Automatic mutation based test data generation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Strong higher order mutation-based test data generation
Proceedings of the 19th ACM SIGSOFT symposium and the 13th European conference on Foundations of software engineering
Mutation based test case generation via a path selection strategy
Information and Software Technology
Mutation testing strategies using mutant classification
Proceedings of the 28th Annual ACM Symposium on Applied Computing
An orchestrated survey of methodologies for automated software test case generation
Journal of Systems and Software
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The automatic test case generation is the principal issue of the software testing activity. Dynamic symbolic execution appears to be a promising approach to this matter as it has been shown to be quite powerful in producing the sought tests. Despite its power, it has only been effectively applied to the entry level criteria of the structural criteria hierarchy such as branch testing. In this paper an extension of this technique is proposed in order to effectively generate test data based on mutation testing. The proposed approach conjoins program transformation and dynamic symbolic execution techniques in order to successfully automate the test generation process. The propositions made in this paper have been incorporated into an automated framework for producing mutation based test cases. Its evaluation on a set of benchmark programs suggests that it is able to produce tests capable of killing most of the non equivalent introduced mutants. The same study also provides some evidence that by employing efficient heuristics it can be possible to perform mutation with reasonable resources.