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100% code coverage is near-meaningless - but is there a good measure to use? (feddit.uk)

submitted 1 year ago by [email protected] to c/[email protected]

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Is there some formal way(s) of quantifying potential flaws, or risk, and ensuring there's sufficient spread of tests to cover them? Perhaps using some kind of complexity measure? Or a risk assessment of some kind?

Experience tells me I need to be extra careful around certain things - user input, code generation, anything with a publicly exposed surface, third-party libraries/services, financial data, personal information (especially of minors), batch data manipulation/migration, and so on.

But is there any accepted means of formally measuring a system and ensuring that some level of test quality exists?

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[–] [email protected] 2 points 1 year ago (1 children)

We are running the above pi tests with an extra (Gradle based) build plugin so that it only runs mutations for the changed lines in that pull request. That drastically reduces runtime and still ensures that new code is covered to the mutation test level we want. Maybe something similar can be done for C or C++ projects.

[–] [email protected] 2 points 1 year ago

I'm currently working on a C++ project that takes about 10 minutes to do a clean build (Plus another 5 minutes in CI to actually run the tests). Incremental builds are set up, and work quite well, but any header changes can easily result in a 5 minute incremental build.

As much as I'd like to try, I don't see mutation testing being worthwhile for this project outside of maybe a few isolated modules that could be tested independently. It's a highly interconnected codebase, and I've personally reviewed (or written) every test, so I already know they're of fairly high quality, but it would be nice to be able to measure.