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That sounds like a problem of too-tightly coupled tests.


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I still don't understand why that would cause testing to be hard, but since you won't explain it... I guess it leaves me thinking the problem might not be entirely them.

Essentially the problem is that our testing isn't perfect.

Tests must not be robust enough, then.

There are tradeoffs to this approach. When the tests break it becomes a lot harder to triangulate the origin of the problems.

Sounds like test data gone awry

All tests are problematic; some are more so.

sounds like the tests are bad.

Flawed tests.

Tests can have bugs too.

With mutable global state I wouldn't be too sure it's the tests that are the problem.

Sounds more like the problem is means-testing with strict cutoffs. Mean-testing is good in helping to even the field, the problem is that (some of) our current programs don't slowly fade out as you climb up.

Can you elaborate a bit on how such testing is done, or share a good article on the topic? It sounds like a hard problem to need to get things right this bad, or else.

It also needs to be corrected for test strategy.

Perhaps an unrealistic test environment?

Yeah sorry, I was just trying to be succinct in the post, I been working on fixing some tests lately so I guess that's why it came to mind.

Writing tests for this feature might be difficult.

But it has broken tests in the similarity tests.

I found that in some of our code the other day, even that wasn't enough to stop the tests from randomly failing.

Possibly, or a myriad of other factors as well, which is why designing proper control/test groups is extremely difficult.
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