Combining Multiple Coverage Criteria in Search-Based Unit Test Generation

peer reviewedAutomated test generation techniques typically aim at max- imising coverage of well-established structural criteria such as statement or branch coverage. In practice, generating tests only for one speci c criterion may not be su cient when testing object oriented classes, as standard structural coverage criteria do not fully capture the properties developers may desire of their unit test suites. For example, covering a large number of statements could be easily achieved by just calling the main method of a class; yet, a good unit test suite would consist of smaller unit tests invoking individual methods, and checking return values and states with test assertions. There are several di erent properties that test suites should exhibit, and a search-based test generator could easily be extended with additional tness functions to capture these properties. However, does search-based testing scale to combinations of multiple cri- teria, and what is the e ect on the size and coverage of the resulting test suites? To answer these questions, we extended the EvoSuite unit test generation tool to support combinations of multiple test criteria, de ned and implemented several di erent criteria, and applied combinations of criteria to a sample of 650 open source Java classes. Our experiments suggest that optimising for several criteria at the same time is feasible without increasing computational costs: When combining nine di erent criteria, we observed an average decrease of only 0.4% for the constituent coverage criteria, while the test suites may grow up to 70%