According to Google research, 84% of failures that look like code regressions in CI systems are actually caused by unstable tests, not real bugs. Atlassian estimates that its engineering organization loses more than 150,000 developer hours per year investigating failures generated by flakiness. In this guide, you will understand what flaky tests are, what the

The bug was right there. Clear, documented, with a screenshot, with step-by-step reproduction. The QA reopened the ticket for the second time. The dev looked into it, tested on their own environment, couldn’t reproduce it. Both are sure they’re right, and neither of them is completely wrong. This scene plays out in virtually every software

There’s a situation that repeats itself across many QA teams: dashboards are packed with numbers, reports go out every week, and yet nobody can clearly answer whether the tests are actually working. The data is there, the problem is that nobody really knows what to do with it. QA metrics don’t exist to fill up

There’s a scenario that repeats itself across many QA teams: the test suite has grown over time, reaching hundreds, sometimes thousands, of test cases, and suddenly the pipeline starts taking hours to run. Failures show up, but when you dig into them, a large portion is flagging the exact same problem across different tests. The

Every development team tests software. The question is whether they do it strategically, knowing exactly which type of test to apply at each stage. There are dozens of types of tests, and choosing the wrong one at the wrong time has a real cost, lost development time, expensive rework, or in the worst case, production