Gasser

Regression testing is an important activity that ensures a System Under Test (SUT) still works as expected after changes. Regression testing can be expensive in case of large Test Suites (TSs). Test Suite Reduction (TSR) approaches speed up regression testing by removing redundant test cases. These approaches can be classified as adequate or inadequate. Adequate approaches reduce TSs so that they completely preserve the test requirements (e.g., statement coverage) of the original TSs. Inadequate approaches produce reduced TSs that only partially preserve test requirements. An inadequate TSR approach is appealing when it leads to a higher reduction in TS size at the expense of a negligible loss in fault-detection capability. We defined an inadequate approach for TSR named GASSER (Genetic Algorithm for teSt SuitE Reduction). It is based on a multi-objective evolutionary algorithm, NSGA-II (Non-dominated Sorting Genetic Algorithm II). GASSER seeks to reduce TSs by maximizing both the statement coverage and diversity of test cases, and minimizing the size of the reduced TSs. We implemented GASSER in a Java prototype of a supporting tool and named it as the approach, namely GASSER. In this tooldemo paper, we present such a tool prototype as well as the results of a preliminary empirical study to assess the validity of both the approach and the tool prototype. A screen-cast of GASSER in action is available at https://youtu.be/20Uf1ugEvAQ.