Foundations: ML for Software Quality

Define flaky tests and their impact on CI/CD pipeline reliability.

Define technical debt and identify common indicators in a codebase.

Describe how ML-based test case generation differs from traditional methods.

Formulate flake detection as a classification problem, debt prioritization as a ranking problem, and test creation as a generation problem.

Compare the three project directions based on data requirements, implementation complexity, and potential impact.