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Imagine that your application is working as if it has no issues at all. This makes customers happy, and you are ready to launch a new feature in the next update. But with the arrival of a new update and new code, everything breaks! It does not only mean that a new feature does not work as intended but also that all functions cease to function correctly. Your team quickly looks for the errors and corrects them, often resulting in increased time, extra costs, and a drop in your company’s credibility.

End-to-end (E2E) testing and regression testing are critical aspects of software testing that play very different roles. E2E Testing evaluates the entire application, simulating real user experiences. In contrast, regression testing checks if recent updates or changes have inadvertently disrupted existing functionality. Choosing the right testing strategies is as important as testing frequently.

The modern-day SDLC methodologies such as agile, CI/CD, and DevOps are flexible enough to incorporate change requests in each sprint, which increases the probability of introducing errors in existing functionality. This makes validating existing functionality, detecting newly introduced bugs, and resolving them mandatory in each build release. Whether manual or automated, such software testing is widespread and referred to as regression testing.

Regression defects are unexpected errors that arise in previously functional software following updates or modifications to the codebase. A significant 85% of development managers agree that reducing technical debt, including regression defects, without compromising innovation has become increasingly difficult. If you’re like most software developers or testers, you’re always looking to improve the quality of your code. One way to do this is by understanding and preventing regression defects.

Regression testing is boring…if you are doing it manually. Indeed, it’s just not efficient when you have to manually repeat the same test steps over and over each iteration. Regression testing is best done with a regression testing tool. These tools allow you to create an automated regression test suite that you can run as a batch when the new build is available. Let’s check out the top regression testing tools on the current market. Here's a quick list.

In today's dynamic software landscape, teams struggle with where to invest their time: new feature testing or regression testing. Obviously, ensuring the reliability and stability of applications is paramount so that the end-user experience is not impacted. However, teams must also ensure that new features and capabilities that will propel the company's business to the next level are also properly tested and ready to be put in the hands of the end users.

Here at SmartBear, our motto is that quality isn’t just the goal, it’s the whole point. The software development process is intricate and dynamic, with constant changes being made to meet evolving user requirements and address defects. However, with these changes come potential risks. One of the most significant challenges in software development is ensuring that making modifications to an application does not inadvertently break existing functionality.

Adding new features or enhancements to an app is a good thing – unless the changes trigger an unexpected problem. To protect against this risk, QA teams and developers can leverage automated regression testing, which offers a fast and efficient means of confirming that software upgrades or changes don't introduce bugs into applications.

Regression testing is a must-have testing activity. A quite common best practice is to build a regression test suite consisting of many related test cases for a particular feature. This test suite is scheduled to run automatically after a code update to check if that particular feature is affected by the update. The real question is not about how to build a regression test suite, but rather, on what criteria we should categorize our test cases.

Regression testing is a necessary process that grows over time, consuming larger amounts of testing capacity as applications scale in features. Katalon TrueTest™ addresses this hurdle by using artificial intelligence (AI) to allow quality engineering teams to realign their limited resources to spend more time validating and testing new release features while relying on Katalon to create, maintain, and run regression tests on existing application code.