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
A density-based greedy algorithm for higher strength covering arrays
Software Testing, Verification & Reliability
Covering arrays avoiding forbidden edges
Theoretical Computer Science
Iterative exhaustive pattern generation for logic testing
IBM Journal of Research and Development
Algorithms to locate errors using covering arrays
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
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In this paper, we define and study error locating arrays (ELAs), which can be used in software testing for locating faulty interactions among parameters or components in a system. We give constructions of ELAs for arbitrary strength $t$, based on covering arrays. We show that the number of tests given by ELAs grows as $O(\log k)$, where $k$ is the number of parameters/components in the system, assuming other quantities (the number $g$ of values per parameter, the strength $t$ of faulty interactions, and the number $d$ of faulty interactions) are bounded by a constant. We then give a series of results for the case of pairwise interactions ($t=2$). We study the computational complexity of deciding whether a graph describing the faulty pairwise interactions is “locatable.” We characterize the locatable graphs for the binary case ($g=2$). We design and analyze efficient algorithms that locate errors under certain assumptions on the structure of the faulty pairwise interactions. 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 $d\in O(\log\log k)$.