A/B testing is a method of comparing two or more versions of a feature to evaluate their effectiveness. The goal of A/B testing is to determine which version better achieves set objectives, such as performance, user experience, or conversion rates. It also helps identify factors that influence user behavior.
Effective testing is crucial to ensuring the quality of deployed changes. Choosing the right approach for test execution helps optimize time and resource costs while minimizing risks associated with potential errors. This article examines two main approaches to test execution during deployment: running all tests (RunLocalTests) and running specific tests (RunSpecifiedTests). Each approach has its advantages and disadvantages, and the choice depends on the project’s current goals and CI/CD strategy.
The Test Coverage Matrix is a tool that tracks the relationship between test classes and the classes they cover, along with additional information such as coverage percentage, the date of the last test run, and comments. It is a vital tool for managing code quality, providing simplified access to test coverage data, and enabling change tracking.