great side effect of having a failing test). If that passes it's a problem in their branch. If not it's the same as having a broken main which happens anyway and you deal with that as you usually do.

Usually though the failure case inputs should be stored, so that once the test fails, it will fail again, no matter how often you hit the run or rebuild button.

When would that be preferable to have nondeterministic random?

I don't think I have said anything about it being nondeterministic.

You can have a prng seeded from something like the commit hash and have prngs generate the test cases. That still can fail on 1/10 tests for a particular run.

With PBT you generate an arbitrary number of inputs, ideally they all pass. However it's entirely possible that you have an error in your program and the property only holds for some inputs, but not all. In that case, since each execution starts with a different seed (unless you provide a specific seed, in which case the generated inputs should be exactly the same each time), you may have some executions that always pass, some that always fail, and others that are in between (have a mix of passes and failures). This is expected.

Just as an anecdotal experience. It doesn't necessarily go without saying.

The most memorable discussion I had around PBT was with a colleague (a skip report) who saw "true" randomness as a net benefit and that reproducibility was not a critical characteristic of the test suite (I guess the reasoning was then it could catch things at a later date?). To be honest, it scared the hell out of me and I pushed back pretty hard on them and the broader team.

I have no issue with a psuedo-random set of test cases that are declaratively generated. That makes sense if that is what is meant by PBT. Since it is just a more efficient way of testing (and you would assume this would allow you to cast a wider net).

This dilemma is of course trivially solvable by persisting a (presumably randomly generated) RNG seed with each test run. You just have to ensure that your RNG is configured once with the seed at the beginning of each test run.

What's the issue you have?

The idea is you have random testing and the test failures are added as explicit tests that then always get run.

Is that so different from someone else testing?

The main issue is you stumble across a new issue in an unrelated branch, but it's not wildly different from doing that while using your application.

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