QA Forum 2025 5 26ΒΆ
Todayβs discussion focused on the current status and improvements in Backend Testing. We covered key topics including:
- Ensemble exploratory testing
- Postman toolkit
- Regression testing status
- Smoke and risk tests
- AI in testing
- QA forum highlights
π Key Discussion PointsΒΆ
β Ensemble Exploratory TestingΒΆ
- Multiple targeted sessions were conducted for different areas.
- These sessions proved valuable for quick feedback and laid a strong foundation for app and regression testing.
- Andy raised the question:
βDo we need to invest this much time and effort? Should we consider fewer people but run these sessions more frequently?β
Action item: Re-evaluate session frequency and participant count for future sessions.
π Regression TestingΒΆ
- Victor suggested building trend charts, similar to integration tests, to better visualize progress.
To-Do:
- Continue monitoring regression test effectiveness
- Build user creation into the internal testing API
π€ AI in TestingΒΆ
AI is showing promise in:
- Checking test coverage
- Supporting integration testing
- Lars created a regression test project using AI.
Next step: Develop a prompt template to help others reuse and extend this AI setup efficiently.
Additional AI-driven ideas:
- Ticket review automation
- Test scenario suggestions
- Specification improvement recommendations
π₯ Risk TestsΒΆ
- Risk tests in certain areas are not run in the CI pipeline.
- Gudmundur noted these tests are largely covered by existing risk tests.
- Since they are rule-dependent and potentially redundant, we may consider removing them from the repo.
π Recognizing ContributionsΒΆ
We also sent out prizes to developers who have made outstanding contributions to quality and testing efforts.
π A big thank you to everyone for your collaboration and commitment!
π Final NotesΒΆ
The meeting was productive with forward-looking ideas on improving our backend testing processes using both manual strategies and AI-driven innovation. A few action items are emerging, particularly around optimizing effort and AI opportunities.