A Lightweight Program Dependence based Approach to Concurrent Mutation Analysis

Mutation analysis is a classical software testing approach which attempts to imitate faults using a set of mutants. It has been advocated to be an appropriate technique for evaluating the quality of test suites as well as the effectiveness of a testing method. However, the applicability of mutation analysis, especially in many practical situations, has been hindered due to the high computation cost and the long execution time, which are mainly caused by the large number of mutants. Numerous studies, particularly those based on parallel computing, have been conducted to reduce the overhead of mutation analysis. In this paper, we aim to improve the efficiency of mutation analysis from a different perspective. We make use of lightweight program analysis techniques to identify a group of mutants that share the common execution traces before the mutation location, and then merge them into a synthesized program with the concurrent mechanism, on which mutation analysis can be efficiently executed without the duplicate execution of common traces. Our empirical study demonstrates that our approach can significantly decrease the computation overhead as well as shorten the execution time of mutation analysis, without jeopardizing its effectiveness. The in-depth analysis further shows that the effectiveness of our approach is positively correlated with the number of branches in the program under test. Our approach makes it possible to efficiently execute mutation analysis even without the need of advanced computer architectures.