Towards impact analysis of test goal prioritization on the efficient execution of automatically generated test suites based on state machines

Test prioritization aims at reducing test execution costs. There are several approaches to prioritize test cases based on collected data of previous test runs, e.g., in regression testing. In this paper, we present a new approach to test prioritization for efficient test execution that is focused on the artifacts used in model-based test generation from state machines. We propose heuristics for test goal prioritizations and evaluate them using two different test models. Our finding is that the prioritizations can have a positive impacton the test execution efficiency. This impact, however, is hard to predict for a concrete situation. Thus, the question for the general gain of test goal prioritizations is still open.