What are the most important lessons learned from regression testing projects?

Majorly the need of regression testing comes when there is a change. This could be due to a change in the feature or a bug fixed, in either of the case the first thing you need to make sure that the feature or the bug fixed should work according to the expectation. The 2nd step should be the impact analysis which will tell you the areas which we need to run the basic testing to make sure that nothing is broken due to the change.

I've learned that in regression testing, it's vital to maintain thorough test documentation, ensure stable test environments, leverage automation for repetitive tasks, prioritize tests based on risk, and foster collaboration with development teams. These lessons have proven invaluable in delivering high-quality software

Regression testing projects have imparted crucial lessons in the software development domain. The indispensability of test automation for ensuring application stability amid continuous evolution stands out prominently. Sustaining a robust and scalable test suite is vital for early detection of regressions. Continuous integration and CI/CD pipelines have been identified as pivotal components for swift and frequent execution of regression tests. Lastly, the adaptability of testing strategies has proven crucial, underscoring the need to adjust approaches in response to rapidly changing requirements and features while maintaining optimal software quality.

Regression testing is a critical process in software development that involves retesting previously tested software to ensure that changes or updates have not introduced new defects or issues. Over the years, many lessons have been learned from regression testing projects. Here are some of the most important ones: 1. Plan ahead 2. Prioritize test cases 3. Automate where possible 4. Use a version control system 5. Monitor test coverage 6. Involve stakeholders 7. Analyze test results 8. Continuously improve

1. Ensure that regression test suites cover a comprehensive range of functionalities, including critical and frequently used features. 2. Prioritize regression tests based on the impact of changes. 3. Automate repetitive and time-consuming regression tests to speed up the testing process. 4. Regularly update and maintain regression test cases to reflect changes in the application. 5. Implement version control for test artifacts, including test cases and scripts. 6. Ensure the stability and consistency of the test environment. 7. Maintain traceability between changes in the application and corresponding regression tests. 8. Include negative testing scenarios in regression test suites.

In my experience automation is a key part of regression testing. As the idea of regression tests is to verify that new features or bug fixes don't break existing functionality, having a pipeline of stable automated tests running on pull requests is one of the most reliable ways of ensuring the software quality, especially if the company wants to scale and have more frequent deployments. Keep in mind that a regression test suite doesn't need to be full of end-to-end tests, as they are slower and more expensive to maintain. The ideal test suite would be a mix of tests of different granularity (like unit, API, acceptance, integration, and some end-to-end where they are really needed).

As we always say that 20% tests are impacting 80% of the functionality. So we need to first run these 20% cases and then the remaining set because there is a high chance of finding issues in these first 20% cases only. In regression runs we should not leave any area untested. Be it low be it high be it medium… doesn’t matter. A bug can be found in any of these areas so we should be very clear while differentiating between regression and sanity run.

Regression testing is useless with poor monitoring and reporting, so you should not just have a solid automated test pipeline, but also a good system to help you monitor and report the test results. Tools like Allure and DataDog do great work in generating reports of test suites. You can integrate them with your CI/CD pipeline, configure them to generate reports as a post-test step, and then share the results with stakeholders (like QA Engineers, Developers and Product Managers) directly on the pull requests, by email or slack.

Hofstadter's law is true. It will take more time than you anticipated, even when you factor in that exact scenario. Therefore, it may be optimal to identify time-consuming activities from earlier regressions in order to not underestimate the time needed for your regression suite. This can vary from aspect to aspect: Writing a bug ticket for feature A can take considerably more time than for feature B, switching documentation systems can save up effort in that regards.

Regression testing is crucial for ensuring existing features works and identifying new bugs. It is integral to the SDLC. It's time-consuming and complex as products evolve, resulting in a large number of tests. Communicating the value of regression testing to stakeholders can be challenging, as executives may prioritize moving the product forward over testing. Re-test everything, selective re-testing, and prioritized re-testing - the chosen approach depends on factors like the size of impacted code and available resources. Automation is important for efficient regression testing. To succeed in agile, a testing team should start building the regression suite early in product development and continue expanding it alongside dev sprints.