Orthogonal Latin squares: an application of experiment design to compiler testing
Communications of the ACM
Applying design of experiments to software testing: experience report
ICSE '97 Proceedings of the 19th international conference on Software engineering
Model-based testing in practice
Proceedings of the 21st 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)
A Measure for Component Interaction Test Coverage
AICCSA '01 Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications
Software Fault Interactions and Implications for Software Testing
IEEE Transactions on Software Engineering
Journal of Combinatorial Theory Series B
The density algorithm for pairwise interaction testing: Research Articles
Software Testing, Verification & Reliability
Iterative exhaustive pattern generation for logic testing
IBM Journal of Research and Development
Covering Arrays Avoiding Forbidden Edges
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
Covering arrays avoiding forbidden edges
Theoretical Computer Science
Locating Errors Using ELAs, Covering Arrays, and Adaptive Testing Algorithms
SIAM Journal on Discrete Mathematics
Characterizing failure-causing parameter interactions by adaptive testing
Proceedings of the 2011 International Symposium on Software Testing and Analysis
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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In this paper, we define error locating arrays (ELAs), which can be used to locate faulty interactions between parameters or components in a software system. We give constructions of ELAs based on covering arrays. Under certain assumptions on the structure of the faulty interactions, we design and analyse efficient algorithms that locate errors. Under the assumption of known "safe values", our algorithm performs a number of tests that is polynomial in log k and d, where k is the number of parameters in the system and d is an upper bound on the number of faulty pairwise interactions. For the binary alphabet case, we provide an algorithm that does not require safe values and runs in expected polynomial time in log k whenever d ∈ O(log log k).