Cost-Cognizant Combinatorial Test Case Prioritization

Combinatorial testing has been widely used in practice. People usually assume all test cases in combinatorial test suite will run completely. However, in many scenarios where combinatorial testing is needed, for example the regression testing, the entire combinatorial test suite is not run completely as a result of test resource constraints. To improve the efficiency of testing, combinatorial test case prioritization technique is required. For the scenario of regression testing, this paper proposes a new cost-cognizant combinatorial test case prioritization technique, which takes both combination weights and test costs into account. Here we propose a series of metrics with physical meaning, which assess the combinatorial coverage efficiency of test suite, to guide the prioritization of combinatorial test cases. And two heuristic test case prioritization algorithms, which are based on total and additional techniques respectively, are utilized in our technique. Simulation experimental results illustrate some properties and advantages of proposed technique.