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Endigest AI Core Summary
This post introduces Just-in-Time Tests (JiTTests), an AI-driven testing approach designed to keep pace with agentic software development.
•Traditional testing relies on static, manually authored test suites that require constant maintenance and struggle with false positives as code change velocity increases.
•JiTTests are generated on-the-fly by LLMs the moment a pull request is submitted, targeting regressions introduced by a specific code change.
•The process infers the intent of a change, creates mutants (deliberately faulty code versions) to simulate failures, then generates and runs tests against those mutants.
•Rule-based and LLM-based assessors work together to filter out false positives and surface only true regression signals.
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Tests are not stored in the codebase, eliminating maintenance overhead and requiring human review only when an actual bug is caught.
This summary was automatically generated by AI based on the original article and may not be fully accurate.
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