Evolution & Future of Software Testing
summary
Shows concrete shifts: manual tests replaced by automation, waterfall replaced by Agile, seasonal releases replaced by CI/CD, and machine learning added to reduce maintenance. Names tools and tactics: SonarQube for test-code quality, NLP that converts plain steps into runnable tests, visual models for locators and self‑healing locators, anomaly detection on execution time (typical case ~30s) and a deployed bag‑of‑words bug triage model that predicts priority and improves assignment consistency. Results report reduced false alarms and faster triage.
AI-written summary · about
chapters (14)
- 0:00Software testing evolution
- 3:04Why testing must evolve
- 5:55Manual testing to automation
- 9:06Test automation challenges
- 15:07Waterfall to agile transition
- 17:36Agile testing collaboration
- 19:18Shift to continuous integration and deployment
- 23:27ML in software testing
- 31:36AI test case design
- 34:52ML for test execution
- 37:22AI bug triage
- 41:40Summary and future
- 42:45Q&A: QA in development
- 44:31Q&A: Waterfall to agile
related talks
08mEvolving of test automation past to present 
38mNext Generation Testing in the Age of Machines
01h 08mTest Automation Monsters
55mQuality Engineering Evolution: What Lies Ahead in
47mHow Testing is Evolving in DevOps
25mFuture of Software Testing: Machine Learning Assistance
42mIn Five Years There Will Be No Testers Left
44mThe future of test automation