TIA Configuration

Test Impact Analysis (TIA) settings is designed to empower you to tailor TIA behavior to your specific project needs, resulting in increased efficiency.

How It Works?

  • Default TIA Configurations: When creating a new branch within a configured application, predefined TIA settings are automatically applied. This streamlines your workflow by eliminating the need for manual setup on each new branch and by ensuring consistent testing practices across your codebase. You can customize these default settings to determine if TIA is enabled by default and set the frequency of full test runs.

  • Recommendation Mode: It is possible to choose between two modes:

    • Build-Based Recommendations: If multiple test runs are associated with the same build, they will share the same set of recommended tests. This approach may lead to redundant test executions, especially for frequently re-run builds (e.g. re-running passed tests, even though no code changes were made).

    • TSR-Based Recommendations: Recommendations are generated for each TSR, focusing on tests that failed or were not executed in previous runs within the same build. This approach optimizes test execution by avoiding unnecessary test re-runs.

  • TIA on Pull Request: The system analyzes code changes within a pull request and determines which tests are impacted. Only these affected tests are executed, optimizing test efficiency. To leverage this feature, integrate your CI/CD pipeline with SeaLights to trigger the desired test stages as part of the pull request process.

  • Full Run Policy: SeaLights automatically schedules full test runs to maintain test data accuracy. You can define the frequency of these runs (daily, weekly, monthly, or every X runs). This policy can be changed at any time.

  • Manual Full Run Trigger: Manual full runs can be initiated as needed, but the system reverts to the scheduled policy afterward.


By leveraging these enhanced TIA settings, you can significantly improve the efficiency and effectiveness of your testing processes, leading to higher quality software and faster time-to-market.

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