SUMMARYTools for automated fault localization usually generate too many bug candidates depending on the underlying technique. Hence, more information is required in order to further restrict the number of bug candidates. Approaches that rely on specific knowledge of the program to be debugged, such as variable values at specific positions in the source code, are not easily accessible for users especially in the case of software maintenance. In order to avoid this problem, we suggest integrating testing to restrict the number of bug candidates. In particular, we propose computing possible corrections of the program and from this distinguishing test cases. A distinguishing test case is a test that reveals different output values for two program variants given the same input values. Besides the formal definitions and algorithms, we extend the first empirical results of our approach in this paper. The obtained empirical results show that the use of mutations and distinguishing test cases reduces the number of bug candidates by more than 90% on average. Copyright © 2012 John Wiley & Sons, Ltd.

In mutation testing the question whether a mutant is equivalent to its program is important in order to compute the correct mutation score. Unfortunately, answering this question is not always possible and can hardly be obtained just by having a look at the program's structure. In this paper we introduce a method for solving the equivalent mutant problem using a constraint representation of the program and its mutant. In particularly the approach is based on distinguishing test cases, i.e., test inputs that force the program and its mutant to behave in a different way. Beside the foundations of the approach, in this paper we also present the algorithms and first empirical results

No abstract

Software testing, i.e., discovering software failures through test case execution, plays a crucial role in the software development process. A high quality software must have a strong test suite. Therefore it is of high importance for a software to evaluate the test suite that is asserting its correctness. Mutation testing is one efficient method to evaluate the process of software testing, i.e., the quality of the test suite.The current research focuses on mutation testing as a metric that can be used not only for establishing a reliable testing process, but also for improving the test case generation process, when the quality of the test suite is proven to be unsatisfactory. More over we aim to come with a solution to the equivalent mutant problem, by combing mutation testing and constraint systems.