The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
Simplifying and Isolating Failure-Inducing Input
IEEE Transactions on Software Engineering
Software Fault Interactions and Implications for Software Testing
IEEE Transactions on Software Engineering
Covering Arrays for Efficient Fault Characterization in Complex Configuration Spaces
IEEE Transactions on Software Engineering
Pseudo-Exhaustive Testing for Software
SEW '06 Proceedings of the 30th Annual IEEE/NASA Software Engineering Workshop
Conflict-driven answer set solving
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Algorithms to locate errors using covering arrays
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Adaptive Interaction Fault Location Based on Combinatorial Testing
QSIC '10 Proceedings of the 2010 10th International Conference on Quality Software
A survey of combinatorial testing
ACM Computing Surveys (CSUR)
Characterizing failure-causing parameter interactions by adaptive testing
Proceedings of the 2011 International Symposium on Software Testing and Analysis
A software debugging method based on pairwise testing
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
Identifying Failure-Inducing Combinations in a Combinatorial Test Set
ICST '12 Proceedings of the 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation
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Combinatorial testing (CT) is an important black-box testing method. In CT, the behavior of the system under test (SUT) is affected by several parameters/components. Then CT generates a combinatorial test suite. After the user executes a test suite and starts debugging, some test cases fail and some pass. From the perspective of a black box, the failures are caused by interaction of several parameters. It will be helpful if we can identify a small set of interacting parameters that caused the failures. This paper proposes a new automatic approach to identifying faulty interactions. It uses (pseudo-Boolean) constraint solving and optimization techniques to analyze the execution results of the combinatorial test suite. Experimental results show that the method is quite efficient and it can find faulty combinatorial interactions quickly. They also shed some light on the relation between the size of test suite and the ability of fault localization.