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
An Empirical Evaluation of Three Defect-Detection Techniques
Proceedings of the 5th European Software Engineering Conference
Constructing test suites for interaction testing
Proceedings of the 25th International Conference on Software Engineering
An Investigation of the Applicability of Design of Experiments to Software Testing
SEW '02 Proceedings of the 27th Annual NASA Goddard Software Engineering Workshop (SEW-27'02)
Covering Arrays for Efficient Fault Characterization in Complex Configuration Spaces
IEEE Transactions on Software Engineering
HDD: hierarchical delta debugging
Proceedings of the 28th international conference on Software engineering
An evaluation of combination strategies for test case selection
Empirical Software Engineering
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)
Locating Errors Using ELAs, Covering Arrays, and Adaptive Testing Algorithms
SIAM Journal on Discrete Mathematics
The Minimal Failure-Causing Schema of Combinatorial Testing
ACM Transactions on Software Engineering and Methodology (TOSEM)
A software debugging method based on pairwise testing
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
Faulty interaction identification via constraint solving and optimization
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
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Combinatorial testing is a widely used black-box testing technique, which is used to detect failures caused by parameter interactions (we call them faulty interactions). Traditional combinatorial testing techniques provide fault detection, but most of them provide weak fault diagnosis. In this paper, we propose a new fault characterization method called faulty interaction characterization (FIC) and its binary search alternative FIC_BS to locate one failure-causing interaction in a single failing test case. In addition, we provide a tradeoff strategy of locating multiple faulty interactions in one test case. Our methods are based on adaptive black-box testing, in which test cases are generated based on outcomes of previous tests. For locating a t-way faulty interaction, the number of test cases used is at most k (for FIC) or t(dlog2 k] + 1) + 1 (for FIC_BS), where k is the number of parameters. Simulation experiments show that our method needs smaller number of adaptive test cases than most existing methods for locating randomly-generated faulty interactions. Yet it has stronger or equivalent ability of locating faulty interactions.