How do you perform regression testing and what tools do you use?

1 Why is regression testing important?

Regression testing is important because it helps to detect and prevent errors that could compromise the software functionality, usability, or security. Without regression testing, new changes could introduce unexpected bugs, break existing features, or cause performance issues. Regression testing also helps to ensure that the software meets the requirements and specifications of the customers and stakeholders.

2 When to perform regression testing?

Regression testing should be performed whenever there is a change in the software code, configuration, or environment. For example, regression testing should be done after adding new features, fixing bugs, refactoring code, integrating components, updating libraries, or migrating to a different platform. Regression testing should also be done before releasing the software to the end-users or deploying it to the production environment.

3 How to perform regression testing?

Regression testing can be performed manually or automatically, depending on the scope, complexity, and frequency of the changes. Manual regression testing involves executing test cases by human testers, following predefined steps and scenarios. Manual regression testing is suitable for small-scale changes, exploratory testing, or testing complex or dynamic scenarios. However, manual regression testing can be time-consuming, costly, and prone to human errors.

Automated regression testing involves using tools or scripts to execute test cases automatically, without human intervention. Automated regression testing is suitable for large-scale changes, repetitive testing, or testing stable or simple scenarios. Automated regression testing can save time, money, and resources, and improve accuracy and consistency.

5 How to select test cases for regression testing?

When selecting test cases for regression testing, it is essential to consider various techniques and criteria, such as impact analysis, risk analysis, prioritization, and optimization. Impact analysis involves identifying the areas or components affected by the changes and selecting the test cases that cover them. Risk analysis assesses the likelihood and severity of errors due to the changes and selects test cases that cover high-risk areas or components. Additionally, prioritization ranks test cases based on their importance, relevance, or complexity and selects those with the highest priority or value. Finally, optimization eliminates or reduces redundant, obsolete, or irrelevant test cases and selects the most optimal or sufficient ones.