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Faster CI with Selective Testing
Li Haoyi, 24 December 2024 Selective testing is a key technique necessary for working with any large codebase or monorepo: picking which tests to run to validate a change or pull-request, because running every test every time is costly and slow. This blog post will explore what selective testing is all about, the different approaches you can take with selective testing, based on my experience working on developer tooling and CI for the last decade at Dropbox and Databricks.
Folder-based selective testing works fine for codebases with 10-100 developers: there are occasional cases where a breakage might slip through, but generally it’s infrequent enough that it’s tolerable. This approach basically automates the manual tweaking described in , and instead of some senior engineer trying to use their intuition to guess what tests to run, the ML model does the same thing. You can then easily tune the model to optimize for different tradeoffs between latency and thoroughness, depending on what is important for your development team at any point in time.
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