There’s only so much work you can do in each time-constrained sprint. As you advance in your testing practices, you accumulate large numbers of tests that can become difficult and time-consuming to maintain and execute.
Code changes and automated test runs may happen daily. Rerunning all these tests for each build slows down productivity. With AI-powered test impact analysis (TIA), you can see what code changed and only run those tests associated with the modifications, which speeds up productivity.
Watch this session to find out how visibility and traceability of tests to code coverage provide important insights to mitigate quality risks and drive efficiency. You’ll learn how to:
- Reduce the scope of re-testing by identifying and executing tests impacted by code changes.
- Collect and merge code coverage across multiple testing practices.
- View and analyze correlated test and code coverage data to identify gaps and risks.