Unit Test Quality Tracking using AI

Unit testing is often treated as a checkbox—but without visibility, it rarely acts as a true quality gate. This 1:1 working session focuses on building an automated Unit Test Monitoring Dashboard that makes auto-quality gates a measurable part of your Definition of Done (DoD).

In this session, we integrate your CI/CD or test execution data to track:

1. Unit test coverage trends
2. Pass/fail stability across builds
3. Test execution reliability
4. Regressions caused by weak test gates
5. DoD compliance through automated quality signals

We then convert this data into a live dashboard and rule-based quality gates that help teams and leaders:

1. Enforce engineering discipline without micromanagement
2. Prevent low-test-quality code from reaching higher environments
3. Detect test debt before it becomes production risk
4. Shift quality conversations from opinion to evidence

✅ You’ll walk away with:

1. A working unit test monitoring framework
2. Clear visibility into test health and coverage trends
3. A practical approach to learn and apply automated quality gates
4. Guidance to embed test signals directly into your DoD and release criteria

⚠️ Technical Requirements (Read Before Booking)

1. Codebase Access: You must have read access to the service or application codebase where unit tests are implemented
2. Environment: VS Code installed with GitHub Copilot active
3. Access: Access to CI/CD pipeline or test execution reports (GitHub Actions, Jenkins, Azure DevOps, etc.)
4. Dashboards (Optional but Helpful): Access to existing test reports or quality dashboards, if any
5. Skill Level: Not for absolute beginners. You should be familiar with Agile workflows and comfortable reviewing code and test outputs, even if you don’t write tests daily.