Model based regression test reduction using dependence analysis

Abstract

Model based testing is a system testing technique used to test software systems modeled by formal description languages, e.g., an extended finite state machine (EFSM). System models are frequently changed because of specification changes. Selective test generation techniques are used to test the modified parts of the model. However, the size of regression test suites still may be very large. In this paper, we present a model-based regression testing approach that uses EFSM model dependence analysis to reduce regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. For each elementary modification, regression test reduction strategies are used to reduce the regression test suite based on EFSM dependence analysis. Our initial experience shows that the approach may significantly reduce the size of regression test suites.