Recommended ML algorithm for mapping files to tests

post by Rubyakerman on Oct 26, 2019

Hey,

I’m searching the best algorithms can help me mapping 10,000 files (code files), on some 40 repositories, for 3 different projects, to 7,000 tests for detecting for each file/repository/project what are the most failing tests it usually failed on, and for each repository/project so I’ll be able to minimize the number of tests will be running (on a daily bases) for updates to the current files/new files were just added to some repository/project.

What kind of algorithms would be suitable for this? Classification? Clustering?

some preffared algorithm?

Thanks

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