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Regression test cases are a core part of any stable release cycle. They help you confirm that what used to work still works, even after new features are added or bug fixes are applied. But not every regression test case should be automated. Some are too brittle. Some don’t run often enough. Others are simply not worth the maintenance effort. So how do you decide which ones are worth automating? This article will guide you through exactly that.

Software updates are inevitable. New features get added. Old bugs get patched. But with every change, there’s one big question: what might break? That’s where a solid regression test strategy comes in. A regression test strategy gives you a reliable process to make sure your existing features still work after each update. Without it, even the smallest change can lead to unexpected bugs in places no one thought to look.

Regression testing helps you make sure that old features still work after new changes are made. With automation, this process becomes faster, more reliable, and easier to scale. But automation can easily become messy. Tests break. Suites grow too large. Bugs slip through. That’s why you need a strategy: one that focuses on the right automated regression testing best practices.

Automated functional testing is more than just running tests on autopilot. It's a way to ensure that your software behaves as expected, across all features and platforms, without slowing down development. But it’s not automatic by default. To get the most out of your efforts, you need to apply the right strategies from the start. That’s where automated functional testing best practices come in. They help you avoid brittle scripts. They reduce maintenance headaches.

Software changes fast. Every new update, bug fix, or feature risks breaking something that used to work. That’s why teams rely on regression testing to make sure the old stuff still runs smoothly. But here’s the challenge: you can’t test everything, every time. Regression test suites get large, fast. Running all of them slows teams down. That’s where a risk-based approach for regression testing makes all the difference. Instead of testing everything, you test what matters most.

Regression testing is the process of re-running tests to make sure new code changes don’t break what used to work. It acts like a safety net. If your app used to calculate prices correctly, and now it doesn’t because of a new update. Regression tests are what tell you something broke. Now here’s the real question: should you run those tests manually or automate them? That’s where the discussion around manual vs automated regression testing begins.

Test scripts break. It’s one of the most frustrating parts of test automation. You update a button. The UI layout shifts. Suddenly, dozens of test cases fail because the locators no longer work. This is where self-healing test automation enters the scene. Instead of failing outright, these smart tests diagnose the issue, find an alternative path, and continue running.

Regression testing is one of the most important parts of software testing. It’s how you make sure that old features still work when new code is added. But running regression tests isn’t enough. You need to maintain them. Test maintenance means updating, cleaning, and adjusting your regression tests to match the latest changes in your product. Without it, your tests break, false positives increase, and your team loses trust in your test suite.

When Katalon made the decision to run its own quality practice entirely on the Katalon platform, it wasn’t just a symbolic gesture. It was a deliberate business decision to replace fragmented tools, eliminate reporting silos, and sharpen product-market fit—all while holding itself to the same standards expected by our customers.

Recently I had the joy of talking to Daniel Knott, a well-known YouTuber and QA leader in the Healthcare testing space. He shares a lot of his knowledge and experience on his channel as well as his blog called Adventures in QA. In this interview, we talked about how Daniel found himself in the QA world, how he applies automation testing in his day-to-day work, and the implications of AI for Healthcare testing. Here are some takeaways from the discussion for you.