LAUSR

Due to the effectiveness and efficiency in detecting defects caused by interactions of multiple factors, Combinatorial Testing (CT) has received considerable scholarly attention in the last decades. Despite numerous practical test case generation techniques being developed, there remains a paucity of studies addressing the automated oracle generation problem, which holds back the overall automation of CT. As a consequence, much human intervention is inevitable, which is time-consuming and error-prone. This costly manual task also restricts the application of higher testing strength, inhibiting the full exploitation of CT in industrial practice. To bridge the gap between test designs and fully automated test flows, and to extend the applicability of CT, this paper presents a novel CT methodology, named COMER, to enhance the traditional CT by accounting for Metamorphic Relations (MRs). COMER puts a high priority on generating pairs of test cases which match the input rules of MRs, i.e., the Metamorphic Group (MG), such that the correctness can be automatically determined by verifying whether the outputs of these test cases violate their MRs. As a result, COMER can not only satisfy the t-way coverage as what CT does, but also automatically check as many test oracle violations as possible. Several empirical studies conducted on 31 real-world software projects have shown that COMER increased the number of metamorphic groups by an average factor of 75.9 and also increased the failure detection rate by an average factor of 11.3, when compared with CT, while the overall number of test cases generated by COMER barely increased.