Regression testing is a process of testing the software and analyzing whether the change of code, update, or improvements of the application has not affected the software’s existing functionality.
Regression testing in software engineering ensures the overall stability and functionality of existing features of the software. Regression testing ensures that the overall system stays sustainable under continuous improvements whenever new features are added to the code to update the software.
Regression testing helps target and reduce the risk of code dependencies, defects, and malfunction, so the previously developed and tested code stays operational after the modification.
Generally, the software undergoes many tests before the new changes integrate into the main development branch of the code. Still, the regression test is the final test among all as it helps you verify the product behavior as a whole.
Before you start building the regression testing strategy, consider the following:
After considering all these points thoroughly, let us start building the regression testing strategy:
Smoke and sanity testing is carried out before the regression testing, which eventually helps to save time for the testing teams. Sanity testing is run through the basic features of the software before additional testing of the new release, which controls that functionality works as planned.
To carry out smoke testing, you require a subset of test cases that test basic and core software workflow, for instance, startup and login, and can run very quickly.
You can use a smoke and sanity test to quickly identify whether an application is too flawed to warrant any testing further such as regression testing. This procedure is much better than performing regression testing on software that doesn’t load login and starts analyzing why hundreds of thousands of regression tests fail.
Consider a test case scenario that often fails. Some features in the application are so error-prone that they always fail after minor code modifications. During the software lifecycle, you can analyze these failing test cases and include them in the regression test suite.
Regression testing focuses on the software areas with the most significant risk of quality issue. While working with a risk-based approach, a tester must select the test case that covers most of the application areas affected by the changes. You can also rank them according to priority.
The best way to deal with it is to prioritize the test cases according to critical and frequently used software functionalities. When you choose the test cases depending on their priority, you can reduce the regression test suite and save time by running fast and frequent regression tests.
Some regression testing tools integrate with error analyzing tools. It lets you see the details about what happened while performing the regression test; if it fails, research which features fail and exactly which line of code is affected. Error tracking tools help you get screenshots and other metrics about the failure during the regression testing, helping identify and debug the issue.
The tester should communicate with the software owner to analyze changes in requirements and assess them. They should communicate with the developers to understand the changes made during an iteration.
Below, we have discussed some common challenges faced while performing regression testing and make it difficult for the agile team:
Generally, there are two primary regression testing methods implemented on software. Let us understand them in detail below:
Manual regression testing is one of the most basic methods for regression testing for every software regardless of the methodology used in the software, i.e., waterfall model, agile, and others. A regression test suite depends on the test cases describing areas of the application that have undergone modification.
Manual testing always precedes automation, sometimes even more efficient than the latter. For instance, it is impossible to write the test scripts for testing the software areas adjacent to the modified code.
Manual regression testing is more efficient in the early stages of the product delivery process. For example, while developing the iOS image processing software, manual regression testing enables you to detect several bugs causing defects in the app UX. Therefore, the app fails to render the image correctly and crashes when the user changes screen orientation.
However, the main problem with manual regression testing is that it is effort and time-consuming. For complex software, running a regression test, again and again, hinders a tester’s concentration and performance. Hence in these cases, tester teams prefer working with automated regression testing.
Automated regression testing is mainly used with medium and large complex projects when the project is stable. Using a thorough plan, automated regression testing helps to reduce the time and efforts that a tester spends on tedious and repeatable tasks and can contribute their time that requires manual attention like exploratory tests and UX testing.
In the current situation, the tester often starts automated regression testing at the early stages of the software development life cycle. It works well enough for agile development where the developers look forward to deploying the product at least weekly and have no time for warming-up manual regression testing.
The tester team can understand the stakeholder’s needs and the product business logic by communicating with the whole team and studying the use cases thoroughly to find the expected results for testing. The primary task in early automation is to decide the testing framework which provides you with easy scripting and low-cost test maintenance.
In some instances, automation testing allows you to detect the bugs found during manual regression testing. For example, while building an image processing app described above, automation lets you see random bugs using automated testing timeouts.
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