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Regression testing is a software testing practice that ensures recent code changes do not negatively impact the existing functionality of an application. It involves re-running previously executed test cases to verify that new updates - such as bug fixes, enhancements, or feature additions - do not introduce defects into previously working software components. The primary goal of regression testing is to maintain software stability while allowing continuous improvements.

AI has been booming and has become a transformative force in several industries, software testing and QA are no different. With the evolution of technology and complexity of applications, automation and big-volume data analysis require extra assistance, and that’s where AI might come in handy. In QA, AI could help improve the efficiency of test management tasks, reducing manual effort.

Nowadays, efficient and integrated testing tools are essential for delivering quality quickly. Forrester's 2025 Total Economic Impact of Xray report illuminates how Xray helps organizations streamline testing processes, improve collaboration, and gain significant cost savings.

Nowadays, data-driven testing has become a critical approach for improving test coverage and ensuring software reliability. By executing test cases with multiple sets of data, teams can validate application behavior under various conditions without manually creating numerous test scripts. This enhances efficiency and uncovers defects that might otherwise go unnoticed in static test scenarios. However, data-driven testing also comes with challenges.

Test automation is an essential component when it comes to delivering high-quality software. However a lot of QA teams face challenges when it comes to deciding which test cases they need to prioritize for automation. The selection process can be hard, especially if you consider the limited resources that these teams sometimes have and complexity of modern applications.