Mutation testing is a neat idea I'd not heard of. Wonder how well it works in practice.
Someone's implemented a package for doing it with Go which looks good: https://github.com/zimmski/go-mutesting
Someone's implemented a package for doing it with Go which looks good: https://github.com/zimmski/go-mutesting
The problem I had is that there were many many mutations which led to code which was functionally identical, just a bit slower, or took a different route. You have to manually verify every mutation to check if this.
For one mutation it took me 30 minutes to convince myself the algorithm was still doing the same thing, just in a different way.
I usually use coverage as a tool to remind me of pieces of code I intended but forgot to test [1], so setting it to an arbitrary percentage is not that useful, in my opinion. If 100% is not feasible usually as well, that makes Mutation Testing in general not worth the effort.
Again, take my opinion with a grain of salt.
Often an integration test would catch the multiple mutations also being caught by (different) unit tests.
I assume that you mean that if a certain (broader) test kills the same mutants as X unit tests, those X tests are not really necessary?
I've looked into https://github.com/boxed/mutmut and https://github.com/sixty-north/cosmic-ray for Python project, and there it is only important that a mutant gets killed, but not how often and by which tests (therefore you can use `pytest -x` to continue with the next mutation after the first test failed due to it).
In my experience, you usually end up with much more coverage than you want or need.
[1] https://docs.microsoft.com/en-us/visualstudio/test/intellite...