Automated tests that appear to fail randomly during a run for reasons not related to the changes being tested.
The process of selecting a subset of tests from a larger test suite, generally to run on a more frequent interval.
Using machine learning to determine which automated tests are most likely to fail based on code changes and selecting only those tests to run.
The process of moving testing earlier in the software delivery lifecycle so that defects can be identified and repaired before it becomes costly to fix them. The goal is to improve quality by moving QA tasks as early as possible.
Automated tests that exercise the major functionality of a system, but not comprehensively.
Using software to automate the selection of relevant tests based on code changes.
Splitting a test suite into multiple runs that execute in separate processes at the same time.
Low-level automated tests that exercise individual units of source code directly, written in the same language as production code.